[From the U.S. Government Printing Office, www.gpo.gov]






                                                                                             DRAFT










                                          Economic Assessment of
                          Managing Coastal Erosion and Shore Protection







 C\r,                                                 Prepared by
                                           Douglas D. Ofiara, Program Manager
                                     Resource and Public Economics Working Group
                                          Institute of Marine & Coastal Sciences
                                                   Rutgers University



                                                      Prepared for
                                            Coastal Hazard Management Plant
                                             New Jersey's Shoreline Future

                                                      White Paper







                                                       July 1996









                                                                                             DRAFT










                                          Economic Assessment of
                         Managing Coastal Erosion and Shore Protection









                                                     Prepared by
                                          Douglas D. Ofiara, Program Manager
                                    Resource and Public Economics Working Group
                                         Institute of Marine & Coastal Sciences
                                                  Rutgers University




                                                     Prepared for
                                          Coastal Hazard Management Plant
                                            New Jersey's Shoreline Future

                                                     White Paper







                                                      July 1996






                                                                                                                         Draft - July
                                                                                                       Economics White Paper
                                                                         Contents


                                                                                                                                  Page


                     Executive Summary                .................................................................................... iii

                      Chapter I Introduction               ................................................................................I
                               Background         .......................................................................................I
                               Objectives         .........................................................................................4
                               References         ........................................................................................5


                   Chapter 2 - Economic Principles and Guidelines of Shore Protection:
                            A Primer        ...........................................................................................  6
                               Background         ...................................................................................... 6
                               Economic Measures               ...........................................................................6
                                        Aggregate Economic Activity                  ......................................................7
                                        Economic Impacts             ....................................................................7
                                        Benefits as Measures of Economic Value                         .....................................9
                                        Benefits in Cost-Benefit Analysis                  ............................................... 10
                               Economic Methods              ........................................................................... 11
                                        Present Value Analysis               ............................................................. 11
                                                  Cost-Effectiveness Analysis               ............................................. 12
                                                  Cost-Benefit Analysis             ...................................................... 13
                                        Economic Impact Analysis (Public Policy Analysis)                           ..................... 14
                                        Input-Output Analysis              .............................................................. 14
                                        Simulation Models            ................................................................... 16
                                        Risk-Return Decision Models                  .................................................... 16
                               References         ....................................................................................... 17



                     Chapter 3 - Economic Aspects of Shore Protection                             ...................... ................ 19
                               Introduction       .....................................................................................  19
                               Literature Review            .............................................................................N
                                        Economic Value of Beach Use and Shore Protection                             .................... 19
                                                  Curtis and Shows           .................................................  ......... 19
                                                  Bell and Leeworthy           .......................................................... 20
                                                  Lindsay and Tupper            ................................................* ........ 25
                                                  Silberman et al         ................................................................ 26
                                                   ACOE Reports             ............................................................. 29
                                                  Koppel and Kucharski              ..................................................   ..29


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                                                                                                                         Draft - July
                                                                                                       Economics White Paper
                                       Beaches, Tourism and Economic Development                              ........................... 32
                                                 Stronge      ......................................................................... 33
                                                 Houston      ...................i .................................................... 34
                                                 Bell and Leeworthy             ......................................................... 35
                                                 Manheim and Tyrrell              ....................................................... 37
                                       ACOE Studies of Shore Protection                      ............................................ 37
                                      Expenditures and Impacts of Tourism on the NJ Shore                               ................ 41
                                                 RL Associates          ................................................................ 42
                                                 Opinion Research Corporation                  .......................................... 42
                                                 Longwoods Int'l           ............................................................. 43
                                      Shore Protection Policy Oriented Studies                       ..................................... 53
                                                 NJ Shore Protection Master Plan                   ...................................... 53


                                                                       Contents


                                                                                                                                 Page

                                                 ICF Report        .................................................................... 56
                                                 Assessments of ACOE Projects                     ....................................... 60
                                                 ACOE Self-Study             ........................................................... 61
                                                 NRC Study of Beach Nourishment                       ................................... 61
                              Characteristics of Typical Beach Fill Projects in New Jersey                             ................. 62
                              Policy Recommendations                 ................................................................... 66
                              Summary        ......................................................................................... 66
                              Recommendations for Further Study                        ................................................... 67
                              References       ....................................................................................... 68
                              Appendix Table I            .............................................................................. 72
                              Appendix Table 2            .............................................................................. 81
                              Appendix Table 3            .............................................................................. 86














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                                                    EXECUTIVE SUMMARY



                 PRIMER ON ECONOMIC MEASURES & ECONOMIC METHODS:


                     ECONOMIC MEASURES:
                         National Income Accounting measures of aggregate economic activity are usually
                         referred to as GDP (Gross Domestic Product) or GNP (Gross National Product). These
                         measures represent the total value of all final goods and services produced in an
                         economy for a given time period, usually a year. Because prices can change over time,
                         the above measures must be adjusted to yield real GDP (gdp), real GNP (gnp), which
                         then represent the value of all final goods and services produced in an economy in terms
                         of constant dollars. As such, changes in gdp/gnp will now reflect changes in real output.
                         Because only final goods and services are considered rather than including sales of used
                         goods and sales of intermediate goods, measures of GDP avoid the problem of double-
                         counting economic activity, a main advantage of these measures; this report will treat
                         national accounting measures as representing measures of "true" economic activity.

                         Economic impacts are not to be confused with economic benefits, they represent
                         different measures of economic activity. Impacts measure the amount of aggregate
                         economic activity usually in terms of sales, income, employment, and sometimes tax
                         revenues that are associated with some type of change to the economy (structural
                         change - plant closing, reduced demand) or policy change (proposed regulation). Many
                         times they are based on multipliers that not only account for direct effects (effects on
                         primary and secondary sectors only), but also indirect and induced effects. Most
                         individuals are familiar with "expenditure impacts," reported in the news media, that is,
                         impacts of consumer/tourism spending. Measures of economic activity as represented
                         by economic impacts involve double-counting when compared to the true measure of
                         aggregate economic activity, GDP; impact measures overstate the true measure of
                         economic activity (GDP). Without evidence of the magnitude of the error involved (the
                         magnitude that impacts overstate GDP) one must exercise caution in the interpretation
                         and use of these measures. Above all they should not be used alone, but in conjunction
                         with other measures in economic justifications of economic development, promotion,
                         etc.


                         Economic benefits in the context of economic welfare theory are associated with the
                         monetary value of specific measures of changes in economic welfare. These measures
                         are associated with losses or gains in economic welfare and represent lost economic
                         value and gains in economic value, respectively. In the production sector, the measure
                         of lost (gains in) economic value is economic rents (or simply rents), i.e., the reduction
                         (gains) in profits and producer surplus. Producer surplus is a measure of the net
                         economic value to the producer from the production and sale of goods and. services. In
                         the consumption sector, a measure of lost (gains in) economic value is the reduction


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                         (gain) in consumer surplus, a monetary surplus that accrues to the consumer over and
                         above expenditures from consumption of a good. It represents a net economic value that
                         accrues to consumers from consumption activities. Any reduction (gain) in it can be
                         considered a loss (gain) in economic value. Aggregate economic benefits are the sum of
                         changes in the value of economic welfare to all agents involved (e.g., consumer and
                         producer). Net benefits are the difference between economic benefits (both direct and
                         indirect) that would accrue to a project and the costs of implementing the project.

                         Economic benefits in the context of Cost-Benefit Analysis represent different measures
                         compared to those of welfare economics. Here, benefits refer to all gains in economic
                         value (welfare part) and gains in economic activity (e.g., increases in sales, income,
                         employment, etc.) that directly and indirectly result from the proposed project. Cost-
                         savings are sometimes included in CBA benefit measures. Hence, benefits in a CBA
                         context comprise economic value and economic impact benefit measures. However, care
                         must be exercised to avoid double-counting of benefit measures.


                     ECONOMIC METHODS:


                         Cost-Effectiveness Analysis concerns the minimum cost option to achieve a given
                         objective. It ignores benefits and does not address economic rationale to achieve a given
                         objective. It is appropriate when considering how a project can be implemented in the
                         least expensive way. The procedure is to estimate all costs for a particular option over
                         time, discount these costs, and then sum the discounted costs (discounted costs
                         represent the total cost in today's dollars); the sum of discounted costs is referred to as
                         present value of costs. The decision criterion is to select that project with the smallest
                         present value of costs over time.

                         Cost-Benefit Analysis (CBA) is the primary method in which both the benefits and
                         costs associated with a project are considered. It is based on economic justifications in
                         determining the implementation of a project; that is, whether the outcome of a project is
                         worth the costs of achieving it. Here the analyst must identify and then measure all
                         possible benefits and costs associated with the presence of the project as opposed to a
                         situation without the project. This technique has two variations commonly used. One
                         is to examine the difference among benefits and costs (benefits less costs) for each time
                         period, discount it, and then sum it, giving the present value of net benefits over time.
                         The present value of net benefits is the appropriate measure for comparing projects over
                         time given equal scale (size) and time period. The decision criterion is to select that
                         project that yields the maximum present value of net benefits over time. The second
                         version is the B/C ratio, where the discounted sum of benefits is divided by the sum of
                         discounted costs. When benefits equal costs this ratio will equal 1. The decision
                         criterion is to select that project that yields the maximum B/C ratio. The use of this
                         ratio is quite controversial even among economists. Most would agree that selecting a
                         project based solely on the B/C ratio is inappropriate.


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                      ECONOMIC IMPACT ANALYSIS (PUBLIC POLICY ANALYSIS):

                          Economic Impact Analysis (EIA) also needs clarification. Many applied policy
                          problems and proposed federal regulations use variations of EIA, where it is referred to
                          as Public Policy Analysis. Here the analyst conducts an economic analysis to determine
                          the effects (impacts) of proposed policy changes, where the economic effects associated
                          with the policy are identified and quantified. These effects are not the same as

                          measures.


                  Economic Input-Output Analysis (1-0) is a specific technique based on an economic input-
                      output model. It uses aggregate measures of economic activity such as sales revenues,
                      income, and employment related to an economy defined by geographic-political boundaries
                      (a state, region, nation). A main feature of this technique is to determine "multipliers"
                      which can be thought of as how changes in primary economic activity translates into final
                      economic activity. Then, one can examine how changes in specific sectors (manufacturing,
                      services, etc.) affect the entire economy in question. 1-0 analysis was primarily developed
                      to address policy questions such as what are the effects on sales, income, and employment
                      that are associated with some type of change to the economy (structural change - plant
                      closings, reduced demand) or policy change (proposed regulation).          Simulation Models
                          Simulation models are hypothetical computer models written in either primary
                          computer code or in a simulation language to represent (mimic) an actual situation and to
                          then simulate the specific application and changes to it. They have been used in
                          epidemiology to simulate the spread of an actual disease epidemic. It has been used in
                          population ecology to simulate population dynamics and the actual spread of an insect
                          population outbreak and the effects of different control strategies.             And some
                          applications have been based on bio-economic models of fisheries.

                      RISK-RETURN DECISION MODELS


                          Risk-Retum models are from the field of finance and consist of the applications of
                          portfolio theory, risk-mean variance models, and variations of the capital asset pricing
                          model. They are used to decide among tradeoffs between risk and return so as to
                          determine an efficient portfolio of holdings (least risky collection of assets that yield the
                          greatest return) for various risk levels.       These models are highly complex and
                          indispensable to analysts and researchers in financial markets.


                 ECONOMIC ASPECTS OF BEACH USE AND SHORE PROTECTION:


                      ECONOMIC VALUE OF BEACH USE AND SHORE PROTECTION:
                      A range of the estimated average net economic value associated with beach protection was
                      derived from several studies for the purposes of this report yielding a low estimate of net


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                     econorruc value of $.35/person per day in 1992 dollars, and a high estimate of $39/person
                     per day in 1992 dollars; a range from $.35/person per day-trip to $.39/person per day-trip
                     in 1992 dollars.


                     BEACHES, TOURISM AND ECONOMIC DEVELOPMENT:
                     Notwithstanding that the nature of tourism in coastal areas can create impact effects
                     (spending effects over and above residents' spending) and possibly contribute to economic
                     development if the tourism effect is large enough, several shortcomings of the papers
                     reviewed weaken their results. These limitations differ by paper and include the following:
                     1) in several papers projected economic impacts were misinterpreted as aggregate economic
                     .activity measures (i.e., GDP); 2) the estimated participation rate of beach use in one paper
                     was based on a misleading procedure that could have introduced an upward bias in the
                     projected estimates of coastal tourism spending and impacts; 3) another paper used
                     statistics from secondary, unofficial sources -- such statistics can be quite misleading and
                     the potential bias and error inherent in secondary source statistics limits the accuracy and
                     usefulness of any research based on such data; 4) other miscellaneous limitations concern
                     the research design, the survey design, interpretation. of expenditure data and impact
                     estimates, derivation of impact estimates, sample size and representativeness of sample
                     data.    Because projected expenses of beach use can become easily inflated and
                     unrepresentative, the limitations and results found in the studies reviewed raise a general
                     word of caution for research in this area. Future studies should be rigorous, based on
                     accepted research approaches and designs, and use appropriate statistical data, otherwise
                     results will be of little use and will only cloud the issue of the relative economic importance
                     of coastal tourism vis a vis investment in shore protection.


                EXPENDITURES AND IMPACTS OF TOURISM ON THE NJ SHORE


                        The usefulness of the Longwoods study is in the generation of projected direct
                expenditures discussed above and not in economic impacts. Direct expenditures represent the
                closest activity to aggregate GNP estimates, because they represent the sales of final goods and
                services sold, and do not contain double-counting. Regarding coastal tourism, the Barrier Island
                (long-term beach rentals)(LTBR) component of the Longwoods study represents only one
                segment of beach travel and underestimates the importance and magnitude of tourism
                expenditure activity (expenditures other than LTBR) in the coastal region of New Jersey. To
                develop an estimate of all expenditures associated with beach travel, similar estimates for day
                trips and other overnight trips (i.e., hotel/motel/resort, campgrounds-private and public, and
                those that stay with friends/relatives) for the four-coastal counties are necessary. On the basis
                of the estimated number of trips and the estimated average trip expense, an upper bound for
                expenditures of all beach-related travel was estimated at $2,095.877 million ($1,917.92 million
                without gambling (by long-term renters)) for 1993. The Barrier Island (LTBR) component
                represented 41.74% of the 1993 estimated tourist              beach-related expenditures.       If this
                proportion is representative across other years, the three-year (1992-94) estimated average
                expense for beach trips would account for an estimated $1,887.64 million average/year (45.57%


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                 of the estimated total) and an estimated $1,726.75 million average/year without gambling in
                 1992 dollars. However, the reader is cautioned in reading too much into these estimates; they
                 were developed for illustrative purposes. Little confidence can be placed in the estimates; such
                 estimates should be developed from a single sample base rather than from two, and should be
                 developed as part of an objective of the travel and tourism studies in the form of a range. The
                 estimates developed are meant to illustrate the point that projected tourism expenses associated
                 with beach trips based on the Barrier Island component are underestimates of such activity,
                 whereas the county-level estimates of the four-coastal counties are overestimates of beach-
                 related economic activity. The derived estimate, $1,887.64 million average/year over the 1992-
                 94 period in 1992 dollars, represents 18% of the four-coastal county three-year average, and
                 9.8% of the state three-year average (without gambling expenditures the estimate is $1726.75
                 million/year representing 23.8% of the 4-coastal county 3-year average, and 10.5% of the 3-year
                 state average). In 1993, the LTBR and other beach. expenditures for the four coastal counties
                 totaled about $2.0 billion; gambling expenditures at Atlantic City totaled $3.2 billion. Thus,
                 beach-related tourism and recreation plus gambling accounted for more than half of the $9.7
                 billion of tourism expenditures in the four coastal counties in 1993. These values are estimates
                 from the data reported in the Longwoods study and represent the approximate role of beach
                 recreation and tourism in New Jersey. Further effort should be directed to incorporate beach-
                 related information in future Longwoods studies.


                    SHORE PROTECTION POLICY ORIENTED STUDIES:


                    The Cost-Benefit Analysis (CBA) performed in the New Jersey Shore Protection Master
                    Plan (NJSPMP) is basically static, although some attempt was made to incorporate changes
                    that occur over time, namely estimates of future beach use and estimates of future property
                    lost or damaged. No attempt was made to incorporate any other dynarnic.elements nor the
                    risk associated with the expected outcome of the projects, where one could introduce
                    uncertainty into the derivation of net benefits (benefits less costs). A dynamic analysis
                    would compare and contrast the monetary value of a projects' outcome if completely
                    certain versus that with the presence of uncertainty. In the case of beach protection,
                    possible risk factors could involve such effects as erosion and storm damage that could
                    cause any project from not being 100% completed, uncertainty over available funds to
                    ensure 100% completion of any project over the planning period, and uncertainty over the
                    estimated number of ftiture beach users, and the value of estimated future property
                    structures lost versus protected.. Probably the most serious fault is the problem @of
                    downward bias in both the cost and benefit estimates which would tend to introduce either
                    an upward bias or a downward bias in the magnitude of the B/C ratio, respectively,
                    distorting the B/C ratio. The net effect is ambiguous, but places concern over the validity
                    and accuracy of the CBA in the NJSPMP.

                    Policy findings of the ICF (1989) study conducted for the New England/New York Coastal
                    Zone Task Force were the following: 1) "new" development in coastal floodplains was
                    found to be a net cost to governments, "existing" development in many cases was worth


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                    protecting; 2) the "best" policy response was found to depend on the following factors a)
                    the existing level of development, b) costs from damage, and c) magnitude of revenues
                    gained; 2.a) in areas that are relatively less-developed, beach nourishment was found to be a
                    viable policy; 2.b) in areas with high levels of development, protection via dikes was found
                    to be a viable policy where large amounts of property could be damaged and where dike
                    building could be coupled with a policy of halting further development; 3) optimal policies
                    differed over time; and 4) the use of subsidies, e.g., NFIP, was found to have important
                    consequences on development (in the promotion of development).
                    Policy recommendations offered by ICF (1989) were for two categories, 1) future
                    development, and 2) existing development.           Concerning future development, ICF
                    recommended that: 1) continued large-scale development would be a net cost to
                    governments (costs greater than revenues); 2) NFIP should tighten the availability of flood
                    insurance to discourage future development (such action would have an effect similar to one
                    where property owners are charged the full costs of flood insurance); 3) policies should be
                    implemented whereby property owners are charged the full costs of cleanup and repairs; 4)
                    policies should be designed to prohibit reconstruction of structures and land should be
                    rezoned following significant storin damage (e.g., when 50% or more of a structure is
                    damaged); and 5) governments should establish future policies on shore protection and
                    announce these to the public (the idea is that if governments pre-committ to a policy of no
                    provision of shore protection in areas facing "new" development, this will create
                    disincentives for future development and cause property-owners to internalize and bear the
                    full costs of damage and cleanup).

                    Regarding existing development, ICF admits that policy choice "is not an easy answer,"
                    (ICF 1987:60). Recommended policy options were found to depend on development levels;
                    in areas with high levels of development it was recommended that policies protect existing
                    structures,, whereas in areas with low levels of development, policies of protection were not
                    recommended, but recommendations of property acquisition, rezoning, tightening of
                    insurance, and having owners assume the full costs of damage and cleanup and accept losses
                    of capital investment in buildings and from losses of the tax base were.



                    OVERALL SUNEVLARY:


                    The basic issue one would like to address concerns whether the deposition of sand on the
                    beach generates tourism and/or economic benefits. One can think of the coastal zone as a
                    kind of "economic engine" in the sense that the coastal zone generates economic activity,
                    such as income, sales, and jobs via tourism and businesses that are water-dependent and/or
                    require to be located in close proximity to the coastal area.       The above studies and
                    investigators attempt to address different components of the beach fill - economic activity
                    question. However, because the above studies are based on different research and sampling
                    designs, and have different objectives, the data and results are too fragmented for one to
                    develop reliable estimates of economic activity. This means that the data from the literature


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                    are inadequate to develop point estimates of the magnitude of the economic activity
                    associated with the coastal zone. Furthermore, studies that have tried to estimate the level
                    of activity from coastal tourism have tended to ignore the effect of beach nourishment on
                    coastal tourism activity. Data from the above coastal tourism studies are inappropriate to
                    address the issue of whether beach nourishment projects on their own, generate economic
                    activity. In order to isolate and address the issue, investigators must develop studies that
                    incorporate research designs to isolate economic activity dependent on the coastal zone
                    and/or on specific beach nourishment projects. Such studies may require data on economic
                    activity and tourism expenditures that are location-specific, in terms of the relative
                    proximity to the shoreline, and to beach nourishment projects, and be collected on a
                    seasonal basis. Such data is sensitive and generally hard to collect. However, without it one
                    may not be able to advance beyond the current level of analysis and findings,


                    RECOMMENDATIONS FOR FURTHER STUDY:


                        a variety of economic techniques such as CBA, Input-Output models, simulation
                        models, risk-return models, and other relevant economic approaches needs to be
                        explored to determine their relative importance and usefulness in policy-oriented studies
                        of shore protection and in their assessment of tradeoffs among the policy options to
                        determine whether or not all economic techniques provide similar policy
                        recommendations (there is a possibility that different policy outcomes could result from
                        different techniques because the techniques emphasize different criteria and
                        information);

                        the building of pertinent databases, which involves the collection and development of
                        appropriate data necessary to specific economic approaches will be dependent on the
                        specific approach and can be a very lengthy process. Some of these data can be gathered
                        from the respective ACOE districts (especially for inventory surveys of physical
                        structures), some will involve statistics and data generated from the state government;

                        future studies with research designs to isolate and identify economic activity dependent
                        on the coastal zone and/or on specific beach nourishment projects. Such studies may
                        require data on economic activity and tourism expenditures that are location-specific, in
                        terms of the relative proximity to the shoreline, and to beach nourishment projects, and
                        be collected on a seasonal basis;


                        resources recommended for support of economic studies are estimated to be in the
                        $100,000 to $150,000 range depending on the 1) time frmne, 2) economic method, 3)
                        range and detail of alternative policy options to be assessed, 4) treatment of.risk and
                        uncertainty, and 5) level of detail required of the data. However, such an estimate could
                        quickly become a lower bound range involving a team approach of economists and
                        expenses of $75,000 - $ 1 00,000/year for several years;



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                        the ICF (1989) study is an exercise that demonstrated the complexity of the issues
                        involved in public policy tradeoffs. However, this is the tip of the iceberg; an analysis
                        should be intertemporal rather than static; performing an analysis that is intertemporal
                        and involves many cost and benefit components is an extremely tedious and complex
                        task; resources of time and funding must match the complexity of the problem;

                        the analysis must incorporate the elements and effects of uncertainty in benefit and cost
                        estimates since these depend on the probability of storm occurrence as well as the
                        magnitude of the storm; hence cost and benefit items are stochastic in nature and vary
                        according to storm severity, time, and sea-level rise, with sea-level rise magnifying the
                        risk elements and the effects of erosion and storm damage;

                        the analysis must also incorporate the element of risk associated with project failure and
                        outcome; and


                        the ICF (1989) demonstrated that there are many more elements to consider regarding
                        policy tradeoffs (level of development, future vs. existing development, level of erosion,
                        storm-events, availability of flood insurance, who should bear the burden of flood
                        insurance and that of cleanup and repair costs, land rezoning issues, reconstruction
                        policies, and future shore protection policy stances); future analysis must be designed to
                        incorporate these numerous and varied elements.


























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                                                                                      Contents


                                                                                                                                                          Page


                                                       NRS Study of Beach Nourishment                     ...........................................I
                                  Characteristics of Typical Beach Fill Projects in New Jersey                           ...............................I
                                  Policy Recommendations                 ........................................................................I
                                  Summary       ...........................................................................................I
                                  R ecommendations for Further Study                   ...........................................................I
                                  References      .........................................................................................I
                                  Appendix Table I          .................................................................................I
                                  Appendix Table 2          .................................................................................I
                                  Appendix Table 3          ..................................................................................I


                       Technical Appendix I - Shore Protection Efforts in New Jersey: Three Decades of Shore
                       Protection     ...................................................................................................I
                                  Background       .......................................................................................I
                                  History of Soft Protection Projects               .............................................................I
                                             Middlesex County            ........................................................................I
                                             Monmouth County             ......................................................................1
                                             Atlantic County        ..........................................................................1
                                             Ocean County         ............................................................................I
                                             Cape May County             .......................................................................I
                                             Summary - Soft Protection Projects                 ...................................................1
                                  History of Hard Protection Projects                 ............................................................I
                                             .Middlesex County           .......................................................................I
                                             Monmouth County             ......................................................................I
                                             Atlantic County        ..........................................................................I
                                             Ocean County         ............................................................................I
                                             Cape May County             .......................................................................I
                                             Summary - Hard Protection Projects                  .................................................I
                                  Summary - Shore Protection Projects in New Jersey                          ........................................I
                                  References      .........................................................................................I













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                                                       Chapter I - Introduction


                                                              Background
                Coastlines have been described as fragile ecosystems that are susceptible to continual erosion
                processes from natural forces, e.g., tides, currents, storms. If left unabetted the natural process of
                coastal erosion will change the natural configuration of coastlines (e.g., peninsulas, barrier
                islands) through a process of attrition sinuilar in nature to a continually depreciating resource/asset.
                If nothing is done to slow or maintain the erosion rate, the asset physically decreases over time,
                similar to a storage technology with depreciation. In the case of a coastline, the physical
                characteristic of this boundary changes over time (i.e., spatial dimensions), decreasing in some
                areas and increasing in others.


                Prior to man's development of these coastal areas, the natural process of erosion posed relatively
                little problem. There was little economic development to warrant public protection and intervention
                a century ago compared to modem times. Presently, where t         'he coastal zone is undeveloped the
                process of erosion creates few problems other than the shoaling of tidal inlets and navigable water-
                ways. But, where widespread and extensive economic development has occurred involving both
                public and private investment, a new and continual problem has emerged. The issue of shoreline
                protection is to slow the natural process of attrition (decay), and to minimize the physical and
                economic damage that can occur to shorelines, as well as to physical structures and to
                infrastructure (i.e., roadways, sewer lines, utility lines, etc) in close proximity to the shoreline.
                Over time, oceanfront real estate has become closer to the water and is threatened from storm
                surges. Private individuals and small communities, in turn, demand protection and assistance from
                government authorities for a location and investment decision that has become susceptible to the
                natural process of coastal 'erosion and storm-events. Had such problems been foreseen and had
                zoning and federally-subsidized flood insurance (through the National Flood Insurance Program,
                NFIP) been designed to discourage economic development, the problem of coastal protection
                might have been avoided or lessened and, in turn, either minimized or eliminated a now necessary
                public service (ICF 1989, noted that the NFIP had important consequences on development, i.e.,
                in its promotion). However, over time, given society's preferences and patterns of location and
                development, this problem was probably inevitable. Furthermore, the occurrence of sea-level rise
                will continue to subject different areas of land to the threat of coastal erosion and storm damage.


                Detrimental effects on specific economic activities occur as a result of physical damage or loss of
                shoreline and property structures in close proximity to the shoreline, from both long-term erosion
                and short-term erosion associated with storm-events. Many of these effects can be classified as
                supply effects; i.e., changes that reduce the abundance (number, quantity, or spatial dimensions
                (length, width)) of beachfront property, beaches, and the coast in general. Effects on the demand

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               for locations in close proximity to the shoreline (i.e., physical property), and on activities
               involving such locations (e.g., recreational beach use, birding, fishing, etc.) can also occur due to
               repeated and one-time physical damage and shoreline loss. However, detrimental effects seem to
               have a perverse effect on such demand behavior, in that demand has usually increased over time no
               matter what the detrimental effect or loss is. Property values have usually risen over time the
               closer properties are to the shoreline.


               Regarding coastal tourism, precise estimates of New Jersey's coastal tourism industry are
               unavailable. Estimates developed by Longwoods Int'l. can give some idea of the range of its
               magnitude. For the Barrier Island component, an estimated average over the three-year period
               1992-94 was $787.9 million a year ($786.88 million/year without gambling expenses) in 1992
               dollars. However, this estimate only represents one component of beach travel and tourism
               activity (i.e., that portion of tourists that rented accommodations along the Jersey Shore), and
               underestimates the importance and magnitude of tourism expenditure activity in the coastal region
               of New Jersey (other components of beach travel consist of other overnight trips and day trips).
               On the basis of the estimated number of trips and the estimated average trip expense, an upper
               bound estimate of the three-year average (1992-94) expenditure of A beach related travel was
               estimated at $1,887.64 million a year ($1,726.75 million/year without gambling expenses).
               However, the reader is cautioned in reading too much into these estimates; they were developed for
               illustrative purposes. Little confidence can be placed in the estimates; such estimates should be
               developed from a single sample base rather than from two, and should be developed as part of an
               objective of the travel and tourism studies in the form of a range. The estimates developed are
               meant to illustrate the point that projected tourism expenses associated with beach trips based on
               the Barrier Island component are u.nderestimates of such activity, while the county-level estimates
               of the four coastal counties are overestimates.


               New Jersey's coastal tourism industry depends closely on the actual and perceived condition of the
               shoreline both in terms of the effects of erosion and the effects of marine pollution. For example,
               Ofiara and Brown (1989), using the number of beach tags sold as a proxy for beach attendance,
               found a decrease in beach tag sales at public beaches in New Jersey that ranged from 7.9% to 34%,
               from 1988 marine pollution events. Both processes of coastal erosion and marine pollution, in
               turn, can adversely effect the state's coastal economic activity. Ofiara and Brown (1989) estimated
               direct economic losses from the 1988 marine pollution events that ranged from $820.7 million to
               $3,060.8 million to the State of New Jersey. Thus, any protection of the shoreline and water
               quality, in turn, will maintain the econornic return of the state's coastal tourism industry. One can
               think of this physical asset, the coastal zone as generating economic returns in terms of jobs,
               income, sales, and tax revenues. Any decrease or lessening of this coastal area could adversely
               affect travel and tourism to the area (direct effects) and in turn, economic returns (indirect effects).

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                Economic analyses of policies concerning the management of coastal erosion can become
                increasingly complex given real world scenarios. Shore protection is complicated due to risk
                associated with the expected life of a project which can vary across projects, as well as, expected
                returns associated with each project that, too, can vary across projects. Furthermore, coastal
                shorelines, and hence, shore protection projects are also subject to exogenous risk due to such
                factors as the geographic location, physical characteristics of the shoreline, weather patterns, and
                storm activity and intensity, where over a sufficiently long time period episodes can be identified
                and categorized that range from periods/occurrences of high risk (i.e., high storm activity) to
                periods of low risk (low storm activity), and from sea-level rise. As one might expect, a project
                undertaken during periods of low risk would have the longest expected life (defined as the
                difference between the projected life measured in years and the actual time a new project must be
                implemented for the same coastal location), and greatest economic return compared to initiating the
                same project during a period of high risk. However, shore protection must be in place before
                periods of high risk are expected to occur just to maintain the coastal area; these projects could be
                treated as one-time emergency projects only to last the life of the current storm activity. The effect
                of sea-level rise could magnify both the above risk factors, and the effects of erosion and storm
                damage.


                Ideally, one would like to conduct a welfare analysis (i.e., a first-best analysis) of alternative
                policy options of shore protection based on benefit data (i.e., measures of the values of society's
                welfare associated with different policies), but such an approach becomes untractable. These data
                are not readily available, and concerning recreational use and nonuse values, costly field surveys
                are necessary and sometimes involve highly controversial economic techniques. Furthen-nore,
                aggregation problems exist that involve many individuals with different tastes so that determining
                some type of benefit function that would depend on the utility of these individuals given altemative
                policy options becomes highly complex.


                In the absence. of a first-best approach, the most common technique used in economic analyses of
                shore, protection policies is Cost-Benefit Analysis (CBA), a second-best approach, for a variety -of
                reasons. Using such an approach, the investigator can determine the ranking of each project in a
                particular year with the decision-rule to fund those projects that yield the greatest net economic
                benefits/returns until the program funds are exhausted (a similar criteria was used in the 1981 New
                Jersey Shore Protection Master Plan). This process could be repeated each year. However, CBA
                has several limitations that may prove unrealistic. Some limitations of CBA are that it assumes that
                benefits are measurable and can be accurately measured, which for nonmarket goods such as beach
                use, benefits usually are not explicitly measurable and are subject to measurement error.
                Comparisons can only be made across projects that yield equal net benefits, and CBA is further

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              limited due to its association with welfare or pareto criteria; projects which yield a pareto
              improvement will be unanimously superior to all other projects, but one can say little about any
              two projects which yield the same social welfare without further assumptions about distributional
              aspects of the projects to members of society (i.e., assumptions regarding equity across society).
              Furthermore, the treatment of risk and uncertainty creates additional complications for CBA
              (detailed discussion is contained in Chapter 2.) However, in spite of its shortcomings, and in lieu
              of perhaps "better" approaches, CBA is widely used and provides practical decision rules for
              public officials that face public policy decisions.




                                                           Objectives,
              The purpose of this report is to address and examine both the economic issues and the economic
              theory relating to the management of coastal erosion, from the dual perspective of coastal erosion
              processes and the public provision of shore protection. It is meant to explore the issues involved
              in shore protection decision-making that must be considered in the preparation of a new Coastal
              Hazard Management Plan. In this regard, this report also summarizes characteristics of typical
              beach fill projects in New Jersey during the 1960-94 period from which economic analyses could
              be perfon-ned.


              Specific objectives are to: 1) examine the economic theory and economic techniques that can aid in
              understanding and evaluating shore protection policy and coastal erosion issues; 2) provide a
              review and assessment of shore protection efforts over the 1960-94 period; 3) review all pertinent
              literature concerning economics and shore protection, recreational beach use and benefits of shore
              protection, coastal tourism, the New Jersey Shore Protection Master Plan (NJSPMP) pertaining to
              its economic analysis, U.S. Army Corps of Engineers (ACOE) studies, and any relevant policy
              evaluations of shore protection; 4) summarize characteristics of typical beach fill projects in New
              Jersey during the 1960-94 period from which economic analyses could be performed; and 5)
              provide future directions and recommendations.


              The plan of this report is as follows. The pertinent economic theory and techniques are contained
              in Chapter 2. Chapter 2 is meant is to serve as a self-contained primer on economic principles and
              guidelines, and Cost-Benefit Analysis (CBA) useful in evaluating shore protection policy and
              coastal erosion issues. A technical appendix contains an overview of three decades of shore
              protection efforts in New Jersey (1960-94). It is meant to form a base from which economic
              analyses could be performed. The last chapter, Chapter 3, contains a detailed review of the
              economic literature relating to the economic value of beach use and beach protection, coastal
              tourism, and public policy issues of shore protection. The economic component of the NJSPMP is

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                reviewed here, as are ACOE studies and policy oriented studies of shore protection. In addition,
                characteristics of typical beach fill projects in New Jersey over the 1960-94 period are sununarized
                in Chapter 3. A contribution of this report is the discussion of appropriate economic issues,
                theory, and methods useful in examining the joint issues of shore protection and managing coastal
                erosion, and of current economic studies and analyses of beach use and shore protection. Such
                material was lacking in the NJSPMP. A detailed and thorough analysis of alternative policy
                options must be deferred to future efforts.





                                                            References
                ICF, Inc.    1989. Developing Policies to Improve the Effectiveness of Coastal Flood Plain
                Mana2ement. Executive Summary to New England/New York Coastal Zone Task Force, Fairfax,
                VA, July.


                Longwoods, Int'l. 1994a. The Economic Impact, Performance and Profile of the New Jersey
                Travel and Tourism Indust[y. 1992-93. Prepared for NJ Division of Travel and Tourism,
                Trenton, NJ, September.

                Longwoods, Int'l. 1995. The Economic Impact, Performance and Profile of the New Jersa
                Travel and Tourism Industry, 1993-94. Prepared for NJ Division of Travel and Tourism,
                Trenton, NJ, June.

                Ofiara, D.D. and B. Brown. 1989. "Marine Pollution Events of 1988 and their Effects on Travel,
                Tourism and Recreational Activities in New Jersey." Ln L.R. Swanson, (ed.) 1989. Proceedings
                from the Conference on Floatable Wastes ig-the Ocean: Social, Economic and Public Health
                I=lications. SUNY Sea Grant Program, Stony Brook, NY.

                NJDEP, DCR. 198 1. New Jersey Shore Protection Master Plan. Prepared by Dames and Moore.
                Prepared for Division of Coastal Resources, NJDEP, Trenton, NJ.





















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                        Chapter 2 - Econorruic Principles and Guidelines of Shore Protection: A Primer



                                                          Background
              Throughout this chapter several terms and concepts will be used to describe detrimental economic
              effects and associated measures of lost economic value attributable to coastal erosion, as well as
              beneficial economic effects and associated measures of gains in economic value attributable to
              shore protection efforts. Such a discussion will give the reader perspective in understanding and
              identifying benefits and losses that can result from shore protection and coastal erosion,
              respectively.


              Some discussion of terminology will be useful. Economic losses can be thought of as losses in
              economic activity (e.g., sales, output, employment, income, etc.) from coastal erosion and storm
              damage. Losses can also represent lost economic value from erosion and storm damage.
              Economic losses and lost economic value represent different concepts. Benefits and economic
              benefits suffer from the same problem; they have different meaning and usage in various contexts.
              There is a strict meaning of economic benefits from economic welfare theory: gains in economic
              value associated with changes in economic welfare measures. This measure will be referred to as
              economic value (or economic welfare) in this report. In the context of economic impact analysis,
              benefits can also be considered as gains in economic activity. And in a CBA context, benefits have
              another meaning and usage; benefits represent all gains in economic value and in economic activity
              from a proposed project.





                                                     Economic Measures
              A number of different economic measures exist that are conceptually separate. From a national
              income accounting perspective, measures of economic activity represent total expenditures of final
              goods and services categorized by distinct sectors, i.e., GDP (Gross Domestic Product) measures.
              The literature of input-output analysis and economic impact analysis treats economic measures as
              the dollar amount of output (sales), number of individuals (employment), the dollar amount of
              income (income), and the dollar amount of tax revenue (taxes) that result from an outside change .
              This represents dollar measures of sales, income, taxes, and employment). From economic
              welfare theory, economic benefits and economic losses are other types of economic measures that
              represent gains or losses in economic value. Lastly, from the CBA literature, econornic benefits
              and economic losses are measures that represent gains or losses in economic value and in economic
              activity (increases/losses of sales, income, employment). Each of these concepts will be treated in

              turn.


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               Aggregate Economic Activity
               Aggregate economic activity measures are usually referred to as GDP (Gross Domestic Product) or
               GNP (Gross National Product). These measures represent the total value of all final goods and
               services produced in an economy for a given time period, usually a year. The distinction between
               GDP and GNP is due to the definition and location of business entities, i.e., firms. If one is
               concerned with all sales within the boundaries of a country or region, GDP is the relevant measure
               (e.g., Coca Cola sold in the US). But if we are concerned with sales of all goods and services
               produced by domestic-owned firms or firms owned within a region, that is, sales both inside and
               outside of the country, then GNP is the relevant measure (e.g., sales of Coca Cola in the US and
               sales outside the US). Because prices can change over time, the above measures need to be
               adjusted to yield real GDP ((Ydp), real GNP (gnp), which represent the value of all final goods and
                                            0                IP
               services produced in an economy in terms of constant dollars. As such, changes in gdp/gnp will
               now reflect changes in real output.


               GDP (GNP) can be measured by two basic approaches, the flow of expenditures approach and the
               flow of earnings approach, because economic activity can be represented as a circular flow. This
               means that final goods and services are produced by firms using inputs (labor, capital, land,
               entrepreneurial ski-11) usually provided by households. These inputs are, in turn, paid compensa-
               tion (wages, rent, and profits, respectively) which constitute the income that is used to finance
               spending on goods and services. As a result, the sum of spending will equal the sum of
               compensation, by definition. Basically, the flow of expenditures approach defines GDP as the
               amount of spending on: consumption (C), private business investment (1), government services -
               both federal, and state and local (G), and if there is foreign trade, exports (X) less imports (M).
               Hence, GDP = C + I + G + X - M. The flow of earnings approach takes the sum of compensation
               paid to all inputs: wages (for labor), rent (for capital and land), and profits (for entrepreneurial
               skill) as national income. Given several adjustments (these include depreciation, and indirect
               business taxes) this measure will now equal spending on goods and services.



               Economic Impacts
               Economic impacts represent another and different measure of economic activity. Impacts measure
               the amount of aggregate economic activity usually in terms of sales ($'s), income ($'s),
               employment (No.'s), and sometimes tax revenues ($'s) that are associated with a change in the
               economy (e.g., structural change - plant closings, reduced demand, increased demand) or policy
               change (e.g., proposed regulation).      Many times they are based on multipliers that not only
               account for direct effects (direct expenditures on goods and services), but also indirect and induced
               effects. Economic impact measures will then reflect the effect that changes (structural changes,

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               such as changes in output, investment, employment; or proposed policy changes) in a particular
               sector (e.g., services sector from expanded gambling facilities) have on the sales (or employment,
               etc.) of other sectors within a study economy. Economic losses (or damages) caused by storms
               and erosion, as well as economic gains from shore protection can also lead to economic impacts.
               Here, impacts represent the monetary loss or gain to a particular segment of the economy. This
               effect consists of several rounds of impacts, that can be described as a multiplier effect. The first
               round of impacts involves only the sector of interest (i.e., primary sector) and sectors that directly
               interact with the primary sector (i.e., secondary sectors). Subsequent rounds involve impacts
               based on the interaction of these secondary sectors with still other sectors (tertiary sectors) i.e., re-
               spending activity, and then the interaction of these other sectors with still other sectors, until the
               effect originating in the designated primary sector is transmitted throughout the economy in
               question.


               Note that the above economic impact measures differ from those of aggregate measures such as
               GDP. The latter measures net changes in the value of fina          'I activity without double-counting.
               Economic impact measures do contain some double-counting in the summation of the effects
               throughout the economy which are precipitated by an initial change. To give some appreciation for
               this, take for example a measure of impacts referred to as primary econorWc impacts. This is
               calculated as the sum of sales of output and expenses for inputs for a given industry or sector.
               First, this measure is a measure of partial economic activity generated by the study sector rather
               than one of total economic activity. This is because it considers only the direct economic activity
               generated from the effect of the primary sector on secondary sectors, and not the effects of
               interactions among secondary sectors with still other sectors in the economy; that is, multiplier
               effects are not included. Secondly, the measure includes double-counting compared to aggregate
               accounting measures as GDP. Here, expenses for inputs of the primary sector reflect sales of
               outputs of the secondary sector (the secondary sector can be considered as producing intermediate
               goods). From a national accounting perspective, by including the full value of input expenses and
               output sales rather than just input expenses and the value added (from further processing by the
               primary sector) as is done in GDP measures we have double-counted by some degree, and have
               overstated the true measure of economic activity throughout the production process. This effor-,g;
               compounded when the effects of multipliers are considered. An arithmetic example will provide
               further illustration. Consider the production of a cigar. Here the first stage consists of a farmer
               selling tobacco to a cigar maker for $3. The value-added to the farmer is $3 which covers his costs
               of production (returns to labor, land, capital, and entrepreneurial ability). The second stage in the
               process consists of the cigar maker. Here he manufactures and sells cigars to a cigar store for $8.
               Now the value-added at the second stage is $5 ($843, i.e., sales less expenses). In the final
               stage, the cigar store sells these cigars to consumers for $15; the value-added is now $7 ($1548).
               The measure of GDP in this example would be the sum of the value-added at each stage, $15.

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               (Note this is equal to the value of final sales.) But by summing sales and expenses at each stage of
               production ($3 + $8 + $15) we have double-counted the true measure of economic activity; GDP is
               $15 and not $26. In this simple example, the measure of primary economic impacts overstates the
               true measure of economic activity by a factor of 1.7333 times, excluding multiplier effects. This
               example also illustrates the problem of basing arguments for shore protection solely on expen-
               diture impacts from beach or coastal tourism; these impact measures can grossly overstate the true
               measure of economic activity in shore regions. Without evidence of the magnitude of the error
               involved, expenditure impacts must be treated with caution and not as fact.




               Benefits as Measures of Economic Value
               Specific measures of changes in economic welfare are quite theoretical concepts and are covered in
               more detail in various textbooks (see Just et al. 1982, Freeman 1979, 1993, Dinwiddy and Teal
               1996, Johansson 1991). These measures are associated with losses and/or gains in economic
               welfare and represent lost economic value and/or gains in economic value, respectively. In the
               production sector, the measure of lost (gains in) economic value is economic rents (or simply
               rents), i.e., the reduction (gains) in profits RLus producer surplus. Producer surplus is included
               because it represents a monetary surplus that accrues to the producer (the firm, entrepreneur) over
               and above the value of goods and services provided (i.e., over variable costs of production), and is
               a more appropriate measure of producer welfare than profits alone (Just et al. 1982). Producer
               surplus can be regarded as a measure of the net economic value to the producer from the
               production and sale of goods and services.


               In the consumption sector, a measure of lost (gains in) economic value is the reduction (gain) in
               consumer surplus, a monetary surplus that accrues to the consumer over and above expenditures
               from consumption of a good (Just et al. 1982). It represents a net economic value to the consumer
               that accrues to consumers from consumption activities.        Any reduction (gain) in it can be
               considered a loss (gain) in economic value. At this point it should stressed that the measure of
               consumer surplus is not very accurate, especially if income effects are present; then more specific
               consumer welfare measures are appropriate (Just et al. 1982, Freeman 1979, 1993, Auerbach
               1985).


               In practice, coastal erosion and shore protection can affect many consumers and producers, and
               economic welfare analysis of the changes at the individual level are both impractical and
               burdensome. To be useful to public officials, economic welfare analysis requires aggregation over
               the individual economic units (consumers and producers) that are affected.            This can be
               accomplished by analyzing the change in economic welfare at the market level since the aggregation
               process yields the economic surpluses associated with the market, or total, demand and supply of

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               private goods and services. These are equivalent to the sum of economic surpluses over all
               consumers and producers in the market under competitive conditions (Just et a]. 1982). Hence, the
               change in aggregate welfare will reflect the sum of changes in individual welfare under competitive
               conditions.
               Unlike private goods and services, public goods and services such as shore protection are usually
               provided at zero or nominal costs and are not rationed by price. Because one does not observe
               market prices and quantities of public goods, changes in economic welfare resulting from changes
               in levels of the public good must be detem-lined at the individual user level and then aggregated
               over all users. This involves the use of various nonmarket valuation and/or indirect market
               valuation techniques based on representative samples of individuals to obtain estimates of
               economic welfare associated with the good in question (these techniques are treated in the
               textbooks previously referenced).


               In order to evaluate changes in economic welfare that result from coastal erosion and storm-
               damage, and from shore protection, two situations in either case must be compared -- the economic
               welfare of the economy that results with the presence of coastal erosion (shore protection), and the
               economic welfare of the economy that would occur without it (i.e., in the absence of coastal
               erosion (shore protection)). The net change would represent the change in economic welfare
               attributable to coastal erosion (shore protection). A procedure known as the "with and without"
               rule commonly used in Cost-Benefit Analysis can assist in this process and avoids attributing
               effects to an event which are not caused by it.


               In the process of assessing changes in economic welfare that result from coastal erosion and storm-
               damage, and from shore protection, the measures of economic welfare can further be identified as
               being national or regional in scope. The approach that the U.S. Army Corps of Engineers (ACOE)
               bases their analyses and decision-making on is based on National Economic Development (NED)
               criteria. Regional development (RD) losses (or gains) are the lost (or gains in) economic value(s)
               that result from erosion/storm-damage (shore protection) in one geographical area (where the gains
               in one area are equal in size to the values lost in another area). NED losses (or gains) represent lost
               economic values that occur as the result of erosion/storm-damage (shore protection) in ojle
               geographic area but do not reappear as gains in other geographic areas. These two definitions
               classify losses (or gains) at two extremes; losses (gains) in one area that are offset by equal gains
               (losses) in another area -- RD losses (gains), and losses (gains) in one area that do not accrue as
               gains (losses) in another area -- NED losses (gains). And situations can exist where both types of
               effects occur.




               Benefits in Cost-Benefit Analysis

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               Benefits in CBA are used in a different context compared to that of welfare economics and, thus,
               represent different measures. In CBA, benefits refer to all gains in economic value (welfare
               component) and gains in economic activity (such as increases in sales, income, employment) that
               directly and indirectly result from a proposed project. Cost-savings are also sometimes included in
               CBA benefit measures. Therefore, benefits in the context of CBA can comprise measures of
               economic value and economic impact benefit measures. However, a word of caution. Care must
               be used to avoid any double-counting of benefits. As an example, consider the aggregate flow of
               capital that has left an economic sector due to an outside (exogenous) effect, such as the loss or
               damage to real property and physical structures from erosion/storm-damage. It is equal to the sum
               of reduced revenue plus increased costs in the production sector, ar the sum of consumer surplus
               lost and reduced expenses in the consumption sector. When both sectors are included, it is equal
               to the sum of reduced revenues and increased costs from the production sector plus the reduction in
               consumer surplus from the consumption sector. Consumer expenditures are not included, because
               they represent purchases of goods and show up in the production sector as revenues. Including
               both consumer expenditures and producer revenues would be double-counting.




                                                         Economic Methods


               Present Value Analysis
               Present value analysis is the technique that economists use to compare costs and/or benefits of
               various projects over time to choose among projects given limited budgets and select a "best" or
               several "bests." Discussion of background material will prove useful so that everyone will be on
               an equal level. First, there are two variations of the present value analysis commonly used by
               economists, cost-effectiveness analysis and cost-benefit analysis, that are often confused. Cost-
               effectiveness analysis concerns the minimum cost way to achieve a given objective. Cost-benefit
               analysis (CBA), however, considers both the benefits and costs associated with a particular pro-
               ject. More detailed explanations of these two versions are discussed below.


               Secondly, there are slightly different interpretations of the present value analysis in the fields
               economics and in finance. In economic theory, CBA is a technique to use to evaluate the economic
               feasibility of public projects, i.e., projects financed with public funds (Kohli 1993, Bohm 1973).
               CBA is also referred to as capital budgeting, financial analysis or investment analysis in finance
               theory and is used to evaluate decisions such as plant expansions and new product development; it
               will be referred to as financial analysis in the remainder of this report (Brealey and Myers t 99 1).
               The main difference between CBA in economic theory and financial analysis in finance theory is
               due to the treatment and measurement of benefits that accrue to the project and the decision criteria.
               In financial analysis, benefits are treated as all additional income (i.e., sales revenues) that results

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                 from the project. The criteria of financial analysis is to undertake a project if the internal rate of
                 return on total investment based on current market prices for a proposed project is greater than the
                 prevailing market interest rate. Regarding CBA, benefits are based on the extra economic surplus
                 (in aH economic sectors affected by the project) that are attributable to a project. The criteria in
                 CBA are to undertake a project if the present value of net benefits (benefits less project costs,
                 discounted) exceeds zero, or equivalently, if the ratio of the present value of benefits to the present
                 value of costs exceeds one. In sum, financial analysis considers direct effects of a project, that is,
                 direct benefits measured as additional income from a project. CBA is based on all direct and
                 indirect effects attributable to a project, all direct and indirect benefits measured as gains in
                 economic surplus cluc to a project. Furthermore, financial analysis is not an appropriate technique
                 nor d6clgl6n criteria foe public projectg becauge government b6dieg are not in the business of
                 maximizing profits. Because public projects involve the use of public funds, an objective such as
                 to maximize social welfare (i.e., the welfare of society) is a more appropriate decision criteria.


                 All investment decisions and the choice among various projects involve a time element in most
                 cases and a concern among economists is to properly evaluate present and future dollars. The
                 issue is that price levels change over time due to inflation and, because one can earn the market rate
                 of return on investments, one must use a common measure to equate present and future dollars.
                 This is usually accomplished through the mechanism of discounting, to express all dollars as
                 present dollars (commonly referred to as the present value) (in much the same manner one could
                 express all dollars in terms of future dollars).


                 The basic present value (PV) formula for CBA is:
                 (1)     PV = -CO + (B-C),/(I+r) + (B-C)2/(I+r)2 + - + (B-C)n/(I+r)n, or
                 (2)     PV = -Co + F, (B-C)i/(I+r)i,
                 where "-Co" refers to the initial cost outlay, 1! the benefit in each period, C the cost in each period,
                 r the discount rate, and n the time period (Herfindahl and Kneese 1974, Kohli 1993). These
                 formulas are appropriate for projects that realize costs and benefits over a time period. The manner
                 in which the formulas are written with the first element " -Co" represents a s.ituation where a
                 project involves front end investment (such as when a municipality buys dredging equipment-to
                 renourish their beaches). In some cases, there is no front end investment and then the term "-C."
                 is simply dropped (such as when a municipality would hire a contractor to provide shore
                 protection). The present value of net benefits (benefits less costs, discounted) is the appropriate
                 measure for comparing projects over time given equal scale (i.e., size) and time period.


                 Cost-Effectiveness Analysis. Cost-Effectiveness Analysis concerns the minimum cost method to
                 achieve a given objective. By definition, it ignores benefits and, thus, does not address economic
                 rationale to achieve a given objective. It is appropriate when considering how a project can be

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               implemented in the least expensive way. The procedure is to estimate all costs for a particular
               option over time, discount these costs, and then sum the discounted costs (discounted costs
               represent the total cost in today's dollars); the sum of discounted costs is referred to as present
               value of costs. Equation (2) can be easily modified as:
               (3)     PV = -Co + F, (C)i/(I+r)l,

               The decision criterion is to select that project with the smallest present value of costs over time.
              'This formula can also be used in comparing projects when the benefits realized from alternative
               projects are equal, and hence one only needs to consider comparative costs since the only concern
               is to provide a project in the cheapest way possible.


               Cost-Benefit Analysis. Cost-Benefit Analysis (CBA) is the primary method in which both the
               benefits and costs associated with a project are considered. It is based on economic justifications
               in detern-iining the implementation of a project; that is, whether the outcome of a project is worth
               the costs of achieving it. Here the analyst must identify, quantify, and value all possible benefits
               and costs associated with the presence of the project as opposed to a situation without the project,
               choose a time horizon and discount rate, and face an investment constraint. This technique has two
               variations commonly used. One is to examine the difference among benefits and costs (benefits
               less costs) for each time period, discount it, and then sum it, giving the present value of net
               benefits over time, i.e., Equation (2). The decision criterion is to select that project that yields the
               maximum present value of net benefits over time. The second version is the B/C ratio, where the
               discounted sum of benefits is divided by the sum of discounted costs:

                                   I (B)i/(I+r)i
               (4)     B/C ratio
                                    I (Qi/(l+r)1


               When benefits equal costs this ratio will equal 1, hence if this ratio is greater than I benefits will be
               above costs. The decision criterion is to select that project that yields the maximum B/C ratio. The
               use of this ratio is quite controversial among economists. A brief summary will suffice. Most
               agree that selection of a project should not be based solely on the B/C ratio, it should be used in
               conjunction with discounted net benefits to rank alternative projects (Margolis 1959, Herfindahl
               and Kneese 1974). Also most agree that maximizing the B/C ratio in order to select a project is
               inappropriate (Herfindahl and Kneese 1974, Eckstein 1958). Where most economists would
               discourage the use of the B/C ratio concerns aggregate (i.e., total) benefit-cost comparison of
               projects, conversely most agree that the B/C ratio is useful in examining incremental (i.e., an extra
               unit, marginal) benefit s and costs associated with a project in each period (Herfindahl and Kneese
               1974, Eckstein 1958). The association between total benefits and costs with marginal benefits
               and costs in project choice will tend perspective on these points. Recall the decision criteria for

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               CBA based on net benefits, choose that project with a maximum of discounted net benefits.
               Maximization of discounted net benefits (total benefits less total costs) occurs where discounted
               marginal benefits (MB) equal discounted marginal costs (MQ or where the ratio of discounted MB
               to discounted MC is equal to 1. Hence, a B/C ratio not equal to one implies a situation where
               discounted net benefits are not at a maximum.


               Further complications arise when comparing projects of unequal scale and time frame. The
               following points apply because the decision criterion for both CBA and cost-effectiveness analysis
               changes. The B/C ratio, Eq. (4), is useful in comparing alternative projects of unequal scale only
               when no extreme variation in scale (referred to as capital intensity) is present (Eckstein 1958). In a
               sense the B/C ratio reduces the scale factor; consider two projects one twice the size of the other so
               that all proportions are equal, then the ratios will be, the same. But, this raises another issue
               concerning the use of capital investment in a project, i.e., front end investment versus rationing of
               capital investment among various periods through the project's life similar to annual operating
               expenses. Then the criterion and comparison become more complicated (see Eckstein 1958 for
               more detail). When faced with unequal time frames in comparing projects, the time frames should
               be made compatible. This can be accomplished by using a least common denominator (LCD) to
               determine equivalent time periods (e.g., a 3 year and a 5 year project have a LCD of 15 years).
               And finally, the literature is rich with discussion of the appropriate discount rate to use (see
               Herfindaht and Kneese 1974, Bohm 1976, Mishan 1976, Kohli 1994).



               Economic Impact Analysis (Public Policy Analysis)
               Economic Impact Analysis (EIA) also needs clarification. Many applied policy problems and
               proposed federal regulations use variations of EIA commonly referred to as Public Policy Analysis
               (Weimer and Vining 1991). Here the analyst conducts an econonuic analysis to determine the
               effects (impacts) of proposed policy changes on all appropriate economic units (consumers,
               producers) and/or economic sectors (consumption, production, government), where the economic
               effects associated with the policy are identified and quantified. Such an approach will be referred
               to as a Public Policy Analysis in the remainder of this report. Furthermore, the meaning pf
               economic impacts and of economic impact analysis based on this technique is different and must
               not be confused with similar terminology used in the context of an input-output analysis discussed
               below.




               Input-Output Analysis
               Economic Input-Output Analysis (1-0) is a specific technique developed by an economist
               (Leontieff 1966) and is based on an input-output model of aggregate measures of economic activity

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               such as sales revenues, income, and employment related to an economy defined by geographic-
               political boundaries (state, region, nation). A main feature of this technique is to determine
               "multipliers" which can be thought of as how changes in primary economic activity translates into
               final economic activity, and to examine how changes in specific sectors (manufacturing, services)
               of an economy affect the entire economy in question.            When one examines such changes
               throughout the economy based on an 1-0 model, such an analysis is refer-red to as an economic
               impact analysis. 1-0 analysis was primarily developed to address policy questions such as what
               are the.effects on sales, income, and employment of various structural changes in the economy
               (e.g., plant closings/openings, changes in local infrastructure investment, reduced demand), and of
               proposed policies (e.g., different minimum wage policies, proposed regulations).


               The following discussion will give some intuition behind the 1-0 approach. The basic prerruse is
               that each dollar of expenditures and/or sales in an industry or sector has an effect on other
               industries and sectors as well as on regional (or state and national--whatever the study area is
               defined as) output, income and employment. Any change in economic activity (e.g., sales,
               investment, employment, technology) will produce a change in a multiplier (or sequential) fashion
               throughout the study economy. The magnitude of impacts within an economy resulting from a
               change in part of the economy is influenced by the degree of interdependency that exists among the
               various sectors within that economy. These 1-0 models can be solved for sector outputs (i.e.,
               sales), income, employment, and tax revenues in some cases. Based on an 1-0 model solved for
               sales, the economic impacts that correspond to the level of activity in a final demand sector on the
               level of outputs of the other sectors and on the economy as a whole can be estimated. These
               impacts in turn are characterized as either direct, indirect, or induced effects. (Similar remarks can
               be developed for 1-0 models solved for income, and employment). Direct effects represent the
               change in demand of industries or sectors directly affected from a change in the final demand of a
               given primary sector. Suppose an increase in demand for certain recreational activities such as
               marine fishing and boating, or even gambling in Atlantic City occurs in a local economy (say
               Atlantic County). This will result in an increased supply of fishing equipment and trips, boats, and
               ex panded gambling facilities to meet the demand represented by increased sales. This, in turn, will
               increase the suppliers' purchases of inputs (goods and services) used in the manufacture of fishinZ
               equipment, recreational boats, and of gambling equipment. Here, an increase in the demand for
               recreational activities has resulted in a direct effect on those industries and sectors (secondary
               sector) that supply the primary recreational sector.


               Indirect effects measure the effect of secondary sectors' increased purchases of the inputs
               necessary to meet the increased demand for their products. The effect of income generated from
               this increased activity that is recipient in the study economy is defined as an induced effect.



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                Aggregate economic impacts on a given economy are referred to as multiplier effects that can
                measure output, income, and employment (and sometimes tax revenue) effects. Output multi-
                pliers measure the total change in the economic activity associated with output (sales) of all sectors
                of the economy (primary, secondary sectors and beyond) that is generated from an additional dollar
                of final demand (goods and services of the primary sector). The total change in income that occurs
                in a given economy due to a dollar change in final demand is reflected by the income multiplier.
                Employment multipliers, have a slightly different interpretation because they are not in terms of
                dollars. They show the change in a given economy's employment generated by a change in output
                that causes an employment change of one unit.


                Two types of multipliers are estimated in 1-0 studies to project the total economic impacts created
                from a change in final demand (sales) per dollar of direct change in the primary sector within the
                economy (i.e., endogenous primary sector). Type I multipliers are defined as (D+I)/D where
                D=direct and I= indirect effects, and represent the combined direct and indirect effects of economic
                activity within a given economy per dollar of direct change in the designated primary sector. Typ e
                H multipliers, (D+I+[N)/D where D and I are already defined, and IN=induced effects, measure
                the combined direct, indirect and induced effects of economic activity throughout the economy per
                dollar change in the primary sector within the economy. It is the product of these multipliers with
                sales (for output and income effects), and employment in the primary sector (for employment
                effects) that results in projections of economic impacts.


                This is how the impacts of tourism expenditures on the state on New Jersey are derived in the
                Longwoods reports (Longwoods Int'l. 1992, 1994, 1995) of the economic impact on the New
                Jersey travel and tourism industry. But measures of economic activity based on such economic
                impacts involve double-counting as previously discussed, and have overstated the true measure of
                aggregate economic activity as represented by GDP. This error is compounded when the effects of
                multipliers are considered. This point cannot be overemphasized. Furthermore, this illustrates the
                essential weakness and problem with arguments for shore protection based solely on expenditure
                impacts from beach or coastal tourism; these impact measures can grossly overstate the true
                measure of economic activity in shore regions. Without evidence of the magnitude of the emqr
                involved, expenditure impacts must be treated with caution and not as fact. Estimates of direct
                expenditures is preferred compared to expenditure impacts of tourism (the Longwoods reports
                develops both estimates).




                Simulation Models
                Simulation models are hypothetical computer models written in either primary computer code or in
                a simulation language to represent (mimic) an actual situation and to then simulate the specific

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                application and changes to it (see Murray 1993 for more details). They have been used in
                epidemiology to simulate the spread of an actual disease epidemic. It has been used in population
                ecology to simulate population dynamics and the actual spread of an insect population outbreak and
                the effects of different control strategies. And some applications have been based on bio-econon-iic
                models of fisheries.




                Risk-Retum Decision Models
                Risk-Return models are from the field of finance and consist of the applications of portfolio theory,
                mean-variance models, and variations of the capital asset pricing model (see Brealey and Myers
                1991 for the basics). They are used to decide among tradeoffs between risk and return so as to
                determine an efficient portfolio of holdings (least risky collection of assets that yield the greatest
                return) for various risk levels. These models are highly complex and indispensable to analysts and
                researchers in financial markets.






                                                             References
                Auerbach, A.J. 1985. "The Theory of Excess Burden and Optimal Taxation," (in) Auerbach,
                A.J. and M. Feldstein, ed. 1985. Handbook of Public Economics, Vol. 1. North-Holland: New
                York, NY: 61-127.

                Brealey, R.A. and S.C. Myers. 199 1. Principles of CoMorate Finance. McGraw-Hill, Inc.:
                New York, NY.

                Dinwiddy, C. and F. Teal. 1996. Principles of Cost-Benefit Analysis for Developing Countries.
                Cambridge Univ. Press: New York, NY.

                Eckstein, 0. 1958. Water Resource Development: The Economics of Project Evaluation.
                Harvard Univ. Press: Cambridge, MA.

                Freeman, A.M. 1979. The Benefits of Environmental Improvement. Johns Hopkins University
                Press: Baltimore, MD.

                Freeman, A.M. 1993.     The Measurement of Environmental and Resource Values: Theory and
                Methods. Resources for the Future, Inc.: Washington, DC.

                Gittinger, J.P. 1972. Economic Analysis of Agricultural Pro ects. Johns Hopkins University
                Press: Baltimore, MD.

                Herfindahl, O.C. and A.V. Kneese. 1974. Egonomic Theo[y of Natural Resources. Charles E.
                Merrill Publ. Co.: Columbus, OH.

                Johansson, P.O. 1991. An Introduction to Modem Welfare Economics. Cambridge Univ. Press:
                New York, NY.

                Just, R.E., D.L. Hueth and A. Schmitz. 1982. A1212lied Welfare Economics and Public Policy.
                Prentice Hall Inc.: Englewood Cliffs, NJ.


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             Leontieff, W. 1966. Input-Outl2ut Economics. Oxford Univ. Press: New York, NY.

             Longwoods, Int'l. 1992. The Economic Impact, Performance and Profile of the New Jersey
             Travel and Tourism Industry, 1990-91. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, May.

             Longwoods, Int'l. 1994. The Economic Impact, Performance and Profile of the New Jersey
             Travel and Tourism IndustU, 1992-93. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, September,

             Longwoods, Int'l. 1995. The Economic Impact, Performance and Profile of the New Jersey
             Travel and Tourism IndustU, 1993-94. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, June.

             Mishan, E.J. 1976. Cost-Benefit Analysis. Praeger Publishers: New York, NY.

             Murray, J.D. 1993. Mathematical Biology. Springer-Verlag: New York, NY.

             NJDEP, DCR. 198 1. New Jersey Shore Protection Master Plan. Prepared by Dames and Moore.
             Prepared for Division of Coastal Resources, NJDEP, Trenton, NJ.

             Weimer, D.L. and A.R. Vining. 1991. Policy Analysis: ConcQts and Eractice. Simmon &
             Schuster, Prentice Hall Inc.: Englewood Cliffs, NJ.

































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                                         Chapter 3 - Economic Aspects of Shore Protection




                                                            Introduction
                This chapter contains a detailed review of the economic literature relating to shore protection, beach
                use, coastal tourism, and public policy issues. The economic component of the New Jersey Shore
                Protection Master Plan (NJSPMP) is reviewed here       , as are ACOE studies and policy-oriented
                studies of shore protection. In addition, characteristics of typical beach fill projects in New Jersey
                over the 1960-94 period are summarized in this chapter.


                Specific objectives are to: 1) review all pertinent literature concerning economics and shore
                protection, recreational beach use and benefits of shore.protection, coastal tourism, the New Jersey
                Shore Protection Master Plan pertaining to its economic analysis, U.S. Army Corps of Engineers
                (ACOE) studies, and any relevant policy evaluations of shore protection; 2) summarize
                characteristics of typical beach fill projects in New Jersey during the 1960-94 period from which
                economic analyses could be performed; and 3) provide future directions and recommendations.


                The overall purpose of this report is exploratory rather than conclusive. It is meant to examine the
                issues involved in shore protection decision-making that must be considered in the preparation of a
                new Coastal Hazard Management Plan.


                The economic literature reviewed in this chapter is in three main areas: 1) studies of the economic
                value of beach use and beach protection, 2) studies of the impacts of coastal travel and tourism , 3)
                previous ACOE studies, and 4) policy-oriented studies of shore protection including a review of
                the NJSPMP. Following the literature review is a brief section about characteristics of typical.
                beach fill projects completed in New Jersey over the 1960-94 period. Recommendations for
                further work concludes the chapter.




                                                         Literature Review



                Economic Value of Beach Use and Shore Protection

                Curtis and Shows (1982, 1984). One of the first studies to assess the economic value of
                recreational beach use, (Curtis and Shows 1982, 1984) conducted two investigations based on
                surveys in Florida. In t981 a survey of residents and tourists were conducted by face-to-face
                interviews (Curtis and Shows 1982). A Contingent Valuation (CV) method based on an open-
                ended question format was used to elicit the willingness-to-pay (WTP) of residents and tourists for
                beach use at Delray Beach, Florida. Survey results indicated that residents were willing to pay

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                $1.88/person per day for beach use, while tourists were willing to pay $2.15/person per day in
                1981 (Table 1). Specific details of the study were not readily available -- these studies were
                summarized in Bell and Leeworthy (1986); it Is not known what type of sample design was used
                nor if specific questions about the value of beach protection were included.


                In 1983, Curtis and Shows (1984) appeared to have conducted a similar study of the value of
                beach use at Jacksonville Beach, Florida. Residents and tourists were surveyed in 1984 and
                results indicated that residents were willing to pay $4.44/person per day and tourists $4.88/person
                per day for beach use (Table 1). Again, specific details of the study were not readily available --
                these studies were summarized in Bell and Leeworthy (1986); it is not known what type of sample
                design was used nor if specific questions about the value of beach protection were included.


                It is hard to conclude much from the Curtis and Shows (1882, 1984) studies without knowing the
                specific details of the overall research design, including the sample design, questionnaire, and
                whether the investigators isolated and controlled for the economic value of recreational beach use
                relative to the economic value of beach protection. Compared to the Bell and Leeworthy studies
                reviewed, these estimates of beach use are higher in magnitude, but show the result that tourists
                were willing to pay more compared to residents as did the Bell and Leeworthy studies. Because
                these estimates only refer to recreational beach use and not to beach protection they are dropped
                from further consideration.




                Bell and Leeworthy (1986, 1985, 1990). In one of the first studies to measure the economic value
                of beach use based on consumer surplus techniques, Bell and Leeworthy (1986) conducted a study
                of the economic importance and value of beaches in Florida. The study used a split sample
                approach, where the population was split into two groups, Florida-residents and tourists.
                Concerning residents, a two-part random sample and survey was used, the first part involved a
                telephone survey of a random sample of 1000 adult residents to determine participation rates in
                beach use, and the second part involved a telephone survey of a random sample of 911 adult
                residents to obtain information on use patterns, spending, and value from use. Regarding tourist@"
                a total of 4,333 tourists were contacted as they exited the state via auto and airplane. Of this group,
                826 were interviewed via a face-to-face survey for data on use, spending, and value from use. AD
                surveys took place during 1984. Results of specific components of this study were published
                elsewhere (Bell and Leeworthy 1985; Bell and Leeworthy 1990), however, discrepancies of the
                reported results were found across studies (1985, 1990) with that of the main report (1986), thus
                the discussion that follows is based on the main report.




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             The study estimated the value of beach use based on both a CV method with an open-ended
             que stion. format, and a Travel Cost approach. Results indicated that residents were willing to pay
             an average of $1.3 I/day per person and tourists $1.45/day per person based on the CV method


















































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            Table 1.































































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              Table I Cont.































































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               Table I Cont.































































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                (1984$, Table 1). Concerning the Travel Cost approach, the researchers first estimated demand
                curves for beach use, and then based on the average number of days used, along with other
                independent variables evaluated at their mean value, estimated the area under the demand curve
                above the average number of days used to calculate consumer surplus. These results indicated that
                economic value from beach use were estimated at $10.23/day per person for residents and
                $29.32/day per person for tourists (Consumer Surplus estimates - CS, 1984$, Table 1). One
                would expect benefits of beach use for residents to be smaller than nonresidents because residents
                are located closer to the beaches, costs of travel to the beach are lower for residents, residents have
                more access to beaches, and they have more alternative beaches to choose from than nonresidents.
                That is, residents face a rather unlimited supply of local beaches compared to tourists and
                accordingly will take advantage of this and use the resource more. Results of the Florida study
                illustrate this with residents spending an average of 14.68 days/year per person for beach visits
                compared to nonresidents who spent an average of 8.64 days/year per person for beach visits.


                Because the Bell and Leeworthy studies did not address the value of beach protection these study
                results are dropped from further consideration.



                Lin@Lsay and Tupper (1989). In one of the studies that estimated the value of beach protection (i.e.,
                erosion control, in general), Lindsay and Tupper (1989) conducted a study to determine three
                separate, but successive, economic values; 1) the value beach users place on their recreational use
                of the beach, 2) the value of beach protection in general, and 3) the value of having a litter cleanup
                program for beaches in New Hampshire and Maine. The study was based on a random sample of
                about 1100 beach users split over four coastal beaches in New Hampshire and Maine that were
                selected because of differences in physical characteristics across these beaches, (e.g., from
                undisturbed-natural environments to some urbanized features - close proximity to seasonal
                cottages/condominiums, presence of seawalls). The survey took place during the summer of
                1988. The researchers used a CV method with an open-ended question format with face-to-face
                interviews to obtain estimates of economic value, i.e., VVTP. Results indicated that the estimated
                WTP bid for recreational use averaged $47-40/day per person, the estimated WTP bid for beach
                protection (i.e., erosion control) averaged $30.80/year per person, and an estimate of the economic
                benefits for beach cleanup averaged $26.40/year per person (1988$, Table 1). If one were to
                assume a 92-day beach season (June-August), an estimate of the d                economic value from
                erosion control would be $0.33/day per person.


                An interesting feature of this study is the finding that the mean estimates of economic value varied
                across all four beaches, which could reflect the difference in beach characteristics across these four
                beaches or difference in tastes, etc.. A limitation of this study is that the estimated mean benefits

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                exhibit high variability, in the case of WTP for erosion control over twice the estimated mean value
                (i.e., the coefficient of variation was 2.233, which measures the relative dispersion of the mean
                WTP bids). Possible reasons for this could be the small sample size and/or that the survey used an
                open-ended WTP question. Furthermore, because respondents were asked to assess three types of
                values in successive order, an upward bias in the estimates of the second and third successive
                values could result.




                Silberman and Klock (1988): Silberman, Gerlowski and Williams (1992). In a study of the
                economic benefits of beach protection in New Jersey, Silberman and others designed a study to
                compare a situation where beaches would undergo a beach protection project to beaches that would
                not so as to examine economic value of beach protection at Northern New Jersey beaches,
                published in two separate papers, (Silberman and Klock 1988; Silberman, Gerlowski and Williams
                1992). The researchers also addressed the issue if economic value from providing beach
                protection should represent the sum of use and nonuse values, a concern to economists in general.
                The overafl objective of the study was to assess economic value attributable to beach protection
                projects (i.e., beach nourishment projects) within the Sea Bright, NJ to Deal, NJ area, a 12-mile
                stretch of the northern New Jersey coastline. The study area ("recreational resource area")
                encompassed the northern NJ coast from Sandy Hook Gateway National Recreation Area through
                Belmar, NJ. Because the study's objectives were to assess both use and nonuse (existence) values
                attributable to beach protection, two separate research designs were used, one associated with the
                use value component, the other associated with the existence value component. Discussion of the
                existence value component will follow that of the use value component.


                To assess benefits from beach use due to beach protection (use value), Silberman and Klock
                (1988) used a split research design where two separate groups of beach users were surveyed. One
                group was to represent the situation without beach protection (Bw/0), the other group the situation
                with beach protection (Bw). Estimates of economic benefits attributable to beach protection were
                treated as the difference between benefits estimated from the second group less those benefits of
                the first group (i.e., B = Bw - Bw/0). A split design was used to avoid introducing any upward
                bias in benefit estimates corresponding to a situation with beach protection (i.e., Bw) to avoid
                possible bias from successive order (a possible bias in the (Lindsay and Taylor 1989) study). One
                group was asked questions pertaining to existing beach conditions (i.e., situation without). The
                other group was asked questions pertaining to beach conditions as if a beach protection project
                were undertaken (situation with). The researchers then surveyed a random sample of beach users
                that represented both groups during the summer of 1985 via face-to-face interviews, but fail to cite
                the sample size of both groups. A contingent valuation approach.based on an iterative bidding
                question format was used to assess economic benefits from beach use, i.e., use-values. Results

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                indicated that beach users were willing to pay an average of $3.90/day per person for beaches that
                would receive beach protection (Bw) compared to an average of $3.60/day per person for beaches
                that did not receive beach protection (Bw/0), ( 1985$, see Table 1). The difference, an average of
                $.30/day per person (i.e., B = Bw/o - Bw), the researchers interpreted as an estimate of economic
                value attributable to beach protection., Before continuing one should note the similarity in the
                estimated econorrdc value from beach protection in this study ($.30/day per person, 1985$) with
                that of the Lindsay and Tupper study conducted using a less sophisticated research design
                ($.33/day per person, 1988$). It is possible that bias from successive order is not measurable in
                small samples.


                The component of the NJ study to assess existence value (or nonuse value) requires some
                discussion about the interpretation of existence value first. In simple language, existence value
                represents a value society places on a specific good, here, beach protection, when use is
                constrained to zero. In other words, a value for beach protection without use. Existence value is
                then interpreted as the value placed on the knowledge that beaches exist that are newly protected
                compared to beaches that are eroded for the segment of the population that would never visit or use
                these beaches. Hence, it represents a value of preservation versus no preservation for beaches in
                general. This component of the study was based on two independent samples and surveys, an on-
                site survey using face-to-face interviews of a random sample of beach-users, and a telephone
                survey of a random sample of 500 residents in I I northern NJ counties and on Staten Island, NY.
                A CV approach was used in each survey but specific formats differed; an iterative-bidding format
                corresponding to the on-site survey and an open-ended format corresponding to the telephone
                survey. Silberman and Klock (1988) estimated existence value based on the on-site survey at an
                average one-time contribution of $16.31 (1985$, Table 1).          If this represents an annual
                contribution, an estimate of nonuse value per day could be $.177/day per person (based on a 92-
                day season, June-August). A shortcoming of this component of the study was that surveyed
                individuals were not given any alternative beach protection projects in other areas along the NJ
                coast to choose from; this fault could have caused an upward bias in the reported estimates.
                Furthermore, the researchers expressed concern that sampled beach users expressed difficulty in
                understanding the concept of existence value.



                Silberman. Gerlowski and Williams (1992). A more detailed analysis of existence values by
                Silberman, Gerlowski and Williams (1992) was based on a comparison of estimated bids from the
                on-site survey and the telephone survey, and the difference in estimated bids of users versus
                nonusers from a statistical Tobit model where the independent variables were estimated at their
                mean values, i.e., E(Y)u - E(Y)nu = XBU - XBnu, where u=will use in future, nu=will not, E(Y)
                refers to the expected value of the dependent variable (existence value) and XB refers to the

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                product of the design matrix of independent variables (the X matrix) and the parameters associated
                with the independent variables (the B vector). This specification is commonly used to describe
                regression models in standard textbooks of statistical and econometric methods (see Ostle and
                Mensing 1985, Johnston 1993). The researchers used a Tobit analysis since many zero responses
                were present (and ordinary least squares techniques yield biased estimates in such a case) and to
                control for the characteristics of use versus nonuse of beaches in the future, because existence
                value is only defined as a value when there is no use, and the on-site survey results contained
                46noise" as a result (see Judge et al. 1988 for more detail on Tobit models). The results based on
                the Tobit analysis indicated that estimates of existence value were an average of $15. 10 from the
                on-site survey, and $9.26 from the survey of residents that were nonusers.          The researchers
                concluded that the estimate from surveyed residents is a more appropriate estimate of the average
                economic benefit based on the existence of a beach environment preserved from erosion (1985$,
                Table 1).


                Based on this study, if economic benefits are to be based on the sum of use and nonuse values,
                then benefits would be estimated as the sum of $.30/day and $.1006/day ($9.26/92-days in the
                season) per person or $.4006/day per user; but if benefits only represent use values then benefits
                would be $.30/day per person. One must keep in mind the limitations of this study in any
                interpretation. It was based on a relatively small sample size, causing a great deal of variation in
                the benefit estimates, survey respondents had difficulty in trying to assess a value for existence
                value of beach protection, and a choice of at least one or more alternative beach protection projects
                located elsewhere in NJ were not offered as alternative choices, which can introduce an upward
                bias in the reported estimates.



                ACOE Rgparts.      Further studies of the economic value of beach use come from ACOE
                unpublished surveys. Using the same survey data as in Silberman and Kloch (1987), Silberman et
                al. (1990), the ACOE provide more complete results concerning the survey of beach users only
                (U.S. ACOE 1989b). A random sample of beach users were surveyed by personal interview over
                the summer of 1985 (July - Labor Day, September) at all public beaches in the Sea Bright to Ocega
                Township (Loch Arbor) area with the exception of Deal. Benefit data were obtained based on a
                CV method using an iterative-bidding question format. Results from 2,917 surveys indicated a
                mean WTP bid of $3.67/person associated without shore protection, $3.89/person for shore
                protection with a 50 foot berm, and $3.93/person for shore protection with a 100 foot berm (Table
                1, 1985 dollars; no estimates of variability for these mean values were given). Results pertaining
                to existence value, the value of preserving the beach, was estimated at an average of $16.41/year in
                1985. From these results an estimate of value from beach protection is estimated to be $.22/person
                per day associated with a 50' berm, afid $.26/person per day associated with a 100' berm; an

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                average of both sizes based on the midpoint of the two WTP-bids pertaining to shore protection is
                $3.9 I/person [(3-89 + 3.93)/2], hence a net effect attributable to shore protection can be estimated
                at $.24/person ($3.91 less $3.67) in 1985 dollars.
                Another CV survey was conducted by the ACOE during the summer of 1987 for conditions of no
                project, a beach fill project with a 50 foot berm, a beach fill project with a 100 foot berm, and a
                beach fill project with a 150 foot berm (ACOE 1994a, 1994b). Unfortunately, results of this
                survey study were not contained in the report (ACOE 1994a, 1994b) nor were readily available.
                Another ACOE study estimated recreational benefits based on a unit day value method for the area
                of Bamegat Inlet to Great Egg Harbor Inlet (Reach 7, 8 and 9), but found no recreational benefits
                to accrue (ACOE 1992). (A unit day value method basically consists of a monetary value of the net
                increase in users as a result of a project valued at a standard day trip expense or at a standard
                entrance fee.)


                An ACOE reconnaissance report (1993) for the Raritan Bay - Sandy Hook (reach 1) area, used a
                unit day value method to obtain estimates of recreational benefits of $2.88/day-trip with shore
                protection and $2.40/day-trip without the project; a net difference attributable to shore protection of
                $.48/day-trip (in 1982 dollars).       Further ACOE reconnaissance studies did not consider
                recreational benefits ( 199 1 a and 1991 b, 1994, 1995).



                KoI212el (1994); Kucharski (1995). In a recent study conducted at southern New Jersey beaches,
                Koppel (1994) and Kucharski (1995), examined the economic value of beach use. During the
                summer of 1994, beach users, business owners/managers, and homeowners were surveyed in a
                three part process in several southern New Jersey communities (Stone Harbor, Avalon, Atlantic
                City, Longport, Margate, Ventnor, and Brigantine). The first phase of the study involved beach
                users. A random sample of 1063 beach users were personally surveyed during the' summer
                months (June, July, August, and Labor Day-September) of 1994. The study used a CV method,
                closed-ended referendum type question format to obtain estimates of the value of beach use in
                general (this represented a without project condition), an open-ended type question format to obtain
                estimates of the value of wider beaches (to reflect beach nourishment), and an open-ended questiQjq
                format to obtain estimates of the value of preserving the beach from erosion (i.e., existence value).


                Survey results indicated that the recreational value of beach use averaged $5.04/person per day
                when bids of zero dollars (i.e., $0 bids) were excluded and $4.22/person per day when $0 bids
                were included in 1994 (Table 1).


                Concerning the value of a wider beach, that is, the value of beach fill, 8 1 % of the respondents
                indicated that they would pay the same, 16% were willing to pay more, and 3% indicated they

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               would pay less (Koppel 1994:26). Of those willing to pay more, the average economic value was
               estimated at $2.72/person per day above the initial use value estimate, and for those willing to pay
               less, the average value was estimated at $1.68/person per day below the initial use value estimate in
               1994. On the basis of this information a weighted average of the economic value of a wider beach
               was estimated to be $4.59/person per day with $0 bids (i.e., $6.94* 165 + $2.54*33 + $4.22*865
               = $4879.22/1063 = $4.59) and $5.41/person per day without $0 bids (i.e., $7.76* 165 +
               $3.36*33 + $5.04*865 = $5750.88/1063 = $5.41) (author's calculations). On average, these
               beach users were willing to pay an additional $.37/person per day for a wider beach in 1994
               dollars (for both cases, including $0 bids and excluding $0 bids, i.e., $5.41-$5.04=$.37, and
               $4.59-$4.22=$.37).


               Concerning the section of the study (Koppel 1994)        'associated with existence value, results
               indicated that the estimated median value was $50 in 1994 dollars (the original report did not
               contain any other point estimates of central tendency of sample distributions such as the mean nor
               estimates of the variability). Assuming a 92-day season, nonuse value is estimated at $.5435/day.
               This would yield an overall economic value (sum of use and nonuse value) of $.9135/day.
               However, because mean values are preferred measures of central tendency of sample data, and the
               fact that the researchers did not examine effects of protest bids and outliers, the estimate of nonuse
               value will not be considered in the remainder of this chapter.


               The second phase of the Koppel (1994) study involved a survey of business owners. General
               information as well as economic value was obtained from a survey of 156 businesses. Economic
               value of beach protection was based on an open-ended CV question fon-nat from face-to-face
               interviews. Results indicated that business owners were willing to pay almost 20% more in taxes
               (19.95% more) for a wider beach, and an average $181/year per business with $0 bids or
               $256/year per business without $0 bids in 1994 (authors calculations). As a result of the small
               sample size, little confidence can be placed on these responses and they will not be considered for
               further analysis.


               The third phase of the Koppel (1994) study consisted of a survey of 621 homeowners. Survey
               results found that 80% of the homeowners were not willing to pay more in taxes/payments for a
               wider beach (i.e., beach protection), 17% were willing to pay more, and 2% indicated they would
               pay less. This is surprising because homeowners are one group that would gain the most from
               shore protection efforts. If the sample were stratified on the basis of proximity to the beach,
               responses might have been different. Survey results indicated that the midpoint of the estimated
               median value of households willing to pay for a wider beach was $35.50/household with $0 bids
               ($25 - owners surveyed at home, $46 - owners surveyed at the beach) or $229.50/household
               without $0 bids ($380 -owners at home, $79 - owners at the beach) in 1994. This also represents

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                a relatively low sample size; 1.5% of all available homes in these communities. Again, little
                confidence can be placed on these estimates and these estimates will not be considered for further
                analysis.


                In addition, the Koppel (1994) study conducted two separate surveys of beach users for the
                communities of Brigantine and South Stone Harbor (results of South Stone Harbor were not
                provided in the report, but, it is believed similar information was obtained). The Brigantine survey
                represented the need to obtain specific information for the ACOE concerning perceptions of beach
                use and beach protection; infori-nation about economic value was not included in this survey.
                Information collected and contained in the report (Koppel 1994) related to perceptions about
                physical appearances of different beach nourishment projects.


                Kucharski (1925). In a subsequent analysis, Kucharski (1995) in an unpublished masters thesis,
                used the estimates cited above and projected them to obtain estimates in 1994 for: 1) all beaches in
                the 5 communities, 2) all homes in the 5 communities, and 3) aU businesses in the 5 communities.
                Projected estimates in 1994 were almost $ 101 million for the economic value of beach use, $4.8
                billion in lost property value from beach erosion to homeowners, $2.5 billion for existence value
                of beach protection to homeowners, and $1.4 million for existence value of beach protection to
                businesses (all in 1994 dollars).


                Lin-fitations of the combined study effort (Koppel 1994, Kucharski 1995) follow. Neither study
                provided estimates of the variability of the estimated average and median sample values along with
                estimates of a range of values when appropriate; this weakens the overall study and limits
                comparisons with other studies. The relatively small sample size of homeowners and business
                owners/managers raises questions about the representativeness of the data and its variability. Both
                aspects limit the usefulness of the data; without some idea of this information one cannot place
                much confidence on the estimates, projected or otherwise. Concerning the economic value
                analysis, the data were not tested for outliers and protect bids (both can result in a significant bias
                of point estimates, i.e., the first and second moments of a sample distribution) and the inclusion of
                outliers and protect bids can bias the estimates upward and increase their relative variability. Tlip,
                result is high sample estimates that are highly variable which one can place little confidence on.
                Furthermore, Kucharski (1995) fails to cite other comparable economic studies based on surveys
                of beach users as well as other studies of the economic importance of beach use and shore
                protection. In both reports (Koppel 1994, Kucharski 1995), neither investigator discusses
                possible reasons for limitations of the study and of the study results, which is a standard practice
                among investigators.




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                More troubling are the projected estimates from Kucharski ( 1995). Throughout the report there is
                a lack of discussion about the theoretical framework used, the research design of the study and its
                survey instrument, the sampling framework, and an appropriate discussion about the derivation of
                the descriptive sample statistics, and possible shortcomings of the estimates. The projected
                estimates are highly questionable being based on relatively small population samples, and hence,
                little can be concluded from this study.


                For the purposes of this report the following studies are used to derive a range of estimated average
                values associated with beach protection: 1) northern NJ (Silberman and Kloch 1988, Silberman et
                al. 1992); 2) southern NJ (Koppel 1994); 3) NH-ME (Lindsay and Tupper 1988); and 4) northern
                NJ (US ACOE 1986). The net economic value from beach use is estimated as follows: from (1)
                $.30/person per day in 1985 ($.39/person per day in 1,992 dollars), from (2) $37/person per day
                in 1994 ($.35/person per day in 1992 dollars), from (3) $.33/person per day in 1988 ($.39/person
                per day in 1992 dollars), and from (4) $.24-$.26/person per day in 1985 (or $.32-$.34/person per
                day in 1992 dollars). Based on these estimates a low estimate of net economic value is about
                $35/person per day in 1992 dollars (from (2) and (4)), and a high estimate of $39/person per day
                in 1992 dollars (from (1) and (3)). Hence, the net economic value associated with beach protection
                for recreational use is estimated to range from $35/person per day-trip to $39/person per day-trip
                in 1992 dollars.




                Beaches, Tourism and Economic Development
                Recently, a series of articles have begun to examine the issue of the role of beaches in tourism
                activity, economic activity, and in economic development (Stronge 1994 and 1995, Houston 1995a
                and 1995b). Because these articles have appeared after the 1981 NJSPMP, some discussion is
                necessary. The basic theme of these articles is that tourism expenditures in beach communities is
                attributable to the presence of the beach and that spending can significantly contribute to local,
                regional, and possibly, national economies. Although one can find little to debate about the general
                nature of tourism in beach communities, two claims of. these researchers that are open for debate is
                1) whether or not spending in beach/coastal communities contributes significantly to local
                economies and/or state/regional/national economies, and 2) if all tourism expenditures are directly
                related to the presence or proximity of the beach.


                Regarding the issue of the association among tourism spending and proximity of the beach, this is
                basically a sampling issue. In New Jersey, counties such as Monmouth, and Ocean counties
                extend well inland from the shoreline, in excess of 30 miles in some areas (this is also true of some
                coastal counties in Maryland, Connecticut, and Massachusetts, for example). Within coastal
                counties, then, tourism spending in areas that are not located in close proximity to the shoreline and

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                beach are probably not influenced by the beach, that is, there is no beach effect in these cases, and
                one can expect that these expenditures would occur regardless if the tourist attractions or business
                entities were located in close proximity to the shoreline or were located far inland. The use of
                county-level statistics and county expenditure data, then, can be misleading in that it contains an
                unknown portion of economic activity that is located well inland (i.e., not in close proximity to the
                shoreline) that has no beach effect, with the effect of introducing an unknown, upward bias in
                county-level statistics. For example, should sales made at shopping malls located 30 miles inland
                while on a visit to the beach be included as beach trip expenditures? Or should economic activity
                from business units located inland and included in county-level data represent coastal economic
                activity? (Such data were used in a recent assessment of the National Coastal Zone Management
                Program as representative of coastal economic activity (Univ. North Carolina 199 1). Use of such
                data does not connote endorsement; it can lead to strong upward biases and portray a misleading
                picture. Research effort should be placed in developing more appropriate data.) Without knowing
                the distribution of economic activity within particular coastal counties, it is not possible to
                determine the amount of economic activity such as tourism spending associated with a beach effect
                from the remainder of the county-level activity, nor the magnitude of the upward bias in coastal
                county-level data if used for the purpose of representing coastal economic activity. This limits the
                usefulness of county-level data and researchers should use caution in their use and interpretation of
                county-level data.


                A number of points should be kept in mind when considering the role of coastal tourism in
                local/national economies. One concern is the purpose of the trip; a specific trip made for the
                purpose of beach recreation is a distinct trip, a trip made to visit friends/relatives and recreational
                attractions not located at the shore area coupled with some of the time spent at local beaches is a
                multi-purpose trip. One must be careful to account for the time or proportion of the trip that was
                only spent at the beach, or that involved a specific trip to a beach. (The time/proportion of the trip
                not spent at the beach is irrelevant.) Another concern is to identify expenditures that are uniquely
                related to the presence of the beach (and or beach trip) or related to the proximity of the beach.
                This problem becomes compounded for multipurpose trips. A case could be made whether
                expenses other than lodging, food, entertainmen                               fees (parking or beach
                                                                  t, transportation, entrance
                should not be directly related to beach use activities. For example, should expenses of durable and
                nondurable goods (small appliances, clothing other than beach apparel) made because of shopping
                convenience and leisure time be included as typical expenses from beach trips. Studies that have
                examined impacts of tourism to local economies discussed below, are all based on field survey
                data. The use of surveys and survey data, and sample design introduces concerns. In these
                studies and in future attempts, one needs to identify only relevant expenditure items made by beach
                tourists/users, and determine the appropriate trip expenses or proportion of total trip expenses due
                only to beach related trips/visits before tourist expenses are projected. Such a process will avoid

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               the problem of artificially inflating projections of tourist expenditures. For example, if only 50%
               of total expenses are relevant and pertain only to beach use from a particular survey, projected
               estimates of total expenses for a region/state would then contain an error of 50%; the sample and
               projected estimates should be reduced by half. Care must be used in developing any projections of
               sample-survey data, because the projected estimates, in turn, form the basis of arguments of the
               relative contribution of coastal tourism to local/regional econornic activity.



               Stronge (1994, 1995). In two papers, Stronge (1994, 1995) advances the case for the importance
               of beach tourism in relation to shore protection, although this issue was first addressed by Bell and
               Leeworthy a decade earlier, in the same journal (1985, 1986, 1990). (None of these references are
               cited. by Stronge.) Stronge (1994) used survey data from the Florida Department of Tourism to
               advance the case for the economic importance of beach tourism. In the survey and in the article,
               beach tourists were identified on the basis of a response to a question about what particular
               facilities and programs they enjoyed during their visit/trip. Beaches were one of the options
               tourists could check off; those that checked off this category were classified as beach tourists.
               Econon-dc impacts were estimated on the basis of the average expenditure of beach tourists, the
               percent of surveys that had the response of beaches checked off (to represent a participation rate),
               and statewide multipliers obtained from the U.S. Bureau of Economic Analysis Regional Input-
               Output model. The economic impact from direct spending of beach tourists was estimated at $7.9
               billion in 1992 in Florida. Other economic impacts estimated pertained to output (i.e., sales),
               earnings (i.e., income) and employment Oobs), Stronge then claims that the contribution of beach
               tourism to Florida's GDP (referred to as Gross Regional Output in the paper) was estimated at
               $15.4 billion; this estimate comes from the economic impact estimate of output (1992; Table 2, pg.
               7 and pg.8). This claim is simply wrong, economic impacts of sales that are based on multipliers
               contain double-counting and do not represent GDP measures (see the discussion in the first chapter
               on the misuse of economic impact measures). It was unfortunate that such a claim was made by an
               economist, but the damage was already done, and Houston (1995a and 1995b) cites Stronge's
               estimates as fact.


               Houston (1995a and 1995b). Houston (1995a and 1995b) further extends the arguments of the
               impacts of beach tourism following Stronge (1992). In both papers, Houston takes the Stronge
               result, compares it to overall tourism spending, estimates a ratio between beach tourism spending
               and overall tourism spending, and projects beach tourism spending on the basis of this ratio for an
               estimate of the beach tourism portion of the state GDP, an estimate of $170 billion for all coastal
               states in the U.S. (Houston 1995a). As in Stronge (1992), this projected estimate is based on
               economic impact measures and contains double-counting. It is not to be interpreted as a measure


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                of GDP. Unfortunately, the press tends to sensationalize such estimates which will only cause
                confusion about the importance of beach tourism in the future.


                Notwithstanding that the nature of tourism in coastal areas can create impact effects (spending
                effects over and above residents' spending) and possibly contribute to economic development if the
                tourism effect is large enough, several shortcomings of the Stronge and Houston papers weaken
                their results and deserve discussion, besides the obvious misinterpretation of economic impacts as
                aggregate economic activity measures (i.e., GDP). The Stronge paper identified beach tourists on
                the basis of whether or not tourists enjoyed Florida beaches during their visit to Florida. Such
                information is misleading, it does not state whether or not tourists actually did visit or spent time at
                beaches in Florida during their visit. Such a procedure can identify both users and non-users.
                More appropriate information would consist of the number of beach trips (day-trips) taken during
                the visit or the portion of time spent on the beach and/or on beach trips (either the number of days
                or the percent of the total visit). It is surprising that this issue is not even mentioned by Stronge.


                Concerning the Houston papers, further limitations that weaken the analyses are the following.
                Houston uses statistics from secondary, unofficial sources such as The World Almanac, and press
                reports (USA Today, National Geographic, Wall Street Journal). Secondary statistical sources are
                usually not tested and examined for accuracy as are official statistics published by various branches
                of the government. Therefore, secondary statistics can be quite misleading and can even portray
                the wrong picture. The potential bias and error inherent in secondary source statistics limits the
                accuracy and usefulness of any research based on such data.


                A general word of caution is necessary about the results of the Stronge and Houston papers
                (similar remarks apply to Kucharski 1995). One can conclude little from these papers, the research
                has introduced unknown, upward biases in their estimates; this limits the usefulness of these
                studies, and raises questions about their estimates. Research of this type will only cloud the issue
                of the importance of beach tourism vis a vis shore protection provision. In order for future studies
                to be useful, investigators should be unbiased and interested in the problem rather than the answer.
                The studies should be rigorous, based on accepted research approaches and designs, and ilke
                appropriate statistical data, otherwise only confusion will be the result. It is hoped that future
                researchers will benefit from this hindsight so that future studies will not fall into the same trap as
                these studies have.




                Bell and Leeworthy (1985. 1986). Because of the interest in the economic importance associated
                with beach use, an earlier study by Bell and Leeworthy (1985, 1986) discussed above, will be
                discussed in detail at this point. Bell and Leeworthy (1985, 1986) were the first investigators to

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               conduct a detailed analysis of the net economic value of beach use and the economic importance of
               beach use for an entire state, the state of Florida. Bell and Leeworthy conducted a study based on
               surveys of residents and non-residents. A two-part telephone survey of a random sample of
               residents 18 years and older was conducted. The first part, a sample of 1000 adults, was designed
               to deten-nine the participation rate of beach use in 1983. The second part, a sample of 911 adults,
               was designed to obtain information on beach and travel behavior, and travel expenses in 1983 (a 9
               month period in 1983, and a 3 month period in 1984). (It would have been preferred to have a
               complete calendar year rather than a split year, but it is suspected that respondents interpreted the
               phrase "in the past 12 months" to refer to the 1983 calendar year.) For the purposes of this report
               it will be assumed that the survey data represent the the 1983 calendar year.


               The survey of non-resident tourists involved adding a number of questions to the State tourism
               survey in a two-part design.      The first part involved a cover tally sheet to deten-nine the
               participation rate for beach use among non-residents, a sample size of 4333 adults. The second
               part was designed to obtain information about beach and travel behavior, and expenses involved
               from a sample of 826 respondents that participated in beach use. Non-residents were personally
               interviewed at major exit sites (airports and auto travel sites) during 1984 (January -November) - A
               similar problem arises with the non-resident tourist survey data concerning the time frame the data
               represent. For the purposes of this report it will be assumed that the expense data reflect the 1983
               period.


               Overall survey results indicated that an estimated average of $450/household per year was spent by
               residents, and an average of $395/household per year was spent by non-residents that visited
               Florida beaches in 1983. The estimated average travel expense was projected on the basis of the
               participation rate (inverse of participation rate times the average travel expense), to yield total
               expenditures associated with beach use estimated at $2,276 million in 1983 ($1,123 million for
               residents and $1,152 million for non-residents). These total expenditures are referred to as total
               sales impacts by Bell and Leeworthy; this is a slightly misleading term because this estimate
               reflects actual sales directly related to beach use and not impacts resulting from these sales.
               Economic impacts are then derived in terms of output (i.e., sales), employment (i.e., jobs), wage@s
               (i.e., income or earnings), and state tax revenues. However, the impacts are not derived in the
               typical manner; impacts for residents are not based on input-output methods but are projected based
               on ratios, and an export based theory is used to derive impacts for non-residents (Bell and
               Leeworthy 1986: 8-10, 19-25). Total sales impacts were estimated at $4,581 million from total
               expenses of $2,276 million in 1983.


               Limitations of the Bell and Leeworthy (1986) study concern the derivation of economic impacts; an
               input-output methodology was not used for resident's impacts and a non-conventional input-output

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                methodology was used for non-resident's impacts. It is preferable to base the economic impacts
                on standard input-output models of a particular state. Bell and Leeworthy claim that only tourist
                (non-residential) expenses generate induced effects; this simply is not correct. Expenditures of all
                individuals that travel to a local area such as a beach-community will generate both direct effects
                (i.e., economic activity of spending to primary industries - sales of industries in primary sectors),
                indirect effects (i.e., additional economic activity generated from the primary sector to industries in
                secondary sectors), and induced effects (i.e., further economic activity from the secondary sectors
                to tertiary sectors and beyond; that is, money respent by the secondary sectors). This is a standard
                multiplier effect in input-output techniques where there are multiple rounds of impacts generated
                from initial expenditures as the money travels throughout an economy (Leontieff 1966). Other
                limitations are related to the small sample of 911 residents and 826 non-residents, which can affect
                how representative these samples are to the general population of residents and non-residential
                Florida travelers.   That is, whether these sample statistics can reasonably approximate the
                population statistics, as well as the variability of these sample estimates (because large variances
                can occur with small samples). However, Bell and Leeworthy correctly point out the need for a
                two-part survey process; the first part to obtain estimates for participation rates. Additionally, the
                researchers collect data on beach use and expenses and adjust the data on the basis of the portion of
                time actually spent at the beach (or OD the beach trip).         This is necessary when trips are
                multipurpose in nature.


                On the basis of the Bell and Leeworthy study, total sales were projected at $2.27 billion and sales
                impacts were estimated at $4.58 billion to the state of Florida in 1983 ($3.206 billion and $6.452
                billion, respectively in 1992 dollars; Bell and Leeworthy 1986: 30). Stronge (1994) projected total
                sales of $7.9 billion from beach tourists, and output (sales) impacts of $15.4 billion in 1992. The
                Bell and Leeworthy estimates still differ from the Stronge estimates by 2.5 times less for projected
                sales and 2.4 times less for sales impacts (all in 1992 dollars). This emphasizes the reason for the
                concern over the use of survey studies, and the need to isolate expenses just for' the portion of the
                trip dedicated for beach use. Projected expenses of beach use can become easily inflated and
                unrepresentative as in the Stronge and Houston papers.



                Manheim and Tyrrell (1986a, 1986b). An additional argument about the effects of tourism on
                coastal communities has been advanced by Manheim and Tyrrell (1986a, 1986b). Manheim. and
                Tyrrell have argued that the influx of non-resident tourists during the summer season places an
                added, and previously ignored, burden on residents because of non-residents' use of the local
                infrastructure, that in many cases is developed based on the needs of local residents and paid for by
                the local residents through property taxes.        The influx of summer populations in beach
                communities literally explode and the local infrastructure (roads, water, sewerage, waste hauling)

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                either wear out or exceed their designed capacities more quickly. These cost's are not internalized
                nor borne by the non-resident touristg, although they are for individuals that own second, sununer
                homes. The issue mainly concerns the proportion of tourists that use hotel, motel accommodations.
                in relation to owner-occupied homes and apartments. Previous studies have not considered this
                aspect of tourism, and communities that advocate tourism need to take these hidden costs into
                consideration.





                ACOE Studies of Shore Protection
                A detailed review of ACOE studies of proposed projects in New Jersey was beyond the scope of
                this paper. The reader is referred to each of the individual reports (U.S. ACOE 1989a, 1989b,
                199 1 a, 199 1 b, 1992, 1993, 1994a &, 1994b, 1994c, 1,995). In general , the ACOE analyses and
                economic analyses including the CBA are thorough and well done. A brief overview of typical
                ACOE studies and analysis, will be useful. Development of the cost component is very detailed and
                thorough, accounting for all items involved with the project in question. Many of these cost items
                are based on detailed engineering studies. The benefit component is also very thorough and well
                done in general. All recent ACOE studies develop economic benefits to consist of up to 5 items:
                        1) storm reduction benefits,
                        2) benefits from the reduction in lost land,
                        3) benefits from intensification,
                        4) recreation benefits, and
                        5) benefits from reduced maintenance and costs of shore protection at other sites.


                Storm reduction benefits, the first item, measures benefits as the reduction in ston-n-related
                damages prevented by the proposed project (i.e., storm damage w/o (without) the project less
                storm damage with the project). Though this definition is quite simplified, storm reduction
                benefits can consist of up to 5 distinct components and involve sophisticated computer models to
                develop estimates. These five components can be: 1) reduction in the inundation of structures, 2)
                reduction in damage caused by wave attacks to structures, 3) reduction in damage associated with
                long-term erosion and storrn events (storm recession), 4) reduction in maintenance costs associatqd
                with other shore protection projects, and 5) reduction in public emergency costs that would arise
                from storm/flooding emergencies. To avoid double counting of storm reduction benefits, the
                ACOE use a critical damage threshold, whereby only the maximum damage to any single structure
                pertaining to the first three components is used for storm-related damage and as the benefit estimate
                of storm reduction benefits.


                The second benefit item, reduction in lost land is the reduction of the assessed value of real
                property that would be lost from erosion prevented by the project (i.e., the assessed value of land

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                lost w/o the project less the assessed value of land lost with the project) plus the value of the
                recreational component of the lost land when the lost land is identified to be beach/recreational land
                (i.e., derived from an estimate of the amount of beach users the lost land would have supported
                over the beach season valued as the sum of beach fees pLus the economic value of beach use based
                on WTP without project conditions). Intensification benefits, the third benefit item, are benefits
                due to increases in the assessed value of real property related to the presence of the proposed
                project. The forth item, recreation benefits, consist of the sum of the net increase in economic
                value (i.e., measured as willingness-to-pay) from a wider/protected beach for current beach users,
                the net increase in the economic value of additional beach users from a wider/protected beach, and
                the economic value from preserving the beach (i.e., existence value) from non-users (i.e., the sum
                of use and nonuse values). Most current ACOE studies use the Contingent Valuation method,
                although some studies use a unit day value method (a monetary value of the net increase in users as
                a result of the project either valued at an average day trip expense or at an average entrance fee).
                The fifth item pertains to benefits from reduced maintenance of shore protection at other locations
                in close proximity to the location of the proposed project (i.e., derived as the maintenance costs of
                shore protection at nearby locations without the project less estimated maintenance costs of shore
                protection of these nearby locations with the project). It should be pointed out that these benefit
                items used in ACOE analyses may be subject to debate and should not be taken as fact. For
                instance, the third benefit item, intensification benefits, implies that benefits arise from increases in
                the assessed value of real estate in close proximity of shore protection projects. Not all coastal
                researchers may agree with this claim nor have studies been conducted to rigorously examine and
                quantify this effect. Similar comments may apply to the remaining benefit items used in the ACOE
                analyses.


                Lin-dtations of ACOE studies concern: 1) inadequate sensitivity analysis of benefit items; 2) lack of
                a sensitivity analysis of cost items; and 3) little and inadequate treatment of uncertainty in cost and
                benefit items, although some of this is conducted regarding the estimation of storm reduction
                benefits (through the use of storm damage - wave surge computer models to simulate storrn
                damage); the treatment of risk and uncertainty should be more explicit in ACOE studies; 4) no
                treatment of risk involved with project lifespans and project outcomes (this is an area where there'
                                                                                                                       J,$
                much room for improvement); and 5) little or no research to support and validate the specific claims
                of benefits realized from shore protection.


                Recommendations for future ACOE studies pertain to both cost and benefit components as follows:
                1) incorporation of uncertainty in cost and benefit items; 2) incorporation of risk in project
                lifespans and project outcome (e.g., more accurate estimates of lifespans and outcomes based on
                local experience); 3) greater coverage/application of sensitivity analysis to derivation of cost and


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                benefit estimates; and 4) future studies should be performed to address the appropriateness of the
                benefit elements included in ACOE procedures.


                The treatment of uncertainty involves two basic components. One concerns benefit and cost items,
                the other concerns the lifespan of shore protection projects. Regarding the cost and benefit items,
                elements of uncertainty pertain to the frequency of occurrence of cost and benefit items, and
                uncertainty over future monetary value of cost and benefit items. There are some elements of costs
                and benefits of proposed shore protection projects that are stochastic in nature; this affects both the
                frequency of occurrence as well as the magnitude of the estimate for cost and benefit items. For
                example, over a 10-year period, some cost and benefit items may only occur I or 2 times in 10
                years due to the occurrence of significant coastal storms; the magnitudes of costs and benefits can
                also be highly variable (e.g., by orders of magnitudes) at these times in comparison to non-storm
                conditions. In future studies, both of these elements of uncertainty (frequency of occurrence and
                variability of magnitudes) should be incorporated into ACOE analyses rather than the use of
                average magnitudes and occurrences over a given time period. It is preferred to have some idea of
                the range of damage estimates and range of storm damage reductions rather than a point estimate
                such as an average value. (The point needs to be emphasized. In CBA it is preferred to have as
                realistic a situation as possible. If, for example, certain cost and benefit items only occur I or 2
                times in a 10 year period, this needs to be reflected in the CBA. Also, when these cost and benefit
                items occur, their magnitudes will be highly variable and could differ by orders of magnitudes
                compared to the- remaining 9 or 8 years. This aspect should also be incorporated in CBA. All too
                often, the investigator uses the average value over the 10 year period as if it occurs in each period.
                This practice detracts from the realism a CBA should reflect.) As an example, in the analysis of
                recreational benefits (ACOE 1989b), ranges (upper and lower bounds and a mean) are developed
                in the analysis (see pages D-88, D-89). However, in the final analysis of Benefit-Cost ratios this
                range is dropped and the ratios and CBA are based on the mean value.


                Furthermore, uncertainty over the future monetary value pertains to estimates of the value of cost
                and benefit items when the monetary value can vary over time due to inflation and economics of
                scale. This element should also be incorporated into future ACOE analyses.


                Incorporation of risk elements concern the expected project lifespan and the expected outcome.
                Both factors are not known with certainty, and there is a risk that projects may fail to achieve their
                expected lifespans and/or expected outcomes, for example a 10% probability that the project fails
                (in terrns of lifespan and outcome), a 20% chance of failure, etc. based on expectations of the
                occurrence of significant coastal storms over the project planning period. These elements should
                be incorporated into future ACOE analyses. This recommendation must also include an effective



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               monitoring program in which the relative effectiveness of the project can be measured, both in
               terms of achieving its expected outcome and in achieving its expected lifespan.


               The third major recommendation is about expanded application of sensitivity analysis in the
               derivation of cost and benefit estimates. The only sensitivity analysis in ACOE analyses pertains to
               the use of a range of discount rates in the present value analysis of net benefits.           Sensitivity
               analysis could be useful in evaluating project outcomes for different scenarios where both cost and
               benefit estimates take on a range of values. For instance, a range of net benefits for different storm
               event scenarios, e.g., net benefits for low storm activity, moderate storm activity, and high storm
               activity.


               Other recommendations of future ACOE analyses concern the following: 1) incorporation of some
               measure of the variability of the cost and benefit items, 2) use of better damage data from more
               recent storm-events as well as the commonly cited 1962 and 1984 "super" storms (here more
               recent data from FEMA and the NFIP agencies are useful), 3) recreational benefits from increased
               use should incorporate costs of building additional parking facilities to accommodate the new users
               as well as if expanded parking facilities are possible and associated with the estimated increased
               use. In New Jersey, beach use is often limited by parking facilities and/or the absence of parking
               facilities. Furthermore, there is little opportunity and space to expand parking facilities, and costs
               of congestion at beach sites and for travel times that such increased use would impose (will the
               increased number of beach users on the proposed wider beach result in the same use density or a
               higher use density?); 4) also some sensitivity analysis of the distribution of increased beach users
               over the season to contrast with different types of seasons (i.e., differences in weather factors,
               water temperatures, will affect beach use patterns; do we expect that all seasons will be the same
               over a 10 year period (such an assumption is presently made in ACOE analyses)? Then a CBA
               should be based on a scenario of the proportion of seasons with average weather conditions, above
               average weather conditions, and below average weather conditions).


               CBA of proposed shore protection projects should consist of the following overall approach. CBA
               should be based on the present value of the expected value of: 1) costs, 2) benefits, and 3) [4
               benefits over a range of significant coastal storm conditions (e,g., severe (>5 in 10 years),
               rnild/average Q in 10 years), light (I in 10 years), based on past history when appropriate), and
               over a range of probabilities of project failure, and pertain to a range of estimated seasonal
               conditions that would affect the benefit estimates over the proposed project period. Over the past
               three decades, for example, 5 significant coastal storms occurred during the 1960-70 decade, 6
               during the 1970-80 decade, and 7 during the 1980-90 decade. From the data in 1990 so far (12
               significant coastal storms over 1990-96), the 1990's appear to be a decade of high/severe activity.



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                Expenditures and Impacts of Tourism on the New Jersey Shore
                Studies regarding the effects of spending by tourists in shore communities are useful because
                statistics on business sales and activity are hard, if not impossible, to disaggregate into sales for
                shore communities and sales for non-shore communities. Limits to this data are that not all
                business sales and activity are measured, non-tourist expenditures remain unknown. One also
                needs to be aware of the distinction among actual expenses from economic impact effects, and if
                expenses represent direct sales versus indirect sales. (Here, the reader is referred to the second
                chapter for a discussion of terms and concepts, and to the previous section for relevant concerns.)


                A number of studies have been conducted for the State of New Jersey, Division of Travel and
                Tourism that have examined the tourism sector, tourism spending and economic impacts of tourism
                (RL Associates 1987, 1988, Opinion Research Corporation 1989, Longwoods International 1992,
                1994, 1995). Discussion of these studies is warranted for several reasons, 1) these studies have
                generated a great deal of interest from the public concerning the tourism sector, especially
                regarding the Jersey Shore area, 2) coastal researchers are rediscovering the importance of coastal
                tourism and are trying to establish some link between shore protection spending and spending
                generated from coastal tourism, and 3) these studies and interest appeared after the New Jersey
                Shore Protection Master Plan was completed.


                As with any study of the tourism industry that generates impacts, some caution is advised in the
                interpretation of the results. A complicating issue concerning the New Jersey tourism studies is
                that the three different organizations used a different approach, different sampling technique, and
                weighting (or projection) technique. These factors limit comparisons across studies.



                RL Associates and Opinion Research Co[VoLation. The first study funded by the State of New
                Jersey to determine the effects (or impacts) of tourism on the New Jersey Shore was conducted in
                1987 by RL Associates (RL Assoc. 1987). A random sample of all households located in non-
                shore counties in New Jersey, and in local areas in New York, Delaware, Pennsylvania, Ohio, aU4
                Maryland were interviewed via telephone. The same approach was used in their 1988 study of the
                Jersey Shore (RL Assoc. 1988). Opinion Research Corporation (1989) also conducted a telephone
                interview of a random sample of households in the same areas but used a different random
                sampling design than did RL Associates. This in turn affects how the sample data were projected
                (weighted) to generate state estimates of tourism expenditures. Because of these differences (other
                differences exist in relation to the Longwoods approach) one cannot compare the projected
                estimates across studies; these studies can only be used as point estimates of tourism activity but
                not for comparison purposes. (Undoubtedly, this limitation has caused the State of New Jersey

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               much frustration which would like to compare such data over time -- hence the reason why
               Longwoods was contracted to perform four consecutive studies.) A further problem concerning
               these three studies involves the research design. In any study of behavior where participation is a
               key factor such as in recreational activity and in travel and tourism, the research design should
               include a segmented sample design (i.e., a two-part sample) as the travel-tourism study conducted
               by Bell and Leeworthy (1986). The first part is to determine the participation rate, which
               determines the projection (weighting) factor, while the second part obtains the sample data on use
               characteristics and expenditures. The fact that neither RL Assoc. nor Opinion Research Corp.
               discuss this approach in relation to that used, should raise concern and question the confidence of
               the projected estimates.


               Because of the problem of different designs across all three studies, Opinion Research Corporation
               in their 1989 study reprojected (i.e., reweighed) the sample data from the two previous RL
               Associates studies using techniques that were as similar to those used in their 1989 survey study so
               that comparisons could be made across all three studies. With these caveats in mind, results from
               Opinion Research Corp. (1989) indicated that an estimated $6.2 billion was spent by tourists that
               traveled to the Jersey Shore in 1987, an estimated $5.4 billion in 1988 and an estimated $7.4
               billion in 1989 (see Appendix Table 1). As one will see the estimates from the Longwoods studies
               for the Barrier Island component are significantly smaller by a factor than these estimates, hence,
               another reason why the studies cannot be compared.


               Longwoods International. A series of studies were funded by the State of New Jersey and
               conducted by Longwoods International of the travel and tourism industry in New Jersey beginning
               in 1991 (Longwoods Int'l. 1992, 1994a, 1994b, 1995). The Longwoods studies used an entirely
               different design from most studies of tourism; they conducted a two-part survey, one of
               establishments and one of tourists. The first-part was used to collect data on lodging expenditures
               from establishments to increase accuracy and to avoid recall error. The second-part was used to
               collect sample data on tourism expenditures so as to determine the proportion of travel and tourism
               expenditures associated with specific types of accommodations used (e.g., hotels, campgrounds,
               state parks, friends/relatives, day trips, and pass throughs). Once the accommodation expenKs
               were projected (from the first-part survey) the remaining expenditure categories were derived on
               the basis of the proportion of all expenses they accounted for (for example, if hotel expenses were
               projected to $15 million, and if hotel expenses represented 38% of the total expense of tourists that
               stayed at hotels, then total expenditures are projected to be $39.47 million ($15 mill./.38). By
               knowing the proportion that the remaining expense categories represent of the total, estimates for
               these categories can be derived, if food/restaurants represented 25% of the total, its estimate would
               be $9.87 million ($39.47*.25) and so on).



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                Another difficulty with the Longwoods study is that the projected estimates are on a county-level
                basis. Such county-level data cannot represent specific areas such as a coastal zone, i.e., a narrow
                area in close proximity to the the coast. In order to be able to isolate such an area from county-
                level data, one would need to know the distribution of retail establishments/businesses and the
                distribution of economic sales on a location basis within the entire county (e.g., municipality
                basis); such information is either not available or not readily available. This method would still be
                subject to error. As a result of this difficulty, Longwoods included a separate survey component
                within their overall effort to isolate tourism spending activity in the Jersey Shore area, i.e., Barrier
                Island component. Statements about the effect of tourism on the Jersey Shore can then be made,
                but only in reference to this Barrier Island component.


                Longwoods estimated that travel and tourism expenditures in the State of New Jersey represented
                $18-28 billion in 1990 ($18.83 billion in 1992 dollars), $17.84 billion in 1991 ($18.37 billion in
                1992 dollars), $18.6 billion in 1992, $18.91 billion in 1993 ($18.36 billion in 1992 dollars), and
                $22.65 billion in 1994 ($2t.44 billion in 1992 dollars) (Table 2). Keep in mind that these
                estimates represent state totals.     Concerning the coastal counties of Atlantic, Cape May,
                Monmouth, and Ocean, estimated totals were $9.1 billion in 1990 ($9.4 billion in 1992 dollars),
                $8.9 billion in 1991 ($9.1 billion in 1992 dollars), $9.6 billion in 1992, $9.7 billion in 1993 ($9.4
                billion in 1992 dollars), and $12.56 billion in 1994 ($11.89 billion in 1992 dollars). If one treated
                gambling activity as not dependent on the coastal area, then the 4-coastal county totals excluding
                expenditures on gambling would represent $6.5 billion in 1990, $6.4 billion in 1991, $6.8 billion
























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           Table 2.






























































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            Table 2 Cont.































































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            Table 2 Cont.





























































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                in 1992, $6.5 billion in 1993, and $9.3 billion in 1994 (Table 3). Even these figures do not
                represent travel and tourism activity at the Jersey Shore and the above discussion regarding the
                misuse of using coastal county-level data to represent coastal tourism activity is appropriate,
                namely because coastal county data represent inflated economic activity if used as coastal tourism
                economic activity. (Note that these estimates are within the same range as those produced by the
                earlier RL Assoc. and Opin. Rsch. Corp. studies, hence, the earlier studies might represent
                county-level totals, and hence, represent inflated estimates of coastal tourism economic activity.)


                Estimates developed for the Barrier Island component, however only represent one component of
                beach travel and tourism activity (i.e., that portion of tourists that rented accommodations along the
                Jersey Shore), and underestimate the level of travel and tourism activity associated with beach
                travel (other components of beach travel consist of other overnight trips and day trips). In 1992 an
                estimated $740.5 million was spent by tourists and travelers that stayed at barrier island rental units
                (the first year data were collected), $874.9 million in 1993 ($849.5 million in 1992 dollars), and
                $817.3 million in 1994 ($773.3 million in 1992 dollars) (Table 2). In 1994, the barrier island
                component represented 6.8% of total tourism expenditures of the four coastal counties, and 3.6%
                of the state tourism expenditure total. Expressed in terms of a three-year average (1992-94),
                tourism expenditures of the Barrier Island component accounted for an estimated $787.9 million a
                year in 1992 dollars or 7.6% of a similar 3-year average of the 4-coastal county tourism
                expenditure total ($10,314.66 million/year) and 4. 1 % of the 1992-94 average of the state tourism
                expenditure total ($19,289.24 million /year). Excluding gambling expenses the 3-year average for
                1992-94 for the Barrier Island component accounted for an estimated $786.9 million a year in 1992
                dollars or 10.8% of the 3-year average of the 4-coastal county tourism experlditure ($7,265.8
                million/year) and 4.8% of the 1992-94 average of state tourism spending without gambling
                ($16,392.93 million/year).


                Recalling the earlier discussion about the misuse of economic impact measures, the usefulness of
                the Longwoods study is in the generation of projected direct expenditures discussed above and not
                in economic impact measures. Direct expenditures represent the closest activity to aggregate GNP
                estimates, because they represent the sales of final goods and services sold, and do not conta.
                double-counting. Regarding coastal tourism, the Barrier Island component of the Longwoods
                study represents one component of beach travel and underestimates the importance and magnitude
                of tourism expenditure activity in the coastal region of New Jersey. To develop an estimate of
                expenditures associated with beach travel, similar estimates for day trips and other overnight trips
                (i.e., hotel/moteUresort, campgrounds-private and public, and those that stay with friends/relatives)
                for the four coastal counties are necessary. To give some idea of the magnitude of an upper bound
                of beach related expenses, an upper bound estimate based on all three components of beach travel



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               (i.e., barrier island rentals, other overnight travel, and day trip travel) was developed. However, a
               word of caution regarding the interpretation and use of the estimates. The estimates were






















































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              Table 3.































































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              Table 3 Cont.


























































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              Table 3 Cont.































































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               developed for illustrative purposes rather than as a reliable point estimate. The estimates are based
               on two separate Longwoods survey studies, and hence, two different sampling bases, and there is
               some error from double-counting (i.e., from overlap of the two different sampling bases). As a
               result, the estimated travel expense probably overstates beach related travel expenses.


               The Longwoods study for the 1993 season (Longwoods, Int'l. 1994a) was the only year in which
               the New Jersey Division of Travel and Tourism supplied complete information (i.e., all reports
               produced by Longwoods Int'l. for a particular year). The discussion that follows is based on the
               derivation in Table 4. One component of the tourist survey conducted by Longwoods International
               for the State of New Jersey, found that 12% of all overnight trips to New Jersey were beach trips,
               and 4% of all day trips were for beach trips (Longwoods Int'l. 1994b); this allowed a derivation of
               beach trips of 7.62 million trips in total in 1993 (steps I and 2, Table 4). An average trip expense
               was derived from projected total expenses and the estimated total number of trips by trip type
               (barrier island, other overnight, day) (step 3, Table 4). On the basis of the estimated number of
               trips and the estimated average trip expense, an estimate for expenditures of all beach related travel
               was developed at $2,095.877 million with gambling and $1,917.92 million without gambling
               (Table 4). The Barrier Island component represented 41.74% ($874.922M/$2095.877M) of the
               1993 estimated tourist expenditures. If this proportion is representative across other years, the
               three-year (1992-94) estimated average expense for beach trips would account for an estimated
               $1,887.64 million ($787.9 million/.4174); similar estimates of tourism spending without gambling
               are 45.57% ($873.915M/$1917.91M) and $1,726.75 million without gambling. However, the
               reader is cautioned in reading too much into these estimates; they were developed for illustrative
               purposes. Little confidence can be placed in the estimates; such estimates should be developed
               from a single sample base rather than from two, and should be developed as part of an objective of
               the travel and tourism studies in the form of a range. The estimates developed are meant to
               illustrate the point that projected tourism expenses associated with beach trips based on the Barrier
               Island component are underestimates of such activity, while the county-level estimates of the four-
               coastal counties are overestimates. The derived estimate, $1,887.64 million per year over the
               1992-94 period represents 18% of the four-coastal county three-year average, and 9.8% of the
               state three-year average (without gambling expenses the comparable estimate is $1,726.7-5
               million/year representing 23.8% of the 4-coastal county 3-year average, and 10.5% of the 3-year
               state average) illustrating the fault with conclusions that the majority of the State of New Jersey's
               travel and tourism industry is generated from the Jersey Shore, but these statements and
               conclusions have appeared from time to time. Here, effort should be continued to develop
               expenses for all beach trips as an objective of the Longwoods studies.





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            Table 4.




























































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                 Shore Protection Policy Oriented Studies
                 In this section two studies are discussed, the Shore Protection Master Plan for New Jersey, and a
                 study conducted by ICF, Int'l. regarding assessments of alternative shore protection policies.



                 NJ Shore Protection Master Plan (198 1). The 1981 New Jersey Shore Protection Master Plan
                 (NJSPMP) prepared by Dames and Moore evaluated several alternative protection plans for the NJ
                 shoreline based on a Cost-Benefit Analysis (CBA) (NJDEP, DCR 1981). The alternative plans
                 evaluated in the Master Plan were classified as follows: 1) a Storm Erosion Protection alternative
                 (i.e., nourishment equivalent to a 75' berm width with groins or a 100' berm width without
                 groins); 2) a Recreation Development alternative (i.e., a berm width and beach width that would
                 vary based on estimates of future recreational demand for beach use so as to provide a maximum of
                 100 sq. ft./person; either an increase or decrease in both berm and beach width compared to the
                 Storm Erosion Protection alternative); 3) a Combination alternative (i.e., the maximum berm and
                 beach width from the first two alternatives); 4) a Limited Restoration alternative (i.e., protection via
                 nonstructural methods that would be greater than the level' of protection from a Maintenance
                 Program (which would yield the smallest protection level of all alternative plans), but smaller than
                 the protection levels of the above three alternative plans); and 5) a Maintenance Program alternative
                 (i.e., whereby the level of protection would be to repair and maintain existing physical structures in
                 place, and to provide nourishment on an as-needed basis (i.e., to compensate for storm erosion),
                 hence, the Maintenance Program can be treated as a reaction effort versus a preventative effort.


                 Parameters used in the CBA were a 50-year planning horizon (whereby the researchers developed
                 some type of time plan for each alternative program as if each were carried out over a 50-year
                 period including the maintenance, repair, construction of any new hard structures needed and any
                 periodic nourishment to maintain and/or increase beach width), and a discount rate of 9%. It
                 should be noted that only in the case of the Recreation Development alternative, the beach and berm
                 width was estimated to increase with estimated recreation demand over time; in all other alternative
                 plans beach and berm width was essentially held fixed over time (i.e., width was "stabilized" or
                 controlled for processes of natural (long-term) erosion and storm (short-term) erosion).


                 Cost elements consisted of estimated Engineering costs (i.e., those costs necessary to implement
                 each alternative plan), plus estimated Public Service costs (i.e., estimated costs for increased
                 infrastructure capacity from future estimates of the demand for beach use associated with each
                 alternative plan). Engineering cost estimates were developed over the 50-year planning period
                 from projections of levels of engineering and labor effort needed to achieve each plan. Public
                 Service cost estimates were based on the product of the projected number of future beach users
                 (i.e., projected demand) and an average cost of infrastructure use estimated at $1/beach user.

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               Benefit elements consisted of estimated Recreational benefits (i.e., estimated benefits from the
               recreational use of the beach associated with each of the alternative plans), and Property Protection
               benefits (i.e., estimated benefits from protection of property associated with each of the alternative
               plans), both direct benefits attributable to beach protection. Recreational benefits were estimated
               from the product of the projected number of future beach users (i.e., an estimate of future demand)
               and the opportunity cost of beach use estimated at $2/day per user (which represented an average
               beach fee at the time). Property Protection benefits were based on the estimated value of losses
               that would have occurred without the plan in place for each of the alternative plans.


               All estimated costs and benefits were discounted over the planning period, summed, and then a
               ratio of the discounted sum of benefits to that of costs, i.e., a B/C ratio, was calculated for each
               plan on a reach-by-reach basis.


               Because the NJSPMP represents a basis from which all future shore protection plans will be
               developed, and that the emphasis was on the CBA of alternative plans, discussion of several
               limitations of the study are warranted. Being that the research team were mostly engineers, it is not
               surprising that so much emphasis and effort was placed on the cost estimates at the sacrifice of the
               benefit estimates. Estimates of the Engineering costs were probably highly accurate, reasonable,
               and probably varied over time. Limitations of the Engineering cost estimates, if any (since the
               exact costs were not given over all 50 years prior to discounting in the NJSPMP), would exist if
               consideration was not given to changes in prices and costs over time due to inflation and/or
               deflation. It is reasonable to expect that over 50 years, the costs of fuel to operate machinery
               would fluctuate and increase along with labor costs, etc. If these effects were not accounted for,
               the Engineering cost estimates presented could be greatly understated.


               Public Service cost estimates could be limited due to two basic reasons, one associated with the
               projected future recreational use estimates, the other from the use estimate of $1/user. Here the
               rationale is that beach users use available public services to travel to and from the beach as well as
               at the beach and from using these services they derive benefits. However, many users may notke
               residents of the beach community and it is residents that pay for these local public services via
               property taxes. Thus, these costs must be estimated. Limitations of the estimates follow. First,
               forecasts of any variable(s) into future time periods are very sensitive to the specific model and
               variables used. Second, for any forecast some sensitivity analysis or a range of estimates
               associated with the errors of forecast or levels of confidence of the estimates is necessary to give
               perspective of the variability and reasonableness of the forecasts. Third, over time many variables
               regarding the Public Service cost estimate can change; the population and hence the number of
               future beach users, property values and property tax rates can increase, and the cost of providing

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                public services or infrastructure generally increase over time. It is surprising that none of these
                points were discussed by the investigators in the NJSPMP. The accuracy of their forecasts of
                beach use is therefore suspect. Also, the use of a constant figure of $1/user over all 50 years is not
                reasonable and seriously erodes the validity of the estimates for Public Service costs. Again, the
                use of a constant figure over time will tend to understate these cost estimates, and misrepresent
                these costs.


                More importantly, if both cost figures, Engineering costs and Public Service costs were
                underestimated and misrepresented, then any ratio of benefits to costs would favor the benefit side.
                Consider a simple ratio, a/b; to increase the value of the ratio one can either increase the numerator
                (a, which represents benefits here), or decrease the denominator (b, which represents costs here).


                Consider the benefit measures. The measure of Recreational benefits was derived from the product
                of an estimated opportunity cost of beach use ($2/day per user) and an estimate of future use. As
                with Public Service costs there are two components of this estimate, and hence, two basic areas for
                limitations. The first is due to the estimates of future beach use, where the previous discussion
                concerning forecasts applies. The second basic reason concerns the use of opportunity costs as a
                benefit measure, the use of a constant figure across all beaches and protection projects in the state,
                and the use of a figure that does not change over time. Again, the researchers ignore these issues.
                Opportunity costs are not an appropriate measure of economic welfare as measured by the area
                under a demand curve above price, and do not represent economic benefits. The use of a constant
                value across different beaches and protection projects, means that either the researchers or the
                public perceive no differences among beaches located at Cape May versus those at Asbury Park,
                thus, benefits from beach use do not vary across beaches or projects for the same reasons. From a
                research perspective, in order to compare one alternative to another, ideally one would like to have
                some variation in the variables across projects, for example, variation in the marginal benefits
                across projects. Because there are physical differences across beaches along the Jersey Shore, and
                people have different tastes and preferences, one would expect that people should recognize these
                differences and choose to go to specific beaches. In turn, differences in these preferences should
                be reflected in values placed on benefits from beach use as seen in the Lindsay and Tupper (198.9)
                study. Lastly, treatment of benefit estimates across time will tend to understate benefit estimates,
                and in turn, decrease the magnitude of a benefit-cost ratio. The researchers did not discuss any of
                these points.


                Finally, consider the estimate of Property Protection benefits. This was derived from estimates of
                property value, not from actual property value or assessed property value available from tax
                assessors offices. The manner in which the researchers estimated these benefits was by first
                identifying what property would be lost or destroyed over a 50-year period if the protection plan

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                were not implemented for each alternative plan. Then benefits were estimated from a product of
                the number of property structures that would be lost or destroyed by general type (business vs.
                residences) estimated over the 50-year period and an average value for the specific type of property
                structure. This estimate depends on two parts, one part involved a forecast, and the other part
                involved the use of an estimate of the average value for the type of property structure. Limitations
                concern both of these parts. First, the part based on forecasted or future estimates can pose
                problems and the above discussion regarding difficulties of forecasts is appropriate, mainly that the
                researchers should have provided some indication of the size of error or variability of the
                forecasted property lost, a level of confidence associated with the forecasts, and/or some type of
                sensitivity analysis. Second, the use of estimates rather than actual values can introduce biases into
                these benefit estimates.


                In sum, the CBA performed in the NJSPMP is basically static, although some attempt was made to
                incorporate changes that occur over time, namely estimates of future beach use and estimates of
                future property lost or damaged. No attempt was made to incorporate any other dynamic elements
                nor the risk associated with the expected outcome of the projects, where one could introduce
                uncertainty into the derivation of net benefits (benefits less costs). A dynamic analysis would
                compare and contrast the monetary value of a projects' outcome if completely certain versus that
                with the presence of uncertainty. In the case of beach protection, possible risk factors could
                involve such effects as erosion and storm damage, that could cause any project from not being
                100% completed, uncertainty over available funds to ensure 100% completion of any project over
                the planning period, and uncertainty over the estimated number of future beach users and the value
                of estimated future property structures lost versus protected. In addition, the effect of sea-level rise
                in the future would increase the risk and magnitude of erosion and storrn damage. Probably the
                most serious fault is the problem of downward bias in both the cost and benefit estimates which
                would tend to introduce either an upward bias or a downward bias in the magnitude of the B/C
                ratio, respectively, distorting the BIC ratio. The net effect is ambiguous, but places concern over
                the validity and accuracy of the CBA in the NJSPMP.



                ICF (19891. One of the only studies that examined policy options for areas within the coastal
                floodplain was conducted by ICF, Inc. (1989) for the New England/New York Coastal Zone Task
                Force of a study of coastal floodplain management. The objectives of the study were to deten-nine
                the following: 1) costs and revenues associated with governmental entities as a result of
                development in the coastal floodplain; 2) costs and revenues of various policies targeted at coastal
                erosion and storm damage in the coastal floodplain;'and 3) how these costs and revenues depend
                on sea-level rise. In regards to (1), revenues consisted of revenues from coastal development,
                tourism and recreation; costs were due to damages from erosion and storm-events, and from

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                protective efforts. Specifically, revenues consisted of the sum of property taxes, income taxes,
                beach use fees, sales taxes, tolls, utility charges, accommodations taxes, and flood insurance
                premiums. Costs consisted of maintenance costs of local government services and infrastructure,
                maintenance costs of protective structures, fire protection, flood insurance claims, storm clean-up
                charges, costs of beach nourishment and dike building, and property acquisition.


                The following policy options were evaluated: 1) no response, 2) beach nourishment only (to
                maintain the beach width, but not for protection of public and residential structures in close
                proximity to the beach), 3) dikes only (i.e., revetments or seawalls; the report is not clear), and 4)
                property acquisition (when damage in excess of 50% of the value for any structure occurred).


                Two locations in New Jersey were examined as case studies, Ocean City and Strathmere, New
                Jersey. Results of the study indicated the following: 1) revenues to government entities from
                storm-event damage and protection were estimated at $114.4 million for Ocean City and $9.9
                million for Strathmere in 1987; 2) costs due to damage and protective efforts were estimated at
                $130.6 million for Ocean City and at $3.2 million for Strathmere in 1987. The remainder of the
                study examined the effects of sea-level rise on the combined revenues lost and added costs for the
                above policy options at specific points in time, "snapshots" (i.e., 2025, 2050). Tables 5 and 6
                contain these results for Ocean City and for Strathmere, respectively.           ICF concluded the
                following: 1) the no-response option realized large losses and added costs in both "storm" and
                "non-storm" conditions over time; 2) the option of beach nourishment prevented substantial losses
                and added costs in "non-storm" conditions, but incurred large losses and costs in "storm"
                conditions because of washouts; 3) dike projects incurred large costs and losses in "non-storm"
                conditions reflecting one-time construction costs, and large losses and costs in "storrif' conditions
                over time because of deterioration of dikes over time (i.e., their assumed lifespan appeared to be 25
                years); and 4) the policy of property acquisition resulted in losses and costs -of an order of
                magnitude higher in "storm" conditions reflecting one-time property costs, although over time
                revenue losses and added costs were less than all other policy alternatives (policies 1-3) under
                "storm" conditions. (It would be useful to know more about the effects of cumulative losses and
                added costs over time in these comparisons rather than the static approach taken here.) Simi*
                remarks apply to Strathmere.


                Policy findings of the study were the following: 1) "new" development in coastal floodplains was
                found to be a net cost to governments, "existing" development in many cases was worth
                protecting; 2) the "best" policy response was found to depend on the following factors a) the
                existing level of development, b) costs from damage, and c) magnitude of revenues gained; 2.a) in
                areas that are relatively less-developed, beach nourishment was found to bea viable policy; 2.b) in
                areas with high levels of development, protection via dikes was found to be a viable policy where

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                                                                coastal economics
           large amounts of property could be damaged and where dike building could be coupled with a
           policy of halting further development; 3) optimal policies differed over time; and 4) the use of
           subsidies, e.g., NFIP, was found to have important consequences on development (in the
           promotion of development).


           Table 5.























































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           Table 6.




























































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                Policy recommendations offered by ICF were for two categories, 1) future development, and 2)
                existing development. Concerning future development, ICF recommended that: 1) continued
                large-scale development would be a net cost to governments (costs greater than revenues); 2) NFIP
                should tighten the availability of flood insurance to discourage future development (such action
                would have an effect similar to one where property owners are charged the full costs of flood
                insurance); 3) policies should be implemented whereby property owners are charged the full costs
                of cleanup and repairs; 4) policies should be designed to prohibit reconstruction of structures and
                land should be rezoned following significant storm damage (e.g., when 50% or more of a structure
                is damaged); and 5) governments should establish future policies on shore protection and announce
                these to the public (the idea, is that if governments pre-committ to a policy of no provision of shore
                protection in areas facing "new" development, this will create disincentives for future development
                and cause property-owners to internalize and bear the full costs of damage and cleanup).


                Regarding existing development, ICF admits that policy choice "is not an easy answer," (ICF
                1987:60). Recommended policy options were found to depend on development levels; in areas
                with high levels of development it was recommended that policies protect existing structures,
                whereas in areas with low levels of development, policies of protection were not recommended,
                but recommendations of property acquisition, rezoning, tightening of insurance, and having
                owners assume the full costs of damage and cleanup and accept losses of capital investment in
                buildings and from losses of the tax base were.


                The main limitation of the study was that it contains only "snapshot" views, distinct years rather
                than cumulative effects over time; hence it is somewhat static, whereas the evaluation of tradeoffs
                among policies should be in an intertemporal context. Other limitations regard the derivations of
                added costs and lost revenues. Concerning lost revenues in property, sales and income taxes, it is
                not clear if all private households and residences located in the coastal communities in the study
                were included or if only those residences in close proximity to the beach were included in the
                analysis. Inclusion of income tax as a revenue item only makes sense for year-round residents and
                not for summer residents with a second home; again it is not clear why income taxes were used and
                who they pertain to in the study.


                In general the ICF study is to be commended for the treatment of many complex issues involved
                with the provigion of Khore protection and in the exwnination of the tradeoffs amons policy
                options. Investi5ators planninS  Futur' FOlivy 9@lvntvd utudlvo hayr. mu@;h to gain from the ICF
                5tudy.




                Assessments of ACOE Projects

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                Two studies have been recently completed that examined overall ACOE projects and beach
                nourishment in general. One is a self-study conducted by the ACOE (U.S. ACOE 1994d), the
                other is an evaluation of national beach nourishment projects conducted by the National Academy
                of Sciences, National Research Council (NRC 1995).



                ACOE (1994d) Self-S11Ldy. The ACOE self-study was the first phase of a two-part process that
                examined cost and beach fill comparisons of ACOE beach nourishment projects over the 1950-93
                period, a total of 56 projects (the second part will examine the contribution of shore protection to
                economic development). The objective of the study was to determine how well the ACOE staff
                was able to estimate beach nourishment costs and beach fill actually needed. Results of the study
                indicated that total costs of these 56 projects were $670.259 million with $403.255 mfllion as the
                federal cost share (in current dollars) or $1489.5 mill ion with $881 million the federal share in
                1993 dollars (these estimates are from the Executive Summary pg. xv; different figures are cited in
                the text as $1459.306 million and $850.712 million as the federal share in 1993 dollars, pg. 64).
                The amount of beach fill deposited was 167 million cubic yards (sum of fill from 39 of 49 beach
                restoration projects and 33 of 40 beach nourishment projects).


                Comparisons of estimated versus actual costs and fill quantities were developed for 80% of the 56
                projects. These comparisons indicated that actual costs were 4.4% less than the estimated project
                costs ($1340.9 million vs. $1403 million, actual vs. estimated, respectively in 1993 dollars).
                Regarding quantities of fill, comparisons indicated that actual quantities of fill were 5.4% greater
                than estimates of fill (158.4 million cu. yd. vs. 167 million cu. yd., estimated  *vs. actual). The
                second phase of the ACOE self-study will concentrate on benefits realized versus estimated
                benefits and the possible effects on devel opment. Limitations of the study pertain to the selection
                of studies analyzed, and to the technique used to convert current dollar measures to 1993 dollar
                measures (constant dollars), the use of a non-conventional price index rather than a price index
                developed by the statistical branch of the federal government (e.g., wholesale price index such as
                the Producer Price Index).



                NRC (1995) Study of Beach Nourishment. The NRC study (1995), convened a panel of experts
                to examine and evaluate beach nourishment projects in the U.S. Conclusions of the study were
                that beach nourishment was found to be a viable protection option to coastal communities and a
                boon to tourism. However, this depends on the following: if projects are well-designed, well-
                built, and provided in areas that experience relatively minor levels of erosion. In the past, many
                projects failed, the panel concluded. The panel recommended that projects need to be monitored
                and evaluated on a periodic basis, and recommended that future ACOE analyses incorporate risk

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               and uncertainty into the economic and CB analyses as well as use the latest economic approaches
               (such as CV techniques based on referendum-type formats) (Bockstael 1995, NRC 1995).
                                    Characteristics of Typical Beach Fill Projects in New Jersey
               The following is meant to serve as a preliminary exercise to illustrate several points regarding
               economic analysis and CBA of shore protection projects covered earlier. The approach below
               examines typical beach fill projects on a reach basis (i.e., average characteristics of beach fill
               projects that were identified to have an estimated life span as estimated in the technical appendix),
               and benefits from shore protection are only based on the recreational use component. Because no
               other benefits are considered the analysis below is only hypothetical; its purpose is meant to
               illustrate application of techniques rather than an evaluation of tradeoffs among various beach fill
               projects or evaluation of alternative policy options.


               The analysis that follows is based on past New Jersey s  hore protection projects for the cases of 1)
               beach fill, and 2) combined soft and hard protection. Average characteristics were developed to
               represent typical project efforts for these two categories. The information that was useful from
               past shore protection projects consists of: 1) the average size (amount of fill for beach nourishment
               projects); 2) the average cost; 3) the average actual life; and 4) the average expected life. Combined
               soft and hard protection projects were identified on the basis of occurrence of the type of project
               (hard vs. soft) within the same municipality or reach. For example, if a municipality had one or
               more hard protection projects and one or more beach fill projects completed within the 1960-94
               period, these projects were treated as representative of combined protection efforts, case 2.
               Communities that did not have hard protection projects but did have beach fill projects completed in
               the 1960-94 period were treated as representative of scenarios of beach fill projects only, case 1.
               Communities that did not receive beach fill projects, but did have one or more hard protection
               projects completed during the 1960-94 period were treated as representative of hard protection
               only.


               Costs of the project were assumed to be represented by the reported and estimated total costs
               associated with each project effort.      Project costs are aggregate costs, costs could not be
               disaggregated into the components discussed in the NJSPMP because they were not recorded npr
               archived in this manner. Furthermore, project costs account for the final total cost of the project;
               project costs were not available on a monthly basis or any other time basis. Complications arise
               when projects cover one or more years from start to end when adjusting the costs to a constant
               dollar measure. In these situations, the year a project was completed was assumed to represent the
               year costs were measured in. For example, a project completed in 1967 was assumed to be
               measured in 1967 dollars.





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                Benefits that are considered are only recreational benefits. Economic impacts of tourism are not
                considered as benefits in this analysis because impacts do not measure the same economic effect as
                the economic value from beach use as pointed out in the second chapter, and contain double-
                counting. Furthermore, the use of trip expenditures developed from the beach tourism studies
                reflect the costs of taking a beach trip, the economic value from beach use is a economic value over
                and above these costs, a net value from beach use. The derivation of economic value was based on
                an average of economic values over all studies discussed in the literature review. Four values are
                measured, 1) the economic value without protection projects, 2) the value with protection projects,
                3) the net economic value due to protection (value w less value Wo), and 4) the existence value
                from knowing a beach is preserved via protection. An important component of this derivation is
                information of beach use. Because information of beach attendance is not recorded, infon-nation of
                the number of beach tags sold (which is recorded) served as a proxy for beach use. Unfortunately,
                not all communities readily supplied beach tag sales for the 1960-94 period (see Appendix Table
                2). The economic value of recreational beach use is estimated from the product of the average
                number of beach tags sold, the average economic value (a low of $.35/person per day and a high
                of $.39/person per day in 1992 dollars), and an estimate of the average actual fife of a typical
                project.


                Results are contained in Table 7. Conclusions that emerge from an examination of the illustrated
                data are that on the basis of costs and recreational benefits of a typical beach fill project in Reach 2
                through Reach 14, benefits other than recreational benefits must be realized for a typical project to
                yield positive net benefits. On the basis of the estimated average lifespan of a typical project, a
                different set of conclusions is reached. Typical projects in Reach's 8 and 6 had the lowest
                lifespans, followed by typical projects in Reach's 2, and 3; typical projects in Reach's 10, 12, 9,
                7, 4, and 14 had the longest average life (in descending order of years). However, because the
                average estimated life of a typical project differed as well as the scale of the project, economic
                analysis and CBA become complicated and must incorporate these elements into the analysis.


                A hypothesis examined in this section was whether there were any differences in estimated average
                characteristics among typical beach fill projects if hard protection structures were present versus ap
                presence of hard structures. Specific hypotheses were:
                        1) whether the estimated mean project cost was equal given the presence of hard structures
                versus their absence;
                        2) whether the estimated mean quantity of beach fill was equal given the presence of hard
                structures versus their absence; and
                        3) whether the estimated mean effective life was equal given the presence of hard structures
                versus their absence.



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                                                                                                 DRRFT - July
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               Preliminary results are contained in Table 8. Overall, a typical beach fill project combined with the
               presence of hard protection structures appeared to have a larger average amount of fill deposited
               (318,349 cu yds vs. 289726 cu yds), a higher average cost ($1,034,194 vs. $833,651), and a
               higher actual lifespan (12.9 yrs vs. 8.1 yrs). One possible explanation is that beach fill projects
               where hard protection structures are in place were typically larger soft protection projects (used













































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                                                                   coastal economics
           Table 7.






























































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                                                                          coastal economics
            Table 8.






























































                                                                                               -:7-.

















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                                                                                           coastal economics
               more fill and cost more), and the presence of hard protection structures appears to have increased
               the effective life of these beach fill projects possibly by lowering the erosion rate. Future papers
               need to explore this issue in more detail.





                                                     Policy Recommendations
               Much of what follows regarding policy recommendations comes from the ICF study (1989) of
               coastal flood zones. Policy recommendations offered by ICF were for two categories, 1) future
               development, and 2) existing development. Concerning future development, ICF recommended
               that: 1) continued large-scale development would be a net cost to governments (costs greater than
               revenues); 2) NFIP should tighten the availability of flood insurance to discourage future
               development (such action would have an effect similar    to one where property owners are charged
               the full costs of flood insurance); 3) policies should be implemented whereby property owners are
               charged the full costs of cleanup and repairs; 4) policies should be designed to prohibit
               reconstruction of structures and land should be rezoned following significant storm damage (50%
               or more); and 5) government should establish future policies on shore protection and announce
               these to the public (the idea, is that if governments pre-committ to a policy of no provision of shore
               protection in areas facing "new" development, this will create disincentives to future development
               and cause property-owners to internalize and bear the full costs of damage and cleanup).


               Regarding existing development, ICF admits that policy choice "is not an easy answer," (ICF
               1987: 60). Recommended policy options were found to depend on development levels; in areas
               with high levels of development is was recommended that policies protect existing structures,
               whereas in areas with low levels of development policies of protection were not recommended, but
               recommendations of property acquisition, rezoning, tightening of insurance, and having owners
               assume the full costs of damage and cleanup and accept losses of capital investment in buildings
               and from losses of the tax base were.






                                                             Summary
               On the basis of the literature reviewed a brief summary follows. The basic issue one would like to
               address concerns whether the deposition of sand on the beach generates tourism and/or econon-dc
               benefits. One can think of the coastal zone as a kind of "economic engine" in the sense that the
               coastal zone generates economic activity, such as income, sales, and jobs via tourism and
               businesses that are water-dependent and/or require to be located in close proximity to the coastal
               area. The above studies and investigators attempt to address different components of the beach fill

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                                                                                          coastal economics
               - economic activity question. However, because the above studies are based on different research
               and sampling designs, and have different objectives, the data and results are too fragmented for
               one to develop reliable estimates of economic activity. This means that the data from the literature
               are inadequate to develop point estimates of the magnitude of the economic activity associated with
               the coastal zone. Furthermore, studies that have tried to estimate the level of activity from coastal
               tourism have tended to ignore the effect of beach nourishment on coastal tourism activity. Data
               from the above coastal tourism studies are inappropriate to address the issue of whether beach
               nourishment projects on their own, generate economic activity. In order to isolate and address the
               issue, investigators must develop studies that incorporate research designs to isolate economic
               activity dependent on the coastal zone and/or on specific beach nourishment projects. Such studies
               may require data on economic activity and tourism expenditures that are location-specific, in terms
               of the relative proximity to the shoreline, and to beach nourishment projects, and be collected on a
               seasonal basis. Such data is sensitive and generally hard to collect. However, without it one may
               not be able to advance beyond the current level of analysis and findings.





                                               Recommendations for Further Study
               Recommendations for further study that were identified from this preliminary economic
               investigation comprise the following:


               1) a variety of economic techniques such as CBA, Input-Output models, simulation models, risk-
               return models, and other relevant economic approaches needs to be explored to determine their
               relative importance and usefulness in policy-oriented studies of shore protection and in their
               assessment of tradeoffs among the policy options to determine whether or not all economic
               techniques provide similar policy recommendations (there is a possibility that different policy
               outcomes could result from different techniques because the techniques emphasize different criteria
               and information);


               2) the building of pertinent databases, which        involves the collection and development of
               appropriate data necessary to specific economic approaches will be depend       ent on the specific
               approach and can be a very lengthy process. Some of these data can be gathered from the
               respective ACOE districts (especially for inventory surveys of physical structures), some will
               involve statistics and data generated from the state government;


               3) studies with research designs to isolate and identify economic activity dependent on the coastal
               zone and/or on specific beach nourishment projects. Such studies.may require data on econon-dc


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                                                                                                     ORRFT - July
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               activity and tourism expenditures that are location-specific, in terms of the relative proximity to the
               shoreline, and to beach nourishment projects, and be collected on a seasonal basis;


               4) resources recommended for support of economic studies are estimated to be in the $ 100,000 to
               $150,000 range depending on the 1) time frame, 2) economic method, 3) range and detail of
               alternative policy options to be assessed, 4) treatment of risk and uncertainty, and 5) level of detail
               required of the data. However, such an estimate could quickly become a lower bound range
               involving a team approach of economists and expenses of $75,000 - $100,000/year for several

               years;


               5) the ICF (1989) study is an exercise that demonstrates the complexity of the issues involved in
               public policy tradeoffs. However, this is the tip of the iceberg; an analysis should be intertemporal
               rather than static; performing an analysis that is intertemporal and involves many cost and benefit
               components is an extremely tedious and complex task; resources of time and funding must match
               the complexity of the problem;


               6) the analysis must incorporate the elements and effects of uncertainty in benefit and cost estimates
               since these depend on the probability of storrn occurrence as well as the magnitude of the storm;
               hence cost and benefit items are stochastic in nature and vary according to storm severity, time and
               sea-level rise;


               7) the analysis must also incorporate the element of risk associated with project failure and
               outcome; and


               8) the ICF (1989) study demonstrates that there are many more elements to consider regarding
               policy tradeoffs (level of development, future vs. existing development, level of erosion, storm-
               events, availability of flood insurance, who should bear the burden of flood insurance and that of
               cleanup and repair costs, land rezoning issues, reconstruction policies, and future shore protection
               policy stances); future analysis must be designed to incorporate these numerous and varied
               elements.






                                                             References
               Bell, F.W. and V.R. Leeworthy. 1985. "An Economic Analysis of Saltwater Recreational
               Beaches in Florida, 1984." Shore and Beach (April): 16-2 1.

               Bell, F.W. and V.R. Leeworthy. 1990. "Recreational Demand by Tourists for Saltwater Beach
               Days." Jrn. of Environmental Economics and Management. 18:189-205.


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                                                                                   coastal economics
             Bell, F.W. and V.R. Leeworthy. 1986. An Economic Analysis of the Importance of Saltwate
             Beaches in Flori . Florida Sea Grant College, SGR-82, February.



             Bockstael, N.E. 1995. "Economic Concepts and Issues: Social Costs and Benefits of Beach
             Nourishment Projects." Appendix E, In NRC. 1995. Beach Nourishment and Protection.
             National Academy Press: Washington, DC.

             Curtis, T.D. and E.W. Shows.       1982. Economic and Social Benefits of Artificial Beach
             Nourishment Civil Works at Delray Beach. Prepared for FL DNR, Div. of Beaches and Shores,
             September.

             Curtis, T.D. and E.W. Shows. 1984. A Comparative Study of        -Social Economic Benefits of
             Artificial Beach Nourishment - Civil Works in Northeast Florida. Prepared for FL DNR, Div. of
             Beaches and Shores, July.

             Freeman, A.M. 1979. The Benefits of Environmental Improvement. Johns Hopkins University
             Press: Baltimore, MD.

             Gittinger, J.P. 1972. Economic Analysis of Agricultural Projects. Johns Hopkins University
             Press: Baltimore, MD.

             Houston, J.R. 1995. "Beach Nourishment." Shore and Beach (January): 21-24.

             Houston, J.R. 1995. "The Economic Value of Beaches." The CERCular. Vol. CERC-95-4
             (December): 1-4.

             ICF, Inc.    1989. Developing Policies to Improve the Effectiveness of Coastal Flood Plain
             Management. Executive Summary to New England/New York Coastal Zone Task Force, Fairfax,
             VA, July.

             Johnston, J. 1984. Econometric Methods. McGraw-Hill: New York, NY.

             Judge, G.G., R.C. Hill, W.E. Griffiths, H. Lutkepohl and T.C. Lee. 1988. Introduction to The
             Theory and Practice of Econometrics. John Wiley & Sons: New York, NY.

             Koppel, R. 1994. Report on Five Studies: For the United States A= Coms of Engineers:
             Absecon Island and Seven Mile Island, New Jersey: Stone Harbor, Avalon. Atlantic City,
             Longl2ort. Margate, Ventnor: Surveys of Beach Users, Businesses, and Homeowners.           The
             Forum for Policy Research and Public Service,, Rutgers University, Camden, NJ.

             Kucharski, S. 1995. Beach Policy: New Jersey's Great Shore Debate. Unpublished M.S. thesis,
             Rutgers University, Camden NJ.

             Leontieff, W. 1966. Input-Output Economics. Oxford Univ. Press: New York, NY.

             Lindsay, B.E. and H.C. Tupper. 1989. "Demand for Beach Protection and Use in Maine and
             New Hampshire: A Contingent Valuation Approach." In Coastal Zone '89: 79-87.

             Longwoods, Int'l. 1992. The Economic Impact, Performance and Profile of the New Jersey
             Travel and Tourism Industry, 1990-91. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, May.

             Longwoods, Int'l. 1994a. The Economic Impact, Performance and Profile of the New Jeragy
             Travel and Tourism Industry, 1992-93. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, September.
                                                white paper - 73 -






                                                                                          DRRFT - July
                                                                                  coastal economics
              Longwoods, Int'l. 1994b. The New Jersey 1993 Travel Research Program. Final Report to NJ
              Division of Travel and Tourism, Trenton, NJ, September.

              Longwoods, Int'l. 1995. The Economic Impact, Performance and Profile of the New Jersey
              Travel and Tourism Industry, 1993-94. Prepared for NJ Division of Travel and Tourism,
              Trenton, NJ, June.

              Manheim, T. and T.J. Tyrrell. 1986a. Social and Economic I=acts from Tourism in Block
              Island, Rhode Island. RI Sea Grant Report. Narragansett, RL

              Manheim, T. and T.J. Tyrrell. 1986b. Social and Economic Impacts from Tourism in Newport.
              Rhode Island. RI Sea Grant Report. Narragansett, RL

              Mishan, E.J. 1976. Cost-Benefit Analysis. Praeger Publishers: New York, NY.

              Nat'l. Research Council. 1995. Beach Nourishment and Protection. National Academy Press:
              Washington, DC.

              NJDEP, DCR. 198 1. New Jersey Shore Protection Master Plan. Prepared by Dames and Moore.
              Prepared for Division of Coastal Resources, NJDEP, Trenton, NJ.

              Opinion Research Corporation. 1989. The Economic Impact of Visitors to the New Jersey Shore
              The Summer of 1989. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, October.

              Ostle, B. and R.W. Mensing. 1975. Statistics in Research. The Iowa State University Press:
              Ames, 10.

              R.L. Associates. 1987. Economic Impact of Tourism to the New Jersey Shore in 1987. Prepared
              for NJ Division of Travel and Tourism, Trenton, NJ, December.

              R.L. Associates. 1988.. The Economic Impact of Visitors to the New Jersey Shore, The Summer
              of 1988. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, November.

              Silberman, J. and M. Klock. 1988. "The Recreational Benefits of Beach Renourishment." Ocean
              & Shore Mana2ement 11: 73-90.

              Silberman, J., D.A. Gerlowski and N.A. Williams. 1992. "Estimating Existence Value for Users
              and Nonusers of New Jersey Beaches." Land Econon-dcs 68(2): 225-236.

              Stronge, W.B. 1994. "Beaches, Tourism and Economic Development." Shore and Beach 62(2),
              April:6-8.

              Stronge, W.B. 1995. "The Economics of Government Funding for Beach Nourishment Projects:
              The Florida Case." Shore and Beach:4-6.

              U.S. ACOE. 1989a. Atlantic Coast of New Jersey Sandy Hook to Barnegat Inlet Beach Erosion
              Control PLo
                        ,- ject Section I - Sea Bright to Ocean Township. New Jersey.     General Design
              Memorandum, Main Report with Environmental Impact Statement, Volume 1, New York District,
              NY, January.



              U.S. ACOE. 1989b. Atlantic Coast of New Jersey Sandy Hook to Bamegat Inlet Beach Erosion
              Control Project Section I - Sea Bright to Ocean Township. New Jersey.       General Design
              Memorandum, Technical Appendices, Volume II, New York District, NY, January.



                                                white paper - 74 -






                                                                                        ORHFT - July
                                                                                coastal economics
             U.S. ACOE. 1991a. Delaware Bay Coastline, New Jersey and Delaware. Reconnaissance
             Report, Philadelphia District, PA, August.

             U.S. ACOE. 1991b. Delaware Bgy Coastline, New Jersey and Delaware. Reconnaissance
             Report - Technical Appendices, Philadelphia District, PA, August.

             U.S. ACOE. 1992. New Jersey Shore Protection Study: Barriegat Inlet to Little Egg Inlet.
             Reconnaissance Report, Philadelphia District, PA, February.

             U.S. ACOE. 1993. Raritan Bay and Sandy Hook Bay, New Jersey Combined Flood Control and
             Shore Protection Rec43nnaissance StgAy. New York District, NY, March.

             U.S. ACOE. 1994a. Atlantic Coast of New Jersey Sandy Hook to Bamegat Inlet Beach Erosion
             Control Project Section 11 - Asbury Park to Manasquan, New Jersey.         General Design
             Memorandum, Main Report & Environmental Impact Statement, Volume 1. New York District,
             NY, April.

             U.S. ACOE. 1994b. Atlantic Coast of New Jersey Sandy Hook to Bamegat Inlet Beach Erosion
             Control Project Section 11 - Asbury Park to Manasquan, New JuLey.          General Design
             Memorandum, Technical Appendices, Volume II. New York District, NY, April.

             U.S. ACOE. 1994c. New Jersey Protection Study: Lower Cape May Meadows - Cape May
             Point. Reconnaissance Study, Philadelphia District, PA, August.

             U.S. ACOE. 1994d. Shoreline Protection and Beach Erosion Control Study : Phase 1: Cost
             Comparison of Shoreline Protection Projects of the U.S. Anny CoMs of Engineers. IWR Report
             94-PS- 1.  Water Resources Support Center, Institute of Water Resources, Alexandria, VA,
             January.

             U.S. ACOE. 1995. New Jersey Shore Protection Study: Barnegat Inlet to Little E22 Inle .
             Reconnaissance Study, Philadelphia District, PA, March.

             University of North Carolina. 199 1. Evaluation of the National Coastal Zone Management
             Program. The Center for Urban and Regional Studies, Chapel Hill, NC, February.






















                                               white paper - 75 -






         Table I Analyses of the Economic Value of Recreational Beach Use.

                                                  Sample        Economic
         Study:                      Year/Area:   Design:       Method:                                    Results:

         Curtis  & Shows (1982)      1981; FL     NA               Face-to-Face:                           Residents      Tourists
                                                                   CV-Open Ended                    WTP     1.88           2.15


         Curtis  & Shows (1984)      1983; FL     NA               Face-to-Face:                           Residents      Tourists
                                                                   CV-Open Ended                    WTP     4.44

         Bell &  Leeworthy (1986)    1984; FL     RS  of            Telephone:                             Residents:     Tourists;
                                                911 residents;         CV-Open Ended                WTP     1.31            1.45
                                                  4333 tourists                                            (3.23)          (2.57)
                                                  contacted, 826 Face-to-Face:                              n=804           n=968
                                                  surveyed             CV-Open Ended             %O-bids      29%            38%
                                                                                             TCM*:
                                                                                                    CS      10.23          29.32
                                                                                                    Cv      10.31          29.45
                                                                                                    EV      10.18          29.29
                                                                                                    No.       870           1051


                                                                                        Estimated from   the area under    an esti-
                                                                                     mated linear demand curve evaluated at
                                                                                     mean values of the independent variables.

         Lindsay & Tupper (1988) 1988;            RS of         CV-Open Ended,               Old        Pine       Ocean    Seabrook,
                                     NH & ME      1100 users Face-to-Face           All      orchard    Pt.        Park     NH
                                                                              CV   47.40     51.15      46.15      52.40     41.03
                                                                                   (53.00)   (49.13)    (52.88)    (60.34)  (52.35)
                                                                                   n=934     n=316      n=173      n=164     n=281
                                                                             CVEC* 30.80     20.08ab    27.37a     34.30a    40.45b
                                                                                   (68.80)   (29.72)    (39.69)    (54.28)  (83.76)
                                                                                   n=834     n=248      n=153      n=156     n=277
                                                                            CVLP* 26.40      26.31a     18.50a     20.16ab   34.47b
                                                                                   (65.30)   (70.55)    (29.82)    (31.69)  (85.13)
                                                                                   n=834     n=248      n=153      n=156     n=277


                                                                              *Differences   significant at    the .05 level.
                                                                              Numbers in parentheses are standard deviations.






         Table 1. Cont.

                                                     Sample         Economic
         Study:                       Year/Area: Design:            Method:                                      Results:

         Silberman                    1985;          Split RS       CV-Iterative-
          & Klock (1988)               No. NJ                         Bidding;            WTP w/o         WTP w        Existence
                                                                      Face-to-Face        Project         Project      Value
                                                                                  Mean     3.60           3.90           16.31
                                                                                    SD     (1.14)         (1.18)         (19.62)
                                                                                     N      462           445            822
                                                                                %0 bids     17%            -             13%
                                                                         % protest bids      -                           38.4%


         Silberman,                   1985           Split RS       Face-to-Face,
          Gerlowski,                   No. NJ                       CV-1terative-
          Williams (1992)                                            Bidding                           Existence               Existence
                                       Staten   Is. RS=500          Telephone,                            Value:                 Value:
                                                                    CV-Open Ended                         Total                 Nonzero
                                                                                                          Sample                Bidders
                                                                    Face-to-Face
                                                                    Will Use in Future Mean               15.21                 23.59
                                                                                            SD            (20.91)              (21.92)
                                                                                             N            1177
                                                                           %0 bids                        -35.5%
                                                                    Will Not Use            Mean           9.34                 21.02
                                                                                            SD            (16.04)              (18.28)
                                                                                             N             754
                                                                           %0 bids                        55.6%
                                                                    Telephone
                                                                    Will Use in Future Mean               19.65                 31.98
                                                                                            SD            (38.37)              (44.00)
                                                                                             N             83
                                                                           %0 bids                        38.6%
                                                                    Will Not Use            Mean           9.51                 23.87
                                                                                            SD            (17.49)              (20.67)
                                                                                             N             138
                                                                           %0 bids                        60.1%


                                                                    Tobit Model:
                                                                    will use in Future                    15.10
                                                                    Will Not Use                          9.26






        Table I Cont.


                                                Sample       Economic
        Study:                    Year/Area: Design:         Method:                                 Results:

        US ACOE (1986)            1985;        RS of         CV-Iterative Bidding;      WTP w/o Protection         3.67
                                   No. NJ        2917 users    Face-to-Face             WTP w 501berm              3.89
                                                                                        WTP w 1001 berm            3.93
                                                                                        Midpoint WTP w Prot.       3.91

        Koppel (1994)             1994;        RS of         Face-to-Face:                           w/o $0-bids w $0-bids
           Kucharski (1995)        So. NJ        1063 users    CV-Closed Ended WTP-Beach use             5.04         4.22
                                                               CV-Open Ended      WTP-Wider beach       5.41          4.59
                                                                                  Wider beach:
                                                                                    % WTP more       16%
                                                                                    % WTP less        3%
                                                                                    % WTP same       81%


        Summary:                  --------------------  Results  ---------------------------          -
              No. NJ              Use values:          1985$         1992$
        (Silberman &  Kloch 1988)WTP w Protection      3.90          5.08
        (Silberman et al. 1992) WTP w/o Prot.          3.60          4.69
                                  Net Value - Prot.    0.30          0.39


                                  Non-Use values:
                                  Existence value 9.26/92-days 12.07/92-days


                                  Sum Use & Non-use 0.4006           0.52


                                                                 1985$                         1992$
                                                      w/o $0-bids w $0-bids         w/o $0-bids w $0-bids
              So. NJ              WTP - Wider beach 5.41              4.59              5.12          4.35
          (Koppel 1994)           WTP - Beach use      5.04           4.22              4.77          4.00
                                  Net value - Prot.    0.37           0.37              0.35          0.35



                                                             1988$                      1992$
              NH-ME               WTP - Beach use            47.40                      56.21
        (Lindsay & Tupper 1988)   WTP - Protection           30.80/92-days=0.33         36.53/92-days=0.39







        Table I Cont.


                                               Sample        Economic
        Study:                    Year/Area: Design:         Method:                                 Results:



        Summary-Cont.:
                                                             1985$        1992$
              No. NJ              WTP-w/o Protection         3.67         4.78
           (US ACOE 1986)         WTP-w 501 berm             3.89         5.07
                                  WTP-w 1001 berm            3.93         5.12
                                  WTP w Protection           3.91         5.10
                                  Net value:
                                          w Protection       0.24         0.315
                                          w 501 berm         0.22         0.29
                                          w 1001 berm        0.26         0.34


        Note: All estimates of economic value are in terms of $/person per day, except for estimates of existence
        value which was converted to $/person/day on the basis of 92-day season. Because of such high economic
        value estimates associated with the NH-ME study, net value of beach protection was estimated from the bid
        value for erosion control divided by 92-day season.

        Symbols refer to the following: NA (Not Available), CV (Contingent Valuation), RS (Random Sample), WTP
        (Willingness-to-Pay), TCM (Travel Cost Model), CVEC (Contingent Valuation for Erosion Control), CVLP
        (Contingent Valuation for Litter Program), SD (standard Deviation), N (no. of observations)

        Sources: see References at end of Chapter 3.










        Table 2. Estimated Expenditures of Travel and Tourism in New Jersey, 1990-94.

           OBS   TYPE                                YR    CO           COST      COST92          NIND


            1   County  level                     1990    Atlantic    6220.26     6407.51          NA
            2   County  level                     1990    Cape May    1458.93     1502.85          NA
            3   County  level                     1990    Monmouth      758.56     781.39          NA
            4   County  level                     1990    Ocean         677.76     698.16          NA

            5   County  level                     1991    Atlantic    5910.94     6088.88       4115.3
            6   County  level                     1991    Cape May    1510.71     1556.19       2583.9
            7   County  level                     1991    Monmouth      753.56     776.24       1990.3
            8   County  level                     1991    Ocean         692.66     713.51       1990.3

            9   County  level                     1992    Atlan@Lic   6704.51     6509.64          NA
           10   County  level                     1992    Cape May    1094.00     1062.20          NA
           11   County  level                     1992    Monmouth    1262.67     1225.97          NA
           12   County  level                     1992    Ocean         892.53     866.59          NA

           13   County  level                     1993    Atlantic    6453.49     6265.91       4427.9
           14   County  level                     1993    Cape May    1390.23     1349.82       5348.9
           15   County  level                     1993    Monmouth    1055.93     [email protected]       2107.9
           16   County  level                     1993    Ocean         769.02     746.67       2107.9

           17   County  level                     1994    Atlantic    6865.98     6499.98       3767.4
           18   County  level                     1994    Cape May    2527.51     2392.78       5461.3
           19   County  level                     1994    Monmouth    1683.21     1593.48       2356.2
           20   County  level                     1994    Ocean       1484.84     1405.69       2356.2

           21   Barrier  Is.  - Jersey  Shore     1992    Atlantic       30.75      29.86       117.80
           22   Barrier  Is.  - Jersey  Shore     1992    Cape May      509.24     494.44       2488.70
           23   Barrier  Is.  - Jersey  Shore     1992    Monmouth       28.91      28.06         90.9
           24   Barrier  Is.  - Jersey  Shore     1992    Ocean         193.78     188.14       579.9

           25   Barrier  Is.  - Jersey  Shore     1993    Atlantic       32.62      31.67       110.7
           26   Barrier  Is.  - Jersey  Shore     1993    Cape May      605.01     587.42       2954.1
           27   Barrier  Is.  - Jersey  Shore     1993    Monmouth       29.86      29.00         94.0
           28   Barrier  Is.  -kJersey  Shore     1993    Ocean         207.43     201.40       621.4











        Table 2 Cont.


          OBS    TYPE                               YR   CO            COST       COST92      NIND

          29    Barrier Is. - Jersey Shore       1994   Atlantic        44.78       45.22     117.5
          30    Barrier  Is. - Jersey Shore      1994   Cape May       554.58      527.85     2881.0
          31    Barrier  Is. - Jersey Shore      1994   Monmouth        39.15       39.89     140.2
          32    Barrier  Is. - Jersey Shore      1994   Ocean          178.78      172.09     781.7

         Note:  COST is  in millions of current dollars associated with       the year of the study and
         refers to the   projected expenditures on travel and tourism, COST92 is in millions of
         1992 dollars adjusted by the relevent CPI index, NIND refers to the estimated number of
         visitors in thousands. NA refers to not available. Concerning NIND, estimates were not
         available on a county basis, o    *nly on a region basis, hence Ocean and Monmouth counties are
         considered as the Shore region (see Longwoods studies for details).


         Source: 19 90- 9 1; Longwoods, Int'l. 1992. The Economic Impact. Performance and Profile of the New Jersey Travel and
                              TourisW IndustEy. 1990-91. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, May.

                  1992-93; Longwoods, Int'l. 1994. The Economic Impact, Performance and Profile of the New Jersey Travel and
                              Tourism IndustU. 1992-93. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, September.

                  19 9 4 Longwoods, Int'l. 1995. The Economic Impact, Perfon-nance and Profile of the New Jersey Travel and
                              Tourism IndustLy. 1993-94. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, June.











        Table 2 Cont.

          OBS    TYPE                              YR           COST         COST92          NIND
            1     County level                      1990      9115.51       9389.91          NA
            2     County level                      1991      8867.87       9134.82       8689.5
            3     County level                      1992      9953.71       9664.40          NA
            4     County level                      1993      9668.67       9387.64       11884.7
            5     County level                      1994      12561.54     11891.93       11584.9


            6     Barrier Is. - Jersey Shore        1992        762.67       740.50       3277.3
            7     Barrier Is. - Jersey Shore        1993        874.93       849.49       3780.2
            8     Barrier Is. - Jersey Shore        1994        817.29       773.71       3920.4
         Note: COST is in millions of current dollars associated with the year of the study and
         refers to the projected expenditures on travel and tourism, COST92 is in millions of
         1992 dollars adjusted by the relevent CPI index, NIND refers to the estimated number of
         visitors in thousands. NA refers to not available. Concerning NIND, estimates were not
         available on a county basis, only on a region basis, hence Ocean and Monmouth counties are
         considered as the Shore region (see Longwoods studies for details).



         Source: 1990-91; Longwoods, Int'l. 1992. The Econornic Impact, Pelformance and Profile of the New Jer ev Travel and
                             Tourism IndiMtry. 1990-91. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, May.
                  1992-93; Longwoods, Int'l. 1994. The Economic linDact- Performance and Profile of the New Jersev Travel and
                             Tourism Industry. 1992-93. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, September.
                  1994; Longwoods, Int'l. 1995. The Economic Impact, Performance and Profile of the New Jersey Travel and
                             Tourism Industry. 1993-94. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, June.








            Table 3. Estimated Expenditures     of Travel and Tourism in New Jersey without Gambling
              Expenditures, 19"90-94.

                OBS    TYPE                             YR    Co          COST      COST92         NIND

                1   County  level                    1990   Atlantic    3622.23     3731.27        NA
                2   County  level                    1990   Cape May    1458.93     1502.85        NA
                3   County  level                    1990   Monmouth      758.56     781.39        NA
                4   County  level                    1990   Ocean         677.76     698.16        NA

                5   County  level                    1991   Atlantic    3421.15     3524.14      4115.3
                6   County  level                    1991   Cape May    1510.71     1556.19      2583.9
                7   County  level                    1991   Monmouth      753.56     776.24      1990.3
                8   County  level                    1991   Ocean         692.66     713.51      1990.3

                9   County  level                    1992   Atlantic    3574.75     3470.85        NA
               10   County  level                    1992   Cape May    1094.00     1062.20        NA
               11   County  level                    1992   Monmouth    1262.67     1225.97        NA
               12   County  level                    1992   Ocean         892.53     866.59        NA

               13   County  level                    1993   Atlantic    3285.75     3190.25      4427.9
               14   County  level                    1993   Cape May    1390.23     1349.82      5348.9
               15   County  level                    1993   Monmouth    1055.93     1025.24      2107.9
               16   County  level                    1993   Ocean         769.02     746.67      2107.9

               17   County  level                    1994   Atlantic    '3663 . 14  3467.87      3767.4
               18   County  level                    1994   Cape May    2527.51     2392.78      5461.3
               19   County  level                    1994   Monmouth    1683.21     1593.48      2356.2
               20   County  level                    1994   Ocean       1484.84     1405.69      2356.2

               21   Barrier  Is. -  Jersey  Shore    1992   Atlantic       29.80      28.93      117.8
               22   Barrier  Is. -  Jersey  Shore    1992   Cape May      509.24     494.44      2488.7
               23   Barrier  Is. -  Jersey  Shore    1992   Monmouth       28.91      28.06        90.9
               24   Barrier  Is. -  Jersey  Shore    1992   Ocean         193.78     188.14      579.9

               25   Barrier  Is. -  Jersey  Shore    1993   Atlantic       31.62      30.70      110.7
               26   Barrier  Is. -  Jersey  Shore    1993   Cape May      605.01     587.42      2954.1
               27   Barrier  Is. -  Jersey  Shore    1993   Monmouth       29.86      29.00        94.0
               28   Barrier  Vs. -  Jersey  Shore    1993   Ocean         207.43     201.40      621.4











             Table 3 Cont.


               OBS     TYPE                              YR   CO              COST     COST92     NIND


               29    Barrier Is. - Jersey Shore       1994   Atlantic        34.56       32.72      117.5
               30    Barrier  Is. - Jersey Shore      1994   Cape May       554.58     527.85      2881.0
               31    Barrier  Is. - Jersey Shore      1994   Monmouth        39.15       39.89      140.2
               32    Barrier  Is. - Jersey Shore      1994   Ocean          178.78     172.09       781.2


              Note:  COST is  in millions of current dollars associated with       the year of the study and
              refers to the   projected expenditures on travel and tourism, COST92 is in millions of
              1992 dollars adjusted by the relevent CPI index, NIND refers to the estimated number of
              visitors in thousands. NA refers to not available. Concerning NIND, estimates were not
              available on a county basis, only on a region basis, hence Ocean and Monmouth counties are
              considered as the Shore region (see Longwoods studies for details).




              Source: 1990-91; Longwoods, Int'l. 1992. The Economic Impact, Performance and Profile of the New Jersey Travel and
                                  Tourism Indusay. 1990-91. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, May.

                       1992-93; Longwoods, Int'l. 1994. The Economic Impact, Performance and Profile of the New Jersey Travel and
                                  Tourism Indusqy, 1992-93. Prepared for NJ Division of Travel and Tour-ism, Trenton, NJ, September.

                       19 94; Longwoods, Int'l. 1995. The Economic Impact. Performance and Profile of the New Jersey Travel and
                                  Tourism Indusqy, 1993-94. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, June.











             Table 3 Cont.


               OBS    TYPE                               YR        COST      COST92          NIND


                 1     County  level                     1990     6517.48     6713.67          NA
                 2     County  level                     1991     6378.08     6570.08        8689.5
                 3     County  level                     1992     6823.95     6625.61          NA
                 4     County  level                     1993     6500.93     6311.98        11884.7
                 5     County  level                     1994     9358.70     8859.82        11584.9

                 6     Barrier Is. - Jersey Shore        1992      761.72        739.58      3277.3
                 7     Barrier Is. - Jersey Shore        1993      873.92        848.51      3780.2
                 8     Barrier Is.   - Jersey Shore      1994      807.07        764.04      3920.4

             Note: COST is in millions of current dollars associated with the         year of the study and
             refers to the projected expenditures on travel and tourism, COST92 is in millions of
             1992 dollars adjusted by the relevent CPI index, NIND refers to the estimated number of
             visitors in thousands. NA refers to not available. Concerning NIND, estimates were not
             available on a county basis, only on a region basis, hence Ocean and Monmouth counties are
             considered as the Shore region (see Longwoods studies for details).




             Source: 1990-91; Longwoods,lnt'l. 1992. The Economic Impact. Performance and Profile of the New Jersey Travel and
                                  Tourism lndusU@!. 1990-91. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, May.

                      1992-93; Longwoods, Int'l. 1994. The Economic Impact- Performance and Profile of the New Jersey Travel and
                                  Tourism lndusu@!. 1992-93. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, September.

                      19 9 4 ; Longwoods, Int'l. 1995. The Economic Impact, Performance and Profile of the New Jersey Travel and
                                  Tourism Indusqy. 1993-94. Prepared for NJ Division of Travel and Tourism, Trenton, NJ, June.








         Table 4. Derivation of Estimated Expenditures of Beach Trips in
         New Jersey in 1993.


                1) Step 1:             Trip type    No.       %
                                       Overnight 20.OM        13%
                                       Day         130.5M     87%
                                       Total       150.5M      100%


                2) Step 2:       Trio nurr)ose       No.*       %
                                 Beach-Overnight 2AM            12%
                                 Beach-Day          5.22M        4%
                                 Total-Beach        7.62M


                                    Estimated based  on %  of (2) and from (1).

                3) Step 3: Derivation of Average     Expense (1993$):

                     Cateaory:         OverniZht       Day-       Barrier Is.
                     Total expense     $10,924.8M $6,461.91M         $874.92 M
                     Total trips            20.OM      130
                                                          .5M   L637,991.561
                     Avg. Exp.
                        ($/trip)       $546.241     $49.517        $1371.368,
                     -------------------     w/o Gambling  ------------------
                     Total expense     $9,862.5M   $4,377.75M      $873.915M
                     Avg. Exp.                                                           t--Y) An le T
                        Wtrip)         $493.123     $33.546        $1369.792          >UWVtj

                                       *3,780,100 persons/5.925 persons/trip
                                          637,991.56 trips.
                                                      0,4"u,
                4) Step 4: Derivation of Number of Trips:
                                           ,@, oo             0    W,
                                 Trip Y_Q@           @<'N'o , -
                                 Total vernight        2.4M
                                 less Barrier Is.     -.638M
                                 Other Overnight*     1.762M

                                 *Overnight trips   other than Barrier Is.

                5) Step 5: Estimated Tourist Beach Expenses (1993$):
                           Category                                                  01 G-
                           Barrier Is. trips: .638M @ $1371.368         $874.922M
                           Other Overnight:      1.762M @ $546.241      $962.476M
                           Day trips:            5.22M @ $49.517       $258.479M

                           Estimated 1993 Beach-Related Expenses        $2,095.87.7m

                           ------------------    w/o Gambling  -------------------
                           Barrier Is. trips: .638M @ $1369.792         $873.915M
                           Other Overnight:      1.762M @ $493.123      $868.883M
                           Day trips:            5.22M @ $33.546       $175.11M
                                                                            8
                                                                             M







                                                                            M




                                                                             rip


























                           Estimated 1993 Beach-Related Expenses        $1,917.91M










        Table 4 Cont.


        Note: M refers to millions.



        Source:
             Expenses and Barrier Is. from:
             Longwoods, Int'l. 1994a. The Economic Imj2act. Performance
             and Prnfile of thp New Jersey Travel and Tourism I-ndustry,
             1992-93. Prepared for NJ Division of Travel and Tourism,
             Trenton, NJ, September.

             Trip No. from:
             Longwoods, Int'l. 1994b. The New Jersey 1993 Travel_
             Research Proaram. Final Report to NJ Division of Travel and
             Tourism, Trenton, NJ, September.











               Table 5.          COMBINED REVENUE LOSS AND INCREASED COSTS RELATIVE TO 1987 FOR OCEAN CITY, NJ
                                                                       (do( I ars)




      Year/                    No Response                Beach Nourishment  - (a)              Dike          (b)  Property Accuisition(c)
      Sea Level Rise       Non-Storm      Storm          Non-Storm      Storm           Non-Storm      Storm        Non-Storm      Storm




      2025:

      Linear             18,498,578      87,841,610      1,108,412     88,286,990     41,2B4,079       299,01     18,498,578     667,338,706
      Mid-Low            23,045,581     93,358,730       2,463,138     97,053,793     42,062,207       299,051    23,045,581     772,692,035
      Mid-High           26,060,507     111,688,471      3,263,657   122,239,897      45,077,133       299M1      26,060,507     838,690,128


      2050:

      Linear             22,094,151     99,328,566       1,108,412   101,344,744      22,094,187     99,328,566   25,947,729      44,340,276
      Mid-Low            28,547,967    115,419,7a3       2,929,374   128,788,189      28,547,967    115,419,783   31,217,619      53,7758,775
      Mid-High           31,746,387     155,047,215      3,958,614   181,381,048      31,746,387. 155,746,215     33,679,370      63,526,340


      (a)      Beach nourishment is undertaken     once  every five  years. Hence,    to make the non-storm beach nourishment scenario's
               costs comparable to other yearly costs or revenues, the non-storm costs for this scenario should be divided by 5.

      (b)      Dike costs are listed in the non-storm column.        These are one-time costs, so they should be compared with other one-
               time costs or annualized before comparing with ongoing yearly costs or revenues.

      (c)      Property acquisition costs are Listed in the storm-reLated column. These are one-time costs, so they should be
               compared with other one-time costs or annualized before comparing with ongoing yearly costs or revenues.


               Source: ICF, In'l. (1989).













               Table 6          COMBINED REVENUES LOSS AND INCREASED COSTS RELATIVE TO 1987 FOR STRATHMERE, NJ
                                                                        (dot Lars)





     Year/                    No Response                 Beach Nourishment (a)                   Dike _(b)          Property Acquisition(c)
     Sea Level Rise       Non-Storm       Storm          Non-Storm       Storm          Non-Storm        Storm       Non-Storm       Storm




     2025:

     Linear               7,180,158      3,398,056       1,243,079      3,467,30        26,196,70        166,100    7,180,158       15,880,655
     Mid-Low              7,244,709      3,051,422       2,762,397      3,467,383       26,261,334       166,100    7,244,709       14,382,069
     Mid-High-            7,379,172      2,435,740       3,660,176      3,674,045       26,395,798       166,100    7,379,172       10,741,090



     2050:


     Linear               7,229,703      3,209,883       1,243,079      3,467,383       7,229,703      3,209,883    7,250,019         251,039
     Mid-Low              7,547,735      2,077,930       2,762,397      3,674,045       7,547,735      2,077,930    7,559,744         222,899
     Mid-High             7,735,464      1,389,266       3,660,176      4,061,535       7,735,464      1,389,266    7,742,383         210,577



     (a)       Beach nourishment is undertaken     once every five years. Hence, to make the          non-storm beach nourishment scenario's
               costs comparable to other yearly costs or revenues, the non-storm costs for this scenario should be divided by 5.

     (b)       Dike costs are Listed in the non-storm column. These are one-time costs, so they should be compared with other one-
               time costs or annualized before comparing with ongoing yearly costs or revenues.

     W         Property acquisition costs are Listed in the storm-re(ated column. These are one-time costs, so they should be
               compared with other one-time costs or annualized before comparing with ongoing yearly costs or revenues.


        Source: ICF Int'l. (1989).









                   Table 7. Average Characteristics of Typical Beach Fill Projects by Reach.

                    OBS    REACH        AQUAN          ACOST           ACOST92       AEXP       AACT
                     1         2     556352.56      1966168.98      2913342.35         5       4.4444
                     2         3      72500.00         57271.84      197044.57         5       6.0000
                     3         4      56598.92          68578.59     211607.15         5      10.5385
                     4         6      60660.00         50204.75      189570.92         5       2.3333
                     5         7     239043.72       256612.59       650296.03         5      12.5455
                     6         8     392500.00       503700.00      1937180.66         5       1.0000
                     7         9     279408.67       294302.82       793608.98         5      13.0000
                     8       10      581688.79      2261670.03      [email protected]         5      19.0000
                     9       11      333218.85      1435325.31      1776595.16         5       8.9000
                    10       12      239004.77       832364.34       915223.62         5      15.0000
                    11       14      200425.31       769394.43      1050722.92         5      10.2353

                    OBS    REACH      TAGS1        TSALES1        MTAGS1           HIGH          LOW
                     1         2         26553      108794       13276.50         5177.84      4646.78
                     2         3      722730       10240316      36136.50       14093.24      12647.78
                     3         4     6336820       31198170     162482.56       63366.20      56868.90
                     4         6     1484461       5826871      123705.08       48244.98      43296.78
                     5         7      671650       3652115       47975.00       18710.25      16791.25
                     6         8      256176       1940721       36596.57       14272.66      12808.80
                     7         9      166259        916620       33251.80       12968.20      11638.13
                     8       10      3136748       15905793     285158.91       1112*11.97    [email protected]
                     9       11       279667       1780092       69916.75       27267.53      24470.86
                    10       12       113156        564571       56578.00       22065.42      19802.30
                    11       14       210971       1162257       21097.10         8227.87      7383.99

                    Note: AQUAN refers to the quantity      of  fill averaged   over all  projects completed
                    within each reach, ACOST refers to      the average cost    of a project within each reach,
                    ACOST92 refers to the average cost      in 1992 dollars,    AEXP refers to the average life
                    of a project within each reach, AACT refers to the estimated average effective life
                    of a project within each reach, TAGSI refers to the total beach tags sold within each
                    reach (for which data were present), TSALES1 refers         to the total sales of beach tags
                    sold within each reach, MTAGS1 refers to the average number of beach tags sold within
                    each reach, HIGH refers to the high average estimated annual recreational benefits
                    from beach protection (MTAGS1*$.39/person per day), LOW refers to the low average
                    estimated annual recreational benefits' from beach protection (MTAGS1*$.35/person per
                    day).









         Table 8. Examination of Presence of Hard Protection Structures Coupled with Typical Beach
         Fill Projects in New Jersey over 1960-94.

           ----------------------------------   DHARD=O -------------------------------------
          Variable      N            Sum           Mean      Variance        Std Dev              CV
          DQUAN       24     6953421.00     289725.88   261893579452       511755.39    176.6343411
          COST        24   20007633.20      833651.38    4.670894E12     2161225.12     259.2480693
          COST92      24   31887138.78     1328630.78    6.600472E12     2569138.38     193.3673683
          EXP         24   120.0000000      5.0000000                0              0              0
          ACT         23   187.0000000      8.1304348      28.7549407      5.3623634      65.9542016



          ---------------------------------  7-DHARD=1  -------------------------------------
          Variable      N            Sum           Mean      Variance        Std Dev              CV
          DQUAN      119   37883513.58      318348.85   225637978496       475013.66    149.2116764
          COST       119      123069120    1034194.29   4.7898335E12     2188568.83     211.6206651
          COST92     119      166533985    1399445.25   5.5293462E12     2351456.19     168.0277377
          UP         119   595.0000000      5.0000000                0              0              0
          ACT        119        1536.00    12.9075630      87.3049423      9.3437114      72.3894306




               OBS     DHARD       AQUAN          ACOST         ACOST92      AEXP       AACT
                 1       0       289725.88       833651.38    1328630.78       5       8.1304
                2        1       318348.85      1034194.29    1399445.25       5      12.9076



               Note: DHARD=O refers to no presence of hard protection structures, DHARD=l refers to
               the presence of hard protection structures. AQUAN refers to the quantity of fill
               averaged over all projects completed within each reach, ACOST refers to the average
               cost of a project within each reach, ACOST92 refers to the average cost in 1992
               dollars, AEXP refers to the average expected life of a project within each reach, AACT
               refers to the estimated average effective life of a project within each reach.

               Source: Appendix Table 3.








                  Appendix Table    1. Estimated Expenditures of Travel and Tourism in New Jersey, 1987-94.

                   OBS     YR       CCODE                               COST           COST92       NIND
                   12     1987*     Seasonal rent                        1.7              2.10      6.0
                   13     1987      Daily rent                           1.8              2.22      6.0
                   14     1987      Beach tag fees                      58.0             71.63      6.0
                   15     1987      Parking fees                        52.0             64.22      6.0
                   16     1987      Daytime entertainment              482.0           595.29       6.0
                   17     1987      Groceries                          625.0           771.90       6.0
                   18     1987      Food & restaurant                  612.0           755.84       6.0
                   19     1987      Nighttime entertainment            653.0           806.48       6.0
                   20     1987      Entertainment                      1135.0          1401.76      6.0
                   21     1987      Gifts                              224.0           276.65       6.0
                   22     1987      Total                                6.2              7.66      6.0


                   23     1988*     Seasonal rent                        1.2              1.42      4.8
                   24     1988      Daily rent                           1.7              2.02      4.8
                   25     1988      Beach tag fees                      43.0             51.00      4.8
                   26     1988      Parking fees                        56.0             66.41      4.8
                   27     1988      Daytime entertainment              453.0           537.24       4.8
                   28     1988      Groceries                          657.0           779.18       4.8
                   29     1988      Food & restaurant                  466.0           552.66       4.8
                   30     1988      Nighttime entertainment            666.0           789.85       4.8
                   31     1988      Entertainment                      1119.0          1327.10      4.8
                   32     1988      Gifts                              191.  0         226.52       4.8
                   33     1988      Total                                5.4              6.40      4.8


                   34     1989*     Seasonal rent                        2.0              2.26      5.7
                   35     1989      Daily rent                           2.7              3.05      5.7
                   36     1989      Beach tag fees                      33.0             37.34      5.7
                   37     1989      Parking fees                        57.0             64.49      5.7
                   38     1989      Daytime entertainment              658.0           744.50       5.7
                   39     1989      Groceries                          495.0           560.07       5.7
                   40     1989      Food & restaurant                  477.0           539.70       5.7
                   41     1989      Nighttime entertainment            643.0           727.52       5.7
                   42.    1989      Entertainment                      1301.0          1472.02      5.7
                   43     1989      Gifts                              279.0           315.68       5.7
                   44     1989      Total                                7.4              8.37      5.7









               Appendix Table I Cont.

                OBS     YR      CO           CCODE                          COST      COST92      NIND
                  ------------------------------   TYPE=County level   ---------------------------------
                  1    1990a    Atlantic     Lodging                      502.23      517.35     4115.3
                  2    1990     Atlantic     Food & restaurant          1186.94      1222.67     4115.3
                  3    1990     Atlantic     Entertainment                286.70      295.33     4115.3
                  4    1990     Atlantic     Automobile                   584.83      602.44     4115.3
                  5    1990     Atlantic     Local transportation          36.19       37.28     4115.3
                  6    1990     Atlantic     Retail                     1025.34      1056.21     4115.3
                  7    1990     Atlantic     Gambling                   2598.03      2676.24     4115.3
                  8    1990     Cape  May    Lodging                      228.14      235.01     2583.9
                  9    1990     Cape  May    Food & restaurant            502.51      517.64     2583.9
                 10    1990     Cape  May    Entertainment                116.61      120.12     2583.9
                 11    1990     Cape  May    Automobile                   232.99      240.00     2583.9
                 12    1990     Cape  May    Local transportation          14.48       14.92     2583.9
                 13    1990     Cape  May    Retail                       364.20      375.16     2583.9
                 14    1990     Cape  May    Gambling                       0.00        0.00     2583.9
                 15    1990     Monmouth     Lodging                       -78. 66     81.03     1990.3
                 16    1990     Monmouth     Food & restaurant            277.74      286.10     1990.3
                 17    1990     Monmouth     Entertainment                 54.93       56.58     1990.3
                 18    1990     Monmouth     Automobile                   117.53      121.07     1990.3
                 19    1990     Monmouth     Local transportation           7.81        8.05     1990.3
                 20    1990     Monmouth     Retail                       221.89      228.57     1990.3
                 21    1990     Monmouth     Gambling                       0.00        0.00     1990.3
                 22    1990     Ocean        Lodging                       69.83       71.93     1990.3
                 23    1990     Ocean        Food & restaurant            251.99      259.58     1990.3
                 24    1990     Ocean        Entertainment                 51.60       53.15     1990.3.
                 25    1990     Ocean        Automobile                   105.09      108.25     1990.3
                 26    1990     Ocean        Local transportation           6.56        6.76     1990.3
                 27    1990     Ocean        Retail                       192.69      198.49     1990.3
                 28    1990     Ocean        Gambling                       0.00        0.00     1990.3

                 29    1991a    Atlantic     Lodging                      473.82      488.08     4115.3
                 30    1991     Atlantic     Food & restaurant          1121.24      1154.99     4115.3
                 31    1991     Atlantic     Entertainment                270.65      278.80     4115.3
                 32    1991     Atlantic     Automobile                   552.30      568.93     4115.3
                 33    1991     Atlantic     Local transportation          34.19       35.22     4115.3









                  Appendix Table 1 Cont.

                 OBS      YR       CO            CCODE                            COST        COST92       NIND
                  34     1991      Atlantic      Retail                         968.95        998.12      4115.3
                  35     1991      Atlantic      Gambling                       2489.79      2564.74      4115.3
                  36     1991      Cape  May     Lodging                        236.84        243.97      2583.9
                  37     1991      Cape  May     Food & restaurant              518.82        534.44      2583.9
                  38     1991      Cape  May     Entertainment                  120.32        123.94      2583.9
                  39     1991      Cape  May     Automobile                     241.36        248.63      2583.9
                  40     1991      Cape  May     Local transportation            15.08         15.53      2583.9
                  41     1991      Cape  May     Retail                         378.29        389.68      2583.9
                  42     1991      Cape  May     Gambling                         0.00          0.00      2583.9
                  43     1991      Monmouth      Lodging                         78.74         81.11      1990.3
                  44     1991      Monmouth      Food & restaurant              275.43        283.72      1990.3
                  45     1991      Monmouth      Entertainment                   54.63         56.27      1990.3
                  46     1991      Monmouth      Automobile                     116.83        120.35      1990.3
                  47     1991      Monmouth      Local transportation             7a.76         7.99      1990.3
                  48     1991      Monmouth      Retail                         220.17        226.80      1990.3
                  49     1991      Monmouth      Gambling                         0.00          0.00      1990.3
                  50     1991      Ocean         Lodging                         72.99         75.19
                  51     1991      Ocean         Food & restaurant              256.58        264.30
                  52     1991      Ocean         Entertainment                   52.90         54.49
                  53     1991      Ocean         Automobile                     107.57        110.81
                  54     1991      Ocean         Local transportation             6.71          6.91
                  55     1991      Ocean         Retail                         195.91        201.81
                  56     1991      Ocean         Gambling                         0.00          0.00

                  57     1992b     Atlantic      Lodging                        657.72        638.60
                  58     1992      Atlantic      Food & restaurant              1198.31      1163.48
                  59     1992      Atlantic      Entertainment                  247.67        240.47
                  60     1992      Atlantic      Automobile                     5667.37       550.88
                  61     1992      Atlantic      Local transportation            42.56         41.32
                  62     1992      Atlantic      Retail                         861.12        836.09
                  63     1992      Atlantic      Gambling                       3129.76      3038.79
                  64     1992      Cape May      Lodging                        237.20        230.31
                  65     1992      Cape May      Food & restaurant              385.26        374.06
                  66     1992      Cape May      Entertainment                   71.07         69.00
                  67     1992      Cape May      Automobile                     170.57        165.61








                Appendix Table 1 Cont.

               OBS       YR    CO            CCODE                         COST      COST92      NIND
               68     1992    Cape May      Local transportation         13.98       13.57
               69     1992    Cape May      Retail                     215.92       209.64
               70     1992    Cape May      Gambling                      0.00        0.00
               71     1992    Monmouth      Lodging                      87.42       84.88
               72     1992    Monmouth      Food & restaurant          432.78       420.20
               73     1992    Monmouth      Entertainment              107.97       104.83
               74     1992    Monmouth      Automobile                 202.58       196.69
               75     1992    Monmouth      Local transportation         10.29        9.99
               76     1992    Monmouth      Retail                     421.63       409.38
               77     1992    Monmouth      Gambling                      0.00        0.00
               78     1992    Ocean         Lodging                      58.30       56.61
               79     1992    Ocean         Food & restaurant          317.35       308.13
               80     1992    Ocean         Entertainment                77.51       75.26
               81     1992    Ocean         Automobile                 142.02       137.89
               82     1992    Ocean         Local transportation          6.96        6.76
               83     1992    Ocean         Retail                     290.39       281.95
               84     1992    Ocean         Gambling                      0.00        0.00

               @5     1993b   Atlantic      Lodging                    662.23       642.98     4317.20
               86     1993    Atlantic      Food & restaurant          1112.83      1080.48    4317.20
               87     1993    Atlantic      Entertainment              214.59       208.35     4317.20
               88     1993    Atlantic      Automobile                 517.68       502.63     4317.20
               89     1993    Atlantic      Local transportation         '41.62      40.41     4317.20
               90     1993    Atlantic      Retail                     736.80       715.38     4317.20
               91     1993    Atlantic      Gambling                   3167.74      3075.67    4317.20
               92     1993    Cape  May     Lodging                    243.79       236.70     2394.80
               93     1993    Cape  May     Food & restaurant          476.75       462.89     2394.80
               94     1993    Cape  May     Entertainment              102.50        99.52     2394.80
               95     1993    Cape  May     Automobile                 220.59       214.18     2394.80
               96     1993    Cape  May     Local transportation         15.40       14.95     2394.80
               97     1993    Cape  May     Retail                     331.20       321.57     2394.80
               98     1993    Cape  May     Gambling                      0.00        0.00     2394.80
               99     1993    Monmouth      Lodging                      90.18       87.56     1392.50
               100    1993    Monmouth      Food &.restaurant          372.69       361.86     1392.50
               101    1993    Monmouth      Entertainment                84.00       81.56     1392.50









               Appendix Table   1 Cont.
               OBS      YR      CO             CCODE                           COST       COST92       NIND
               102     1993     Monmouth       Automobile                    166.83       161.98      1392.50
               103     1993     Monmouth       Local transportation            9.65         9.37      1392.50
               104     1993     Monmouth       Retail                        332.58       322.91      1392.50
               105     1993     Monmouth       Gambling                        0.00         0.00      1392.50
               106     1993     Ocean          Lodging                        59.94        58.20      1392.50
               107     1993     Ocean          Food & restaurant             281.80       273.61      1392.50
               108     1993     Ocean          Entertainment                  63.02        61.19      1392.50
               109     1993     Ocean          Automobile                    120.58       117.08      1392.50
               110     1993     Ocean          Local transportation            6.60         6.41      1392.50
               ill     1993     Ocean          Retail                        237.08       230.19      1392.50
               112     1993     Ocean          Gambling                        0.00         0.00      1392.50

               113     1994d    Atlantic       Lodging                       645.75       611.33      6365.90
               114     1994     Atlantic       Food & restaurant            1216.34      1151.50      6365.90
               115     1994     Atlantic       Entertainment                 263.74       249.68      6365.90
               116     1994     Atlantic       Automobile                    578.98       548.12      6365.90
               11-7    1994     Atlantic       Local transportation           41.38        39.17      6365.90
               118     1994     Atlantic       Retail                        916.95       868.07      6365.90
               119     1994     Atlantic       Gambling                     3202.84      3032.11      6365.90
               120     1994     Cape  May      Lodging                       649.49      .614.87      8984.10
               121     1994     Cape  May      Food & restaurant             722.93       684.39      8984.10
               122     1994     Cape  May      Entertainment                 179.68       170.10      8984.10
               123     1994     Cape  May      Automobile                    331.99       314.29      8984.10
               124     1994     Cape  May      Local transportation           18.14        17.17      8984.10
               125     1994     Cape  May      Retail                        625.28       591.95      8984.10
               126     1994     Cape  May      Gambling                        0.00         0.00      8984.10
               127     1994     Monmouth       Lodging                       451.39       427.33      1344.26
               128     1994     Monmouth       Food & restaurant             451.39       427.33      1344.26
               129     1994     Monmouth       Entertainment                 113.77       107.71      1344.26
               130     1994     Monmouth       Automobile                    210.15       198.95      1344.26
               131     1994     Monmouth       Local transportation           10.33         9.78      1344.26
               132     1994     Monmouth       Retail                        446.18       422.40      1344.26
               133     1994     Monmouth       Gambling                        0.00         0.00      1344.26
               134     .1994    Ocean          Lodging                       404.50       382.94      1279.52
               135     1994     Ocean          Food & restaurant             404.50       382.94      1279.52
               136     1994     Ocean          Entertainment                 101.57        96.16      1279.52









              Appendix Table   1 Cont.

              OBS      YR      CO           CCODE                         COST       COST92      NIND
              137     1994     Ocean        Automobile                  180.26        170.65    1279.52
              138     1994     Ocean        Local transportation          8.42         7.97     1279.52
              139     1994     Ocean        Retail                      385.59       365.04     1279.52
              140     1994     Ocean        Gambling                      0.00         0.00     1279.52


               -------------------------   TYPE=Barrier Is. - Jersey    Shore  --------------------------
              141     1992b    Atlantic     Lodging                      18.310        17.778      117.8
              142     1992     Atlantic     Food & restaurant             4.756         4.618      117.8
              143     1992     Atlantic     Entertainment                 2.648         2.571      117.8
              144     1992     Atlantic     Automobile                    0.603         0.586      117.8
              145     1992     Atlantic     Local transportation                                117.8
              146     1992     Atlantic     Retail                        3.481         3.380      117.8
              147     1992     Atlantic     Gambling                      0.951         0.923      117.8
              148     1992     Cape May     Lodging                     363.275        352.716    2488.7
              149     1992     Cape May     Food & restaurant            62.265        60.456     2488.7
              150     1992     Cape May     Entertainment                13.732        13.333     2488.7
              151     1992     Cape May     Automobile                   11.734        11.393     2488.7
              152     1992     Cape May     Local transportation                                  2488.7
              153     1992     Cape May     Retail                       58.233        56.540     2488.7
              154     1992     Cape May     Gambling                      0.000         0.000     2488.7
              155     1992     Monmouth     Lodging                      20.619        20.020       90.9
              156     1992     Monmouth     Food & restaurant             3.534         3.431       90.9
              157     1992     Monmouth     Entertainment                 0.779         0.757       90.9
              158     1992     Monmouth     Automobile                    0.666         0.647       90.9
              159     1992     Monmouth     Local transportation                                    90.9
              160     1992     Monmouth     Retail                        3.305         3.209       90.9
              161     1992     Monmouth     Gambling                      0.000         0.000       90.9
              162     1992     Ocean        Lodging                     138.233        134.215     579.9
              163     1992     Ocean        Food & restaurant            23.693        23.004      579.9
              164     1992     Ocean        Entertainment                 5.225         5.073      579.9
              165     1992     Ocean        Automobile                    4.465         4.335      579.9
              166     1992     Ocean        Local transportation                                   579.9
              167     1992     Ocean        Retail                       22.159        21.515      579.9
              168     1992       cean       Gambling                      0.000         0.000      579.9









             Appendix Table   1 Cont.
             OBS      YR      CO           CCODE                         COST      COST92      N;ND
             169     1993b    Atlantic     Lodging                      19.460       18.894      110.7
             170     1993     Atlantic     Food & restaurant             5.032        4.886      110.7
             171     1993     Atlantic     Entertainment                 2.802        2.721      110.7
             172     1993     Atlantic     Automobile                    0.638        0.620      110.7
             173     1993     Atlantic     Local transportation                                  110.7
             174     1993     Atlantic     Retail                        3.684        3.577      110.7
             175     1993     Atlantic     Gambling                      1.006        0.977      110.7
             176     1993     Cape May     Lodging                     431.595       419.050    2954.1
             177     1993     Cape May     Food & restaurant            73.975       71.825     2954.1
             178     1993     Cape May     Entertainment                16.314       15.840     2954.1
             179     1993     Cape May     Automobile                   13.941       13.535     2954.1
             180     1993     Cape May     Local transportation                                 2954.1
             181     1993     Cape May     Retail                       69.185       67.174     2954.1
             182     1993     Cape May     Gambling-                     0.000        0.000     2954.1
             183     1993     Monmouth     Lodging                      21.303       20.684       94.0
             184     1993     Monmouth     Food & restaurant             3.651        3.545       94.0
             185     1993     Monmouth     Entertainment                 0.805        0.782       94.0
             186     1993     Monmouth     Automobile                    0.688        0.668       94.0
             187     1993     Monmouth     Local transportation                                   94.0
             188     1993     Monmouth     Retail                        3.415        3.316       94.0
             189     1993     Monmouth     Gambling                      0.000        0.000       94.0
             190     1993     Ocean        Lodging                     147.972       143.671     621.4
             191     1993     Ocean        Food & restaurant            25.362       24.625      621.4
             192     1993     Ocean        Entertainment                 5.593        5.431      621.4
             193     1993     Ocean        Automobile                    4.780        4.641      621.4
             194     1993     Ocean        Local transportation                                  621.4
             195     1993     Ocean        Retail                       23.720       23.030      621.4
             196     1993     Ocean        Gambling                      0.000        0.000      621.4

             197     1994C    Atlantic     Lodging                      21.297       20.161      117.5
             198     1994     Atlantic     Food & restaurant             5.461        5.170      11'7.5
             199     1994     Atlantic     Entertainment                 3.087        2.922      117.5
             200     1994     Atlantic     Automobile                    0.698        0.661      117.5
             201     1994     Atlantic     Local transportation                                  117.5
             202     1994     Ptlantic     Retail                        4.018        3.804      117.5









              Appendix Table   1 Cont.

              OBS      YR      CO           CCODE                          COST      COST92      NIND
              203     1994     Atlantic     Gambling                      10.216        9.671        117.5
              204     1994     Cape May     Lodging                      395.086       374.025     2881.0
              205     1994     Cape May     Food & restaurant             68.118       64.487      2881.0
              206     1994     Cape May     Entertainment                 14.909       14.114      2881.0
              207     1994     Cape May     Automobile                    12.745       12.065      2881.0
              208     1994     Cape May     Local transportation                                   2881.0
              209     1994     Cape May     Retail                        63.724       60.327      2881.0
              210     1994     Cape May     Gambling                       0.000        0.000      2881.0
              211     1994     Monmouth     Lodging                       27.886       26.400        140.2
              212     1994     Monmouth     Food & restaurant              4.808        4.552        140.2
              213     1994     Monmouth     Entertainment                  1.052        0.996      140.2
              214     1994     Monmouth     Automobile                     0.900        0.852      140.2
              215     1994     Monmouth     Local transportation                                   140.2
              216     1994     Monmouth     Retail                         4.498        4.258      140.2
              21@     1994     Monmouth     Gambling                       0.000        0.000      140.2
              218     1994     Ocean        Lodging                      127.366       120.576
              219     1994     Ocean        Food & restaurant             21.960       20.789
              220     1994     Ocean        Entertainment                  4.806        4.550
              221     1994     Ocean        Automobile                     4.109        3.890
              222     1994     Ocean        Local transportation
              223     1994     Ocean        Retail                        20.543       19.448
              224     1994     Ocean        Gambling                       0.000        0.000










          Appendix Table 1 Cont.



          Note: COST is in millions of current dollars associated with the year of the study and
          refers to the projected expenditures on travel and tourism, COST92 is in millions of
          1992 dollars adjusted by the relevent CPI index, NIND refers to the estimated number of
          visitors in millions for the 1987-89 period and in thousands for the 1990-94 period.
          Regarding the 1992 tourism expenditure estimates from the Longwoods study, the 1992
          estimates under the COST column are in 1993 dollars and had to be deflated to express them
          in 1992 dollars under the COST92 column. Concerning NIND, estimates were not available on
          a county basis, only on a region basis, hence Ocean and Monmouth counties are considered
          as the Shore region (see Longwoods studies for details).




          Source:
                   *1988-89; Opinion Research Corporation, 1989.
                   a1990-91; Longwoods Int'l, 1992.
                   b,992-93; Longwoods Int'l, 1994.
                   C1994; Longwoods Int'l, 1995.
                   (see References in Chapter 3.)









                     Appendix Table 2. Historical Beach Use Data for Selected Municipalities,
                      NJ, 1970-94.


                              OBS    PLACE                  YR        TAGS     TSALES



                                 ------------------  CO=Atlantic   ------------------
                                1    Brigantine   City     1985     39352      162464
                                2    Brigantine   City     1986     38204      158645
                                3    Brigantine   City     1987     40541      168959
                                4    Brigantine   City     1988     34857      182621
                                5    Brigantine   City     1989     33393      173303
                                6    Brigantine   City     1990     34115      180884
                                7    Brigantine   City     1991     35714      186928
                                8    Margate City          1987     35058      165359
                                9    Margate City          1988     34381      172661
                                10   Ventnor City          1986     33500      200700
                                11   Ventnor City          1987     32500      195900
                                12   Ventnor City          1988     30820      182000










                     Appendix Table 2 Cont.

                          OBS      PLACE                      YR         TAGS      TSALES



                           -----------------------   CO=Cape  May  ----------------------
                          13     Cape May  City               1987       84907      403922
                          14     Cape May  City               .1988      87603      410888
                          15     Cape May  Point  Borough     1987        6143       44481
                          16     Cape May  Point  Borough     1988        5667       41208
                          17     Cape May  Point  Borough     1989        4354       41885
                          18     Cape May  Point  Borough     1990        4373       41239
                          19     Cape May  Point  Borough     1991        4540       42461
                          20     Cape May  Point  Borough     1992        4413       41833
                          21     Cape May  Point  Borough     1993        4707       43506
                          22     Cape May  Point  Borough     1994        4264       50834
                          23     Ocean City                   1984     312710      1237429
                          24     Ocean City                   1985     316687      1258194
                          25     Ocean City                   1986     310286      1246508
                          26     Ocean City                   1987     311924      1545718
                          27     Ocean City                   1988     261931      1352368
                          28     Ocean City                   1989     233560      1252579
                          29     Ocean City                   1990     282830      1341451
                          30     Ocean City                   1991     282055      1364229
                          31     Ocean City                   1992     245094      1541383
                          32     Ocean City                   1993     298896      1900872
                          33     Ocean City                   1994     280775      1865062
                          34     Sea Isle City                1991       67966      415227
                          35     Sea Isle City                1992       63351      428976
                          36     Sea Isle City                1993       74372      466766
                          37     Sea Isle City                1994       73978      469123
                          38     Stone Harbor Borough         1987       71000      306000
                          39     Stone Harbor Borough         1988       42156      258571










                     Appendix Table 2 Cont.

                          CBS     PLACE                          YR        TAGS      TSALES



                           -----------------------   CO=Monmouth   ----------------------
                          40     Asbury Park  City             1986      65670       248833
                          41     Asbury Park  City             1987      45470       205868
                          42     Asbury Park  City             1988      19155         91431
                          43     Avon by the  Sea Borough      1986      28677       449745
                          44     Avon by the  Sea Borough      1987      34103       476362
                          45     Avon by the  Sea  Borough     1988      28486       326362
                          46     Belmar Borough                1970     174141       366127
                          47     Belmar Borough                1971     190013       393996
                          48     Belmar Borough                1972     165680       359547
                          49     Belmar Borough                1973     178062       386042
                          50     Belmar Borough                1974     164631       429612
                          51     Belmar Borough                1975     177996       465029
                          52     Belmar Borough                19'76    192605       488661
                          53     Belmar Borough                1977     222514       627608
                          54     Belmar Borough                1978     227703       643877
                          55     Belmar Borough                1979     203366     .581885
                          56     Belmar Borough                1980     293849       926557
                          57     Belmar Borough                1981     278969       911624
                          58     Belmar Borough                1982     310165     1131061
                          59     Belmar Borough                1983     402596     1428545
                          60     Belmar Borough                1984     299700     1567363
                           61     Belmar  Borough             1985     320301     1949498
                           62     Belmar  Borough             1986     151225     1751054
                           63     Belmar  Borough             1987     140919     1684960
                           64     Belmar  Borough             1988      98259     1225692
                           65     Belmar  Borough             1989     144970     1052101
                           66     Belmar  Borough             1990     230344      949596
                           67     Belmar  Borough             1991     271043     1211972
                           68     Belmar  Borough             1992     234203     1064808
                           69     Belmar  Borough             1993     284249     1370331
                           70     Belmar  Borough             1994     248611     1264013
                           71     Belmar  Borough             1995     253332     1262456










                     Appendix Table 2 Cont.

                          OBS    PLACE                          YR        TAGS       TSALES



                           -----------------------   CO=Monmouth  ----------------------
                           72    Bradley Beach Borough        1986      65060      418484
                           73    Bradley Beach Borough        1987      62713      504061
                           74    Bradley Beach Borough        1988      32829      380867
                           75    Long  Branch  City           1987      35971      126979
                           76    Long  Branch  City           1988      18717        72227
                           77    Long  Branch  City           1989      25343        85428
                           78    Long  Branch  City           1990      24552        86432
                           79    Long  Branch  City           1991      40762      144684
                           80    Long  Branch  City           1992      28868      104093
                           81    Long  Branch  City           1993      35474      118799
                           82    Long  Branch  City           1994      30567      105388
                           83    Manasquan Borough            1986      73479      932202
                           84    Manasquan Borough            1987      70764      905910
                           85    Manasquan Borough            1988      57052      823572
                           86    Neptune Township             1986      53208      379812
                           87    Neptune Township             1987      34125      314000
                           88    Neptune Township             1988      12980      177240
                           89    Sea  Bright Borough          1987      15-078       61722
                           90    Sea  Bright Borough          1988      11475        47072
                           91    Sea  Girt Borough            1985      19368      312088
                           92    Sea  Girt Borough            1986      16018      339018
                           93    Sea  Girt Borough            1987      15492      350875
                           94    Sea  Girt Borough            1988      13528      323404
                           95    Sea  Girt Borough            1989      29134      237010
                           96    Sea  Girt Borough            1990      29992      268900
                           97    Sea  Girt Borough            1991      40325      310060
                           98    Sea  Girt Borough            1992      34041      290148
                           99    Sea  Girt Borough.           1993      42476      295040
                           100   Sea  Girt Borough            1994      35705      315928









                     Appendix Table 2 Cont.

                         OBS     PLACE                         YR         TAGS       TSALES



                          -----------------------    CO=Ocean  -------------------------
                        101     Berkeley Township              1992       8890       37029
                        102     Berkeley Township              1993       9418       33572
                        103     Berkeley Township              1994       5409       24607
                        104     Brick Township                 1987      12687       66980
                        105     Brick Township                 1988       9429       61917
                        106     Dover Township                 1987       2090          6270
                        107     Dover Township                 1988       1614          4842
                        108     Harvey Cedars Borough          1986      11635       64526
                        109     Harvey Cedars Borough          1987      10588       76860
                        110     Harvey Cedars   Borough        1988       9124       67142
                        ill     Long Beach Township            1986      87267       277435
                        112     Long Beach Township            1987      80769       375082
                        113     Long Beach Township            1988      @4385       346236
                        114     Seaside Heights Borough        1986     498905      1789535
                        115     Seaside Heights Borough        1987     450551      1689981
                        116     Seaside Heights Borough        1988     272779       -744694
                        117     Seaside Park Borough           1987     131492       785469
                        118     Seaside Park Borough           1988      81197       581975
                        119     Ship  Bottom Borough           1992      62668       255684
                        120     Ship  Bottom Borough           1993      54597       274444
                        121     Ship  Bottom Borough           1994      46862       310851
                        122     Ship  Bottom Borough           1995      '77051      467644
                        123     Surf  City Borough             1992      38573       248734
                        124     Surf  City Borough             1993      44790       289201
                        125     Surf  City Borough             1994      37165       299276
                        126     Surf  City Borough.            1995      36176       299000

                     Note: TAGS refers to the number of beach tags       sold, TSALES the   revenue
                      from beach tags sold.

                     Source: Obtained from individual municipalities.









            Appendix Table 3. Average Characteristics of Typical Beach Fill Projects by Reach and
            Presence of Hard Protection Structures Delineation.


             OBS    REACH      DHARD       AQUAN           ACOST           ACOST92       AEXP       AACT
               1        2        0       651024.71       2455468.99      3468778.02        5        5.0000
               2        2        1       225000.00       253618.93        969317.50        5        2.5000
               3        3        1        72500.00          51271.84      197*044.57       5        6.0000
               4        4        0        80231.20       101463.27        308193.00        5        8.8000
               5        4        1        41828.75          48025.67      151240.99        5      11.6250
               6        6        0        60660.00          50204.75      189570.92        5        2.3333
               7        7        1       239043.72       256612.59        650296.03        5      12.5455
               8        8        1       392500.00       503700.00       1937180.66        5        1.0000
               9        9        0       279408..67      294302.82        793608.98        5      13.0000
              10       10        1       581688.79       2261670.03      2771169.43        5      19.0000
              11       11        1       333218.85       1435325.31      1776595.16        5        8.9000
              12       12        1       239004.77       832364.34        915223.62        5      15.0000
              13       14        0        38000.00       172699.00        272395.05        5      11.5000
              14       14        1       222082.02       848953.82       1154499.97        5      10.0667

              Note: DHARD=O refers to    no presence of hard protection structures,        DHARD=l refers to the
              presence of hard protection structures. AQUAN refers to the quantity of fill averaged
              over all projects completed within each reach-DHARD combination, ACOST refers to the
              average cost of a project within each reach-DHARD combination, ACOST92 refers to the
              average cost in 1992 dollars, AEXP refers to the average expected life of a project
              within each reach-DHARD combination, AACT refers to the estimated average effective life
              of a project within each reach-DHARD combination.




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