Airline Deregulation: Changes in Airfares, Service, and Safety at Small,
Medium-Sized, and Large Communities (Chapter Report, 04/19/96,
GAO/RCED-96-79).

Pursuant to a congressional request, GAO examined the deregulation of
the airline industry, focusing on: (1) airfares and the quantity,
quality, and safety of air service since deregulation.

GAO noted that: (1) the average fare per passenger mile is 9 percent
lower at small-community airports, 11 percent lower at medium-sized
airports, and 8 percent lower at large-community airports; (2) the
largest increase in fares occurred in the Southeast and Appalachian
regions, and the largest decrease occurred in the West and Southwestern
regions; (3) this geographic disparity exists because of the intense
competition between low-cost, new carriers in the west and dominant,
high-maintenance carriers in the Southeast; (4) the overall quantity of
air service at airports has increased, but large communities have
experienced the largest increase; (5) air service quality is difficult
to measure and depends on the number of destinations served by nonstop
flights and one-stop connections, and the type of aircraft used; (6) air
service quality since deregulation has been mixed largely due to the
airlines hub networks and greater use of turboprop aircraft; and (7) the
overall accident rate since deregulation has dropped, but there are no
statistically significant differences in air safety trends for any of
the airport groups.

--------------------------- Indexing Terms -----------------------------

 REPORTNUM:  RCED-96-79
     TITLE:  Airline Deregulation: Changes in Airfares, Service, and 
             Safety at Small, Medium-Sized, and Large Communities
      DATE:  04/19/96
   SUBJECT:  Airline industry
             Competition
             Airports
             Commercial aviation
             Transportation rates
             Airline regulation
             Aircraft accidents
             Air transportation operations
             Economic analysis
             Transportation safety

             
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Cover
================================================================ COVER


Report to the Chairman, Committee on Commerce, Science, and
Transportation, U.S.  Senate

April 1996

AIRLINE DEREGULATION - CHANGES IN
AIRFARES, SERVICE, AND SAFETY AT
SMALL, MEDIUM-SIZED, AND LARGE
COMMUNITIES

GAO/RCED-96-79

Changes in Airfares, Service, and Safety

(341422)

CAB@Civil Aeronautics Board DOT@Department of Transportation
FAA@Federal Aviation Administration GAO@General Accounting Office
NTSB@National Transportation Safety Board OAG@Official Airline Guide
O&D@Origin and Destination Survey


Letter
=============================================================== LETTER


B-265766

April 19, 1996

The Honorable Larry Pressler
Chairman, Committee on Commerce,
 Science, and Transportation
United States Senate

Dear Mr.  Chairman: 

As you requested, this report examines the changes in (1) airfares
and (2) the quantity, quality, and safety of air service since the
deregulation of the airline industry in 1978.  Specifically, the
report compares data on these issues for airports serving small,
medium-sized, and large communities. 

As arranged with your office, unless you publicly announce its
contents earlier, we plan no further distribution of this report
until 30 days after the date of this letter.  We will then send
copies to the Secretary of Transportation; the Director, Office of
Management and Budget; and other interested parties.  We will also
make copies available to others upon request. 

If you have any questions, please call me at (202) 512-2834.  Major
contributors to this report are listed in appendix VIII. 

Sincerely yours,

John H.  Anderson, Jr.
Director, Transportation and
 Telecommunications Issues


EXECUTIVE SUMMARY
============================================================ Chapter 0


   PURPOSE
---------------------------------------------------------- Chapter 0:1

Nearly two decades have passed since the Congress began deregulating
the U.S.  airline industry.  The Airline Deregulation Act of 1978
phased out the federal government's control over fares and service,
relying instead on market forces to decide the price, quantity, and
quality of domestic air service.  In 1989, the then-Chairman, Senate
Committee on Commerce, Science, and Transportation, concerned that
people traveling to and from small and medium-sized communities might
be paying higher fares as a result of deregulation, asked GAO to
compare the trends in airfares at airports serving small and
medium-sized communities with the trend at airports serving large
communities.  GAO reported that between 1979--the earliest year for
which reliable data on fares are available--and 1988, the average
fare per passenger mile, adjusted for inflation, declined by 9
percent at small-community airports, 10 percent at
medium-sized-community airports, and 5 percent at large-community
airports.\1 GAO also found that the largest decreases were at
airports in the Southwest, regardless of the community's size.  In
June 1995, expressing concerns similar to those of his predecessor,
the Committee's current Chairman asked GAO to (1) update its analysis
of airfare trends and (2) compare changes in the quantity, quality,
and safety of air service since deregulation at airports serving
small, medium-sized, and large communities. 


--------------------
\1 Airline Deregulation:  Trends in Airfares at Airports in Small and
Medium-Sized Communities (GAO/RCED-91-13, Nov.  8, 1990). 


   BACKGROUND
---------------------------------------------------------- Chapter 0:2

Before 1978, the Civil Aeronautics Board regulated airlines,
controlling the fares they could charge and the routes they could
fly.  Legislatively mandated to promote the air transport system, the
Board believed that passengers traveling shorter distances--more
typical of travel from small and medium-sized communities--would not
choose air travel if they had to pay the full cost of service.  Thus,
the Board set fares relatively lower in short-haul markets and higher
in long-haul markets than would be warranted by costs.  Concerned
that such practices caused inefficiencies and inhibited the growth of
air transportation, the Congress deregulated the industry. 
Deregulation was expected to result in (1) lower fares at
large-community airports, from which many trips are long-distance,
and somewhat higher fares at small- and medium-sized-community
airports; (2) increased competition brought about by new airlines,
commonly referred to as "new entrant" airlines; and (3) greater use
of turboprop (propeller) aircraft by airlines in place of jets in
smaller markets that could not economically support jet service. 


   RESULTS IN BRIEF
---------------------------------------------------------- Chapter 0:3

The average fare per passenger mile, adjusted for inflation, has
fallen since deregulation about as much at airports serving small and
medium-sized communities as it has at airports serving large
communities.  In addition, the regional differences that GAO
previously found in fare trends still exist.  The largest decreases
in fares since deregulation have occurred at airports located in the
West and Southwest, regardless of the community's size.  Conversely,
the largest increases in fares have been at airports located in the
Southeast and in the Appalachian region. 

The quantity of air service, as measured by the number of both
departures and available seats, has increased since deregulation for
all three airport groups.  The largest increases in service have been
at large-community airports.  Assessing trends in the overall quality
of such service is difficult, on the other hand, because many factors
contribute to service quality and combining them into a single
objective measure is problematic.  Judging service quality involves a
subjective weighting of the relative importance of these factors,
which include, among other things, the (1) number of destinations
served by nonstop flights, (2) number of convenient one-stop
connection possibilities, and (3) type of aircraft used.  The changes
in these factors since deregulation suggest a mixed record for small
and medium-sized communities.  While the number of one-stop
connection possibilities has increased, the number of nonstop
destinations and the percentage of departures involving jets have
decreased.  These trends are largely the result of the
"hub-and-spoke" networks developed by airlines after deregulation. 
In these networks, airports serving small- and medium-sized
communities serve as spokes, connected to hub airports by frequent
service on turboprops.  At large-community airports, on the other
hand, air service has improved substantially, largely because of
their central role in these networks. 

Finally, for each airport group, the accident rate was lower in 1994
than in 1978.  However, from year to year the rates fluctuate
greatly.  These sharp fluctuations occur because in a given year
airports in a group might experience no accidents, while in the next
year they might experience two or three accidents.  As a result, GAO
did not find any statistically significant differences between the
trends in air safety for airports serving small, medium-sized, and
large communities. 


   PRINCIPAL FINDINGS
---------------------------------------------------------- Chapter 0:4


      FARES HAVE FALLEN OVERALL
      BUT HAVE RISEN SHARPLY AT
      SOME AIRPORTS
-------------------------------------------------------- Chapter 0:4.1

The average fare per passenger mile was about 9 percent lower in 1994
than in 1979 at small-community airports, 11 percent lower at
medium-sized-community airports, and 8 percent lower at
large-community airports.\2 Of the 112 airports that GAO reviewed,
fares declined at 73 and increased at 33.\3 Fares declined at 36 of
the 49 small-community airports, 19 of the 38 medium-sized-community
airports, and 18 of the 25 large-community airports.  As shown in
figure 1, the largest decreases occurred at airports serving
communities of various sizes in the West and Southwest.  In contrast,
as figure 1 also shows, the airports serving several
communities--particularly small and medium-sized communities in the
Southeast and Appalachian region--have experienced sharp increases in
fares since deregulation. 

   Figure 1:  Airports in GAO's
   Sample That Experienced an
   Increase or Decrease in
   Airfares of More Than 20
   Percent, 1979-94

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of data from the
   Department of Transportation.

   (See figure in printed
   edition.)

Factors contributing to this geographic disparity in fare trends
include the (1) intense competition at many western airports from
low-cost, new entrant airlines, such as Southwest Airlines, and (2)
dominance of one or two airlines with relatively high operating
costs, such as Delta Air Lines and USAir, at several airports in the
Southeast and in Appalachia.  In nearly every case in which fares
have fallen by more than 20 percent since deregulation, one or more
low-cost new entrant airlines serve the airport.  For example, in
1994 Southwest Airlines accounted for nearly half of the passenger
enplanements at the airport serving Albuquerque, New Mexico, where
fares have fallen by 32 percent since deregulation.  In contrast, in
every case in which fares have risen by more than 20 percent, one or
two higher-cost airlines dominate service at the airport.  For
example, Delta and USAir accounted for 96 percent of the enplanements
in 1994 at the airport serving Chattanooga, Tennessee, where fares
have risen by 26 percent since deregulation. 


--------------------
\2 In 1994, the 112 airports in GAO's sample accounted for about
two-thirds of the 7.1 million domestic airline departures and 481.7
million domestic passenger enplanements in the United States.  They
are the same airports examined in GAO's prior study. 

\3 For six airports in its sample, GAO did not find a statistically
significant increase or decrease in fares between 1979 and 1994. 
(See app.  VII.)


      MOST AIRPORTS HAVE MORE AND
      SAFER SERVICE, BUT QUALITY
      FACTORS ARE MIXED
-------------------------------------------------------- Chapter 0:4.2

In comparing the data on air service quantity for May 1978 and May
1995, GAO found that the number of scheduled departures increased by
50 percent at airports serving small communities, 57 percent at
airports serving medium-sized communities, and 68 percent at airports
serving large communities.  Likewise, the number of available seats
increased for all three groups.  Not all the airports that GAO
reviewed, however, shared in the general trend toward more air
service.  Some airports--particularly those serving small and
medium-sized communities in the Upper Midwest--had less air service
in 1995 than they did under regulation.  Sioux Falls, South Dakota,
for example, had 25 percent fewer departures and 31 percent fewer
available seats in 1995.  In addition, because of the increasing
substitution of turboprops for larger jets, a number of other small
and medium-sized communities experienced a decrease in the number of
available seats even though the number of departures increased. 
Fargo, North Dakota, for example, had a 21-percent decrease in the
number of seats, even though the number of departures increased by 25
percent. 

Although the various measures of service quality indicate that large
communities receive better air service today--in particular, with
many more departures and available nonstop destinations--than they
did in 1978, those measures show a mixed record for small and
medium-sized communities.  For example, for the small-community
airports that GAO reviewed, the number of destinations served via
one-stop flights has increased by 9 percent.  On the other hand, the
number of destinations served via nonstop flights has declined by 7
percent, and the largest declines have occurred in the Southeast and
Upper Midwest.  In addition, the use of jets has declined from 66 to
39 percent of all departures.  (App.  I summarizes the changes in
fares and service at the airports GAO reviewed). 

In general, the long-term decline in the rate of accidents has
continued since deregulation.  Indeed, there are so few accidents
each year that an increase of just one or two accidents in a given
year can cause significant fluctuation in the rate for an airport
group.  While turboprops do not have as good a safety record as the
larger jets they replaced in many markets serving small and
medium-sized communities, this fluctuation in accident rates makes it
difficult to discern any impact of the increasing use of turboprops
on relative safety between airport groups. 


   AGENCY COMMENTS AND GAO'S
   RESPONSE
---------------------------------------------------------- Chapter 0:5

GAO provided a copy of a draft of this report to the Department of
Transportation for its review and comment.  GAO discussed the draft
report with senior Department of Transportation officials, including
the Director, Office of Aviation and International Economics.  They
agreed with GAO's findings concerning the trends in airfares,
service, and safety; said that the report provides useful
information; and suggested no revisions to the report.  They also
noted that the 112 airports in GAO's sample account for a sizable
majority of the nation's air travelers.  These officials commented,
however, that the small- community airports in GAO's sample
represented the larger "small" airports in the United States and
therefore were not completely representative of the nation's smallest
airports.  They stated that they have recently completed a study,
which they expect to issue soon, on the trends in fares and service
at the smallest airports and that the conclusions of their study are
consistent with GAO's findings.  They noted that although the
airports included in their study account for only about 3 percent of
the total passenger enplanements in the United States, they believe
that the study provides a valuable and necessary complement to GAO's
report. 

GAO agrees that the Department of Transportation's study could serve
as a valuable complement to this report.  Because GAO was interested
in the trends in fares at individual airports, it was necessary to
limit the airports examined to those that had a sufficient number of
tickets to ensure that the results were statistically meaningful. 
GAO examined data on the same 112 airports that it examined in its
prior report in order to provide consistent, comparable information
in updating that report and to ensure that there were sufficient
observations for statistical validity. 


INTRODUCTION
============================================================ Chapter 1

Before 1978, the U.S.  airline industry was tightly regulated.  The
federal government controlled what fares airlines could charge and
what cities they could serve.  Concerned that government regulation
had made the industry inefficient, inhibited its growth, and caused
airfares to be too high in many heavily traveled markets involving
the nation's largest communities, the Congress passed the Airline
Deregulation Act of 1978.  The act phased out the government's
control of fares and service but did not change the government's role
in regulating and overseeing air safety.  Opponents of economic
deregulation warned that relying on competitive market forces to
determine the price, quantity, and quality of domestic air service
could adversely affect safety and harm the economies of smaller
communities.  In 1990, both GAO and the Department of Transportation
(DOT) reported that fares had fallen since deregulation at airports
serving small and medium-sized communities as well as at airports
serving large communities.\4 Studies by DOT and others have differed
in their conclusions about deregulation's impact on airline service
and safety. 


--------------------
\4 Airline Deregulation:  Trends in Airfares at Airports in Small and
Medium-Sized Communities (GAO/RCED-91-13, Nov.  8, 1990) and
Secretary's Task Force on Competition in the U.S.  Domestic Airline
Industry, U.S.  Department of Transportation (Washington, D.C.:  Feb. 
1990). 


   DEREGULATION OF THE AIRLINE
   INDUSTRY
---------------------------------------------------------- Chapter 1:1

Between 1938 and 1978, the Civil Aeronautics Board (CAB) regulated
the airline industry, controlling the fares airlines could charge and
the markets they could enter.  Legislatively mandated to promote and
develop the air transportation system, CAB believed that passengers
traveling shorter distances--more typical of travel from small and
medium-sized communities--would not choose air travel if they had to
pay the full cost of service.  Thus, in keeping with its mandate, CAB
set fares relatively lower in short-haul markets and higher in
long-haul markets than would be warranted by costs.\5 In effect,
long-distance travel subsidized short-distance markets.  In addition,
CAB did not allow new airlines to form and compete against the
established carriers. 

Concerned that these practices had, among other things, caused fares
to be too high in many markets, the Congress passed the Airline
Deregulation Act, which the President signed into law on October 24,
1978.  The act phased out CAB's control of domestic air service and
placed reliance on competitive market forces to decide fares and
service levels.  As a result, fares were expected to fall at airports
serving large communities, from which many trips are long-distance
over heavily traveled routes.  However, without the cross-subsidy
present under regulation, fares were expected to increase somewhat at
airports serving small and medium-sized communities.  In addition, it
was expected that airlines, free to make their own decisions
concerning service, would stop flying to some smaller communities
where they could not make a profit and replace jets with smaller
turboprop (propeller) aircraft in others because those communities
could not economically support jet service. 


--------------------
\5 By fares, we mean fares per passenger mile.  This measure is also
commonly referred to as "yield."


   PRIOR STUDIES BY GAO, DOT, AND
   OTHERS ASSESSED THE IMPACTS OF
   DEREGULATION
---------------------------------------------------------- Chapter 1:2

In 1989, the then-Chairman, Senate Committee on Commerce, Science,
and Transportation, concerned that people traveling to and from small
and medium-sized communities could be paying higher fares as a result
of airline deregulation, asked us to compare the trends in airfares
at airports serving small and medium-sized communities with the trend
for airports serving large communities.  Contrary to the Chairman's
expectation, however, we found that the real (adjusted for inflation)
fare per passenger mile was 9 percent lower in 1988 than in 1979 at
airports serving small communities, 10 percent lower at airports
serving medium-sized communities, and about 5 percent lower at
airports serving large communities.\6 Fares had declined at 76 of the
112 airports we reviewed (68 percent), including 38 of the 49
airports serving small communities (78 percent).  Nevertheless,
airports in several small, medium-sized, and large communities
experienced increases in fares of over 20 percent.  We noted that the
greatest fare increases tended to be in the Southeast, while the
largest fare decreases were in the Southwest.  In addition to this
study, we have reported on several other issues concerning airfares
since deregulation, including the effects of market concentration and
the industry's operating and marketing practices on fares.  These
reports are listed at the end of this report. 

In 1990, DOT also reported that airfares were lower since
deregulation at airports of all sizes and that small communities had
experienced the greatest decline in fares.  DOT attributed the
overall lower fares to increased competition, noting that 55 percent
of all passengers in 1988 traveled in city-pair markets served by
three or more air carriers, up from 28 percent in 1979.  Similarly,
DOT held that the main reason for the second, less expected, finding
was that competition had increased on routes from many smaller
markets as a result of the "hub-and-spoke" networks developed by
airlines after deregulation.  In these networks, airports serving
small and medium-sized communities serve as spokes, connected to
large hub airports by frequent service on smaller turboprop aircraft. 
According to DOT, the hub-and-spoke system has increased competition
and improved service for small and medium-sized communities by
providing greater frequency of flights, convenience, and travel
options to the public than was provided during regulation.  DOT held
that

     "Smaller cities have benefited from the shift to hub and spoke
     service.  Most small cities receive more frequent service than
     previously, and many now receive service to connecting hubs from
     more than one major airline or their affiliates, thereby
     providing the traveler with a choice of airlines and routings to
     most destinations."\7

Many other studies have been conducted of deregulation's impact on
airfares and service.  While generally concluding that fares overall
have declined, the studies have reached different conclusions about
the impact on the quantity and quality of service.  For example,
Morrison and Winston estimated that the lower fares since
deregulation save passengers $12.4 billion annually.\8 They also
estimated that because of the (1) increased number of flights, (2)
efficiencies of the hub-and-spoke networks in connecting smaller
communities to the overall aviation system, and (3) resulting savings
in travel time, passengers save an additional $10.3 billion a year as
a result of deregulation.  While other studies generally agree that
fares have decreased since deregulation, they point out that the
lower fares may have been achieved at the cost of reduced service
quantity and quality for many smaller and medium-sized communities
and that therefore the overall net benefits of deregulation are less
clear.  Brenner, for example, concluded that service quality has
declined for small and medium-sized communities, largely because his
research showed that a number of very small communities have lost air
service completely and that many small and medium-sized communities
are served mostly or entirely by turboprops, as opposed to the jet
service they had under regulation.\9

Extensive research has also been conducted on the impact of
deregulation on air safety.\10 This body of work commonly
acknowledges that since deregulation, the rate of accidents has
continued its historic decline.  Figure 1.1 shows the sharp decline
in the number of airline accidents per million aircraft miles flown
since 1960.\11

Although the rate of improvement has slowed in recent years as the
number of accidents each year has grown very small, the accident rate
for airlines in 1994 (0.004 accidents per million aircraft miles
flown) was half the rate in 1978 (0.008 accidents per million
aircraft miles flown).  Preliminary data for 1995 indicate that the
rate increased somewhat, although it remained below the rate in 1978. 

   Figure 1.1:  U.S.  Airlines'
   Accident Rates, 1960-95

   (See figure in printed
   edition.)

Note:  Data for 1995 are preliminary. 

Source:  GAO's illustration based on information from the National
Transportation Safety Board (NTSB) and Bureau of Transportation
Statistics. 

A study committee sponsored by the National Research Council
concluded that the decline in the accident rate has largely been a
result of the (1) introduction in the 1960s of more advanced, "second
generation" jet aircraft into the U.S.  fleet (such as the 727,
737-200, and DC-9) in place of the first generation of jets
introduced in the late 1950s (such as the 707 and DC-8) and (2)
subsequent advancements in aircraft technology, air traffic control
procedures, and pilot training.\12 The committee found little
evidence to support concerns that deregulation had negatively
affected air safety in general or safety for travelers from small and
medium-sized communities in particular. 

Nevertheless, others have come to different conclusions, holding that
deregulation has prevented further gains in safety because the
increased competitive pressures brought by deregulation have forced
airlines to limit spending on maintenance.  Rose, for example,
demonstrated some correlation between lower profitability and higher
accident rates, particularly for smaller airlines.\13 Many of these
researchers also believe that for smaller communities, air safety has
decreased since deregulation because substituting commuter carriers
and turboprops, which have higher accident rates, for larger airlines
and jet aircraft at these airports has increased those communities'
accident risk.  Although the accident rate for commuter carriers fell
by 93 percent between 1978 and 1995 (from 0.270 to 0.019 accidents
per million aircraft miles flown), these researchers note that the
accident rate for these carriers in 1995 was still more than three
times higher than the rate for the larger airlines.  Nevertheless,
research has been inconclusive to date on whether the increased
presence of commuter airlines and turboprops has resulted in more
accidents at airports serving small communities. 


--------------------
\6 We analyzed data on fares at 112 airports:  49 serving small
communities, 38 serving medium-sized communities, and 25 serving
large communities.  All of the airports in our study were among the
largest 175 in the nation.  We defined small communities as those
with a metropolitan statistical area population of 300,000 or less,
medium-sized communities as those with a metropolitan statistical
area population of 300,001 to 600,000, and large communities as those
with a metropolitan statistical area population of 1.5 million or
more. 

\7 Secretary's Task Force on Competition in the U.S.  Domestic
Airline Industry, DOT, 1990. 

\8 Steven A.  Morrison and Clifford Winston, The Evolution of the
Airline Industry (Washington, D.C.:  The Brookings Institution,
1995). 

\9 Melvin A.  Brenner, "Airline Deregulation:  A Case Study in Public
Policy Failure," Transportation Law Journal, Vol.  16, Issue 2, 1988. 

\10 See for example Clinton V.  Oster, Jr., John S.  Strong, and C. 
Kurt Zorn, Why Airplanes Crash:  Aviation Safety in a Changing World
(Oxford University Press, 1992), and Winds of Change:  Domestic Air
Transport Since Deregulation, National Research Council, Committee
for the Study of Air Passenger Service and Safety Since Deregulation,
Transportation Research Board Special Report 230 (Washington, D.C.,
1991). 

\11 Aviation accident rates are generally calculated either per
million aircraft miles or per 100,000 departures.  Both measures show
that accident rates have fallen substantially since 1960 and that
this decline has continued, albeit gradually, since deregulation.  In
fig.  1.1, we use million aircraft miles because this measure
provides a better gauge of overall accident risk, as flights are
generally over longer distances today.  In chapter 3, however, we
calculate rates for the airports in our sample using the number of
departures from those airports, primarily because airport-specific
data on aircraft miles flown are not available. 

\12 Winds of Change:  Domestic Air Transport Since Deregulation,
1991. 

\13 Nancy L.  Rose, "Profitability and Product Quality:  Economic
Determinants of Airline Safety Performance," Journal of Political
Economy, Vol.  98 (Oct.  1990). 


   OBJECTIVES, SCOPE, AND
   METHODOLOGY
---------------------------------------------------------- Chapter 1:3

Noting that several years had passed since our comparison of airfares
at airports serving small, medium-sized, and large communities, the
Chairman, Senate Committee on Commerce, Science, and Transportation,
asked us to update our work and to determine whether the regional
differences in airfare trends that we previously observed still
existed.  In addition, expressing concern that deregulation may have
adversely affected small and medium-sized communities to the extent
that airlines eliminated service or replaced jets with turboprops and
noting that opinions differed on this subject, the Chairman requested
that we compare the changes in the quantity, quality, and safety of
air service since deregulation for airports serving small,
medium-sized, and large communities. 

In updating our prior comparison of airfares, we analyzed data on
fares for the same 112 airports that we had reported on previously. 
Specifically, we examined the trends in the average yields--fares per
passenger mile--between 1979, 1984, 1988, 1991, 1994, and the first
half of 1995 for travel out of 49 airports serving small communities,
38 airports serving medium-sized communities, and 25 airports serving
large communities.  In 1994, these airports accounted for 4.7 million
(66 percent) of the 7.1 million domestic airline departures and 320.6
million (67 percent) of the 481.7 million domestic airline
enplanements in the United States.  In our prior report, we examined
the trends using fare data for 1979, 1984, and 1988 for these
communities.  We updated these trends using data for 1991 and 1994
because (1) 1991 represented the mid-point between 1988 and 1994 and
(2) the 1994 fare data were the most current full-year data available
at the time of our review.  The data for the first 6 months of 1995
provided us with the most current data available.  To provide
consistent, comparable information, we identified and used the same
routes (origin and destination airport combinations) that we reviewed
in our prior work.  We also adjusted the fare data for inflation,
using the consumer price index, so that the fares in each of the
years reflect 1994 dollar values. 

As in our previous study, we used DOT's "Passenger Origin-Destination
Survey" (O&D Survey).  The O&D Survey contains data reported
quarterly to DOT by airlines from a 10-percent sample of all tickets
sold.  Because the estimate of the fare per passenger mile is
developed from a statistical sample, it has a sampling error.  The
sampling error is the maximum amount by which the estimate obtained
from the sample can be expected to differ from the actual fare per
passenger mile if the entire universe of tickets were examined.  Each
sampling error was calculated at the 95-percent confidence level. 
This means the chances are 19 out of 20 that if we reviewed all
tickets purchased, the results would differ from the estimate
obtained from our sample by less than the sampling error.  (App.  II
provides estimates of fares, and app.  III provides the sampling
error for each of these estimates.)

To determine why regional differences in airfares may exist, we
analyzed DOT's data on airline market shares at each of the 112
airports and discussed with DOT analysts and airline representatives
how the presence of different carriers may affect fares.  To
determine the extent to which economic changes could explain any
observed regional differences, we analyzed data provided by the
Bureau of Economic Analysis on economic growth between 1979 and 1993,
which was the latest year for which data were available, for each of
the 112 communities served by the airports we reviewed.  Appendix VII
provides additional details on the scope and methodology of our
analyses of airfares. 

To compare changes in the quantity of air service since deregulation
at airports serving small, medium-sized, and large communities, we
analyzed data for our 112 airports for May 1978 and May 1995 from the
Official Airline Guide (OAG), a privately published list of all
scheduled commercial flights.  Specifically, we documented changes in
the total number of departures as well as the total number of
available seats for each airport.  We examined data from 1978 because
they provided information on air service before deregulation and data
from 1995 because they were the latest available at the time of our
review.  We chose May to avoid the typical seasonal airline schedule
changes that occur in the winter and summer months.  We used the OAG
as our primary data source because DOT's database on total annual
departures by airport contains only the data reported by the airlines
that operate aircraft with more than 60 seats.  As a result, DOT's
data on airport operations do not provide information on departures
by commuter carriers or air taxis.  However, we analyzed DOT's data
on annual departures by the larger airlines and the Federal Aviation
Administration's (FAA) estimates of annual commuter and air taxi
departures for each airport to confirm the results of our analyses of
the OAG data. 

To compare changes in the quality of air service since deregulation
at airports serving small, medium-sized, and large communities, we
analyzed the OAG data described above for the 112 airports in our
sample.  Specifically, for each airport we calculated the changes in
a number of indicators of service quality, including the number of
destinations served by nonstop and one-stop flights and the
percentage of jet departures.  We then summarized these calculations
for the three airport groups and compared the trends in the various
quality indicators to gain an overall perspective on how service
quality has changed.  We did not, however, develop a formula that
would weight these indicators and provide an overall "quality score"
for each airport because developing such weights requires subjective
judgments of the relative importance of each indicator. 

To compare the trends in the safety of air service since deregulation
at small, medium-sized, and large community airports, we analyzed
National Transportation Safety Board (NTSB) data on airline,
commuter, and air taxi accidents (1) that occurred at or near each of
the airports in our sample and (2) for which the airport in our
sample was the origin or destination of the flight.  Using these
data, we calculated accident rates per 100,000 departures for each
airport from 1978 through 1994.  We then calculated the overall rate
for each of the three airport groups. 

We discussed a draft of this report with senior DOT officials,
including the Director, Office of Aviation and International
Economics.  They agreed with our findings concerning the trends in
airfares, service, and safety since deregulation and suggested no
revisions to the report.  Additional details on their comments and
our response are provided at the end of chapter 3.  We conducted our
review from August 1995 through March 1996 in accordance with
generally accepted government auditing standards. 


AIRFARES HAVE FALLEN SINCE
DEREGULATION AT AIRPORTS SERVING
COMMUNITIES OF ALL SIZES
============================================================ Chapter 2

Overall, airfares, adjusted for inflation, have declined since
deregulation at airports serving small, medium-sized, and large
communities.  The largest reductions have occurred at airports
located in the West and Southwest, regardless of the community's
size.  Increased competition, stimulated largely by the entry of
low-cost, low-fare airlines at these airports, has been a key factor
in the decline in fares.  By contrast, some airports in our sample,
particularly those serving small and medium-sized communities in the
Southeast and Appalachia, have experienced large increases in fares
since deregulation.  At these airports, one or two larger,
higher-cost carriers account for the vast majority of passenger
enplanements.  Until very recently, these airlines have faced
relatively little competition, particularly from low-cost new entrant
airlines.  The geographic disparity in airfare trends also stems from
several adverse factors, such as airport congestion and poor weather
conditions, that contribute to higher costs and are more prevalent in
the eastern United States. 


   FARES ARE LOWER OVERALL, BUT
   SOME AIRPORTS HAVE EXPERIENCED
   SIZABLE INCREASES
---------------------------------------------------------- Chapter 2:1

Over 5 years ago, we reported that real airfares (adjusted for
inflation) had fallen between 1979 and 1988 not only at airports
serving large communities, as was expected, but also at airports
serving small and medium-sized communities.\14 As figure 2.1 shows,
real fares through the first 6 months of 1995 for all three airport
groups remained lower than they were in 1979.  When full-year data
for 1979 and 1994 are compared, fares were 8.5 percent lower at
airports serving small communities, 10.9 percent lower at airports
serving medium-sized communities, and 8.3 percent lower at airports
serving large communities.\15 However, as figure 2.1 also shows,
since 1988 fares have risen slightly at airports serving small and
medium-sized communities and fallen slightly at airports serving
large communities. 

   Figure 2.1:  Comparison of
   Airfares at Airports Serving
   Small, Medium-Sized, and Large
   Communities for Selected Years

   (See figure in printed
   edition.)

Note:  1995 data are for the first 6 months of the year. 

Source:  Illustration based on GAO's analysis of DOT's O&D Survey. 

As figure 2.1 also shows, despite the overall trend toward lower
fares since deregulation, fares at small- and medium-sized-community
airports have been consistently higher than fares at large-community
airports.  It is generally accepted that fares tend to be lower at
large-community airports because of the economies associated with
traffic volume and trip distance.  As the volume of traffic and
average length of the trip increase, the average cost per passenger
mile decreases, allowing for lower fares.  Airports serving small and
medium-sized communities tend to have fewer heavily traveled routes
and shorter average trip distances, resulting in higher average costs
and higher fares per passenger mile than those of large-community
airports. 

Nevertheless, fares fell following deregulation for most of the
airports that we reviewed.  (App.  I provides a summary of the
overall changes in both fares and service at the airports in our
review, and app.  II shows the specific fare trends at each airport.)
Of the 112 airports in our sample, 73 airports experienced a decline
in fares.  Specifically, fares declined at 36 of the 49 airports
serving small communities, 19 of the 38 airports serving medium-sized
communities, and 18 of the 25 airports serving large communities.\16

The general trend toward lower fares has largely resulted from
increased competition.  Between the onset of deregulation and 1994,
the average number of large airlines competing at the small-community
airports that we reviewed increased from 1.8 to 2.8, and the average
number of commuter carriers increased from 2.5 to 4.5.\17 Similarly,
the average number of large airlines competing at airports serving
medium-sized communities increased from 2.8 to 4.3, and the average
number of commuter carriers increased from 3.3 to 4.6.  Finally, the
average number of large airlines competing at the large-community
airports that we reviewed increased from 9.0 to 11.2, although the
number of commuter carriers decreased from 11.3 to 6.4. 

In addition, the transition to hub-and-spoke systems since
deregulation has increased competition at many airports serving small
and medium-sized communities.  By bringing passengers from multiple
origins (the spokes) to a common point (the hub) and placing them on
new flights to their ultimate destinations, these systems provide for
more frequent flights and more travel options than did the direct
"point-to-point" systems that predominated before deregulation. 
Thus, instead of having a choice of a few direct flights between
their community and a final destination, travelers departing from a
small community might now choose from among many flights from several
airlines through different hubs to that destination. 

While real fares fell at the majority of airports, fares rose--in
some cases substantially--for 33 of the 112 airports.  Table 2.1
shows the five airports of those we reviewed that had the largest
fare decreases and the five airports with the largest fare increases. 
As table 2.1 indicates, those airports experiencing the largest
increases in fares serve small and medium-sized communities and have
had a decrease or little change in the number of large airlines and
commuter carriers.  Conversely, the airports experiencing the largest
decrease in fares since deregulation have had a substantial increase
in the number of large airlines and, to a lesser extent, an increase
in the number of commuter carriers. 



                                        Table 2.1
                         
                           Airports With Largest Increases and
                          Decreases in Yield (Fare per Passenger
                                      Mile), 1979-94

                                      (1994 dollars)

                                     1979              Percentage   Change in   Change in
                                    yield  1994 yield   change in   number of   number of
Airport            Size           (cents)     (cents)       yield    airlines   commuters
-----------------  ----------  ----------  ----------  ----------  ----------  ----------
Yield decrease
-----------------------------------------------------------------------------------------
Phoenix, AZ        Large             22.2        15.0       -32.4         + 4         + 3
Albuquerque, NM    Medium            24.4        16.5       -32.4         + 5          -2
Las Vegas, NV      Medium            22.5        15.3       -32.2         + 7          -2
El Paso, TX        Medium            24.3        16.6       -31.5         + 3          -1
Midland, TX        Small             27.0        18.6       -31.1         + 1         + 2

Yield increase
-----------------------------------------------------------------------------------------
Augusta, GA        Medium            23.5        29.7      + 26.3           0          -4
Chattanooga, TN    Medium            25.6        32.3      + 26.2          -1          -1
Knoxville, TN      Medium            25.0        31.3      + 25.1         + 1         + 1
Jackson, MS        Medium            24.0        30.0      + 25.1           0         + 3
Charleston, WV     Small             26.0        32.4      + 24.7         + 1          -1
-----------------------------------------------------------------------------------------
Source:  GAO's analysis of DOT's data from the O&D Survey and Forms
41 and 298-C. 


--------------------
\14 Airline Deregulation:  Trends in Airfares at Airports in Small
and Medium-Sized Communities (GAO/RCED-91-13, Nov.  8, 1990). 

\15 When the increase in fares that occurred between 1994 and the
first half of 1995 is factored in, the fares since deregulation are
6.1 percent lower at airports serving small communities, 9.1 percent
lower at airports serving medium-sized communities, and 5.9 percent
lower at airports serving large communities.  Because the data for
1995 cover only 6 months, however, we used primarily the latest
available full-year data (for 1994) in analyzing the trends since
deregulation. 

\16 For six airports in our sample, we were unable to determine the
direction, if any, of the change in fares from 1979 to 1994.  Because
the data on fares are developed from a statistical sample of tickets,
they have a measurable precision, or sampling error.  For these
airports, it was not possible to determine the direction of the
change in fares due to sampling error.  (See app.  VII.)

\17 Large airlines operate aircraft with more than 60 seats and
report traffic data to DOT on Form 41.  Commuter carriers operate
aircraft with 60 or fewer seats and report less-detailed traffic data
to DOT on Form 298-C.  To ensure that we only included large airlines
that provided at least a minimum level of competition at an airport,
we counted only those airlines that had at least 100 annual
departures at that airport.  Because DOT's data on commuter carriers
do not provide such detail, we did not set such a minimum threshold
for commuter carriers. 


   REGIONAL DIFFERENCES IN FARE
   TRENDS ARE CAUSED LARGELY BY
   THE ENTRY OF LOW-COST AIRLINES
   AND MORE COMPETITION IN THE
   WEST
---------------------------------------------------------- Chapter 2:2

Since deregulation, the largest decreases in fares have occurred at
airports in the West and Southwest, and the largest increases in
fares have occurred at airports in the Southeast and Appalachian
region.  In the West and Southwest, fares have declined largely
because of increased competition caused by the entry of new airlines,
particularly low-cost airlines such as Southwest and Reno Air.  Over
the last decade, high economic growth, relatively little airport
congestion, and more favorable weather conditions have attracted
these airlines to serve western airports.  By contrast, competition
at airports serving the Southeast and Appalachia has been more
limited because (1) low-cost carriers have generally avoided the East
because of its slower growth, airport congestion, and harsher weather
and (2) one or two relatively high-cost carriers have dominated the
routes to and from these airports.  Although during 1994 one low-cost
airline initiated operations in the East and subsequently failed,
other low-cost airlines, such as Valujet, have emerged to compete
with the higher-cost carriers in some eastern markets.  However, data
are not yet available to determine the extent to which these low-cost
carriers have affected fare trends in the East. 


      AIRFARE TRENDS SINCE
      DEREGULATION DIFFER BETWEEN
      WEST AND EAST
-------------------------------------------------------- Chapter 2:2.1

As figure 2.2 shows, the airports in our sample that experienced the
largest fare decreases following deregulation are predominantly
located in the West and Southwest.  These substantial declines in
real fares were experienced by airports serving large communities as
well as by those serving small and medium-sized communities.  Of the
15 airports in our sample for which fares declined by more than 20
percent between 1979 and 1994, 5 serve small communities, 5 serve
medium-sized communities, and 5 serve large communities.  By
contrast, the largest fare increases occurred at airports that serve
small and medium-sized communities in the Southeast and Appalachia
(see fig.  2.2).  Of the eight airports for which fares have
increased by more than 20 percent since 1979, three serve small
communities, four serve medium-sized communities, and one serves a
large community. 

   Figure 2.2:  Airports for Which
   Fares Increased or Decreased by
   More Than 20 Percent, 1979-94

   (See figure in printed
   edition.)

Note:  We only included those airports where the change in fares
between 1979 and 1994 was greater than 20 percent regardless of the
sampling error (i.e., the lower bound estimate of the percentage
change was greater than plus or minus 20 percent). 

Source:  Illustration based on GAO's analysis of DOT's O&D Survey. 


      COMPETITIVE CONDITIONS HAVE
      GEOGRAPHICAL DIFFERENCES
-------------------------------------------------------- Chapter 2:2.2

Over the last 17 years, a number of new airlines with very low
operating costs--including America West, American Trans Air, Markair,
Morris Air, Reno Air, and Southwest--have begun interstate air
service, primarily concentrating their operations in the West.\18
These low-cost airlines have focused on the West because of that
region's higher economic growth rates, lesser airport congestion, and
more favorable weather.  Because of their style of service--high
frequency between a limited number of city-pairs and few
amenities--these airlines have operating costs that are about 30
percent lower than those of larger airlines such as American and
United.  As a result, these low-cost airlines are able to charge
lower fares.  Further downward pressure on fares is caused by the
competitive responses of the larger carriers.  To date, these
responses have ranged from substantial fare cuts in the case of
Northwest to the creation by United in late 1994 of a low-cost
"airline within an airline"--called Shuttle by United--to compete
with Southwest in key markets on the West Coast.  We found the
presence of low-cost carriers and the resulting increase in
competition to be a common factor at the airports in our sample that
have experienced the largest fare decreases since deregulation.  In
1994, low-cost airlines accounted for at least 10 percent, and often
much more, of the total enplanements at 14 of the 15 airports that
experienced the largest decreases in fares (see table 2.2). 



                               Table 2.2
                
                 Airports for Which Fares Have Declined
                     by More Than 20 Percent Since
                 Deregulation and Market Share of Low-
                Cost Airlines at Those Airports in 1994

                              Percentage
                             decrease in                    Percentage
                            fares, 1979-  Low-cost             of 1994
Community                             94  airlines        enplanements
--------------------------  ------------  --------------  ------------
Small
----------------------------------------------------------------------
Midland, TX                        -31.1  Southwest               74.2
Lafayette, LA                      -23.2  None                     0.0
Eugene, OR                         -22.4  Morris                  10.0
                                           Reno                    0.3
Fort Myers, FL                     -21.8  American Trans           9.4
                                           Air Spirit              1.6
                                           Valujet                 1.5
Reno, NV                           -21.1  Reno                    29.9
                                           Southwest              25.2
                                           America West           12.2
                                           Morris                  1.6
                                           Markair                 0.5

Medium
----------------------------------------------------------------------
Albuquerque, NM                    -32.4  Southwest               46.1
                                           America West            7.8
                                           Frontier                0.3
Las Vegas, NV                      -32.2  Southwest               26.1
                                           America West           22.6
                                           Reno                    2.0
                                           Morris                  1.5
                                           Markair                 0.9
El Paso, TX                        -31.5  Southwest               63.8
                                           America West            7.1
                                           Frontier                0.5
Colorado Springs, CO               -23.6  America West            12.8
                                           Morris                  7.7
                                           Reno                    0.8
Tucson, AZ                         -22.7  America West            22.2
                                           Morris                 14.6
                                           Southwest               4.5
                                           Reno                    4.2
                                           Frontier                0.4

Large
----------------------------------------------------------------------
Phoenix, AZ                        -32.4  America West            37.9
                                           Southwest              31.3
                                           Morris                  0.8
                                           Reno                    0.5
                                           Markair                 0.3
Houston (Hobby), TX                -28.3  Southwest               77.8
Seattle, WA                        -27.1  Reno                     3.0
                                           Morris                  2.8
                                           Markair                 2.8
                                           Southwest               2.6
Kansas City, MO                    -25.1  Southwest               21.8
                                           America West            4.3
                                           Markair                 1.5
San Diego, CA                      -24.1  Southwest               33.7
                                           America West            5.4
                                           Reno                    5.0
                                           Morris                  1.7
                                           Markair                 0.9
----------------------------------------------------------------------
Source:  GAO's analysis of DOT's data from the O&D Survey and Form
41. 

In part, these low-cost competitors have been attracted by the
relatively strong economic growth at the communities these airports
serve.  Between 1979 and 1993, the average annual growth in
population, personal income, and employment at these 15 communities
substantially exceeded that for the other 97 communities in our
sample (see table 2.3).  In particular, low-cost airlines have been
attracted to the area of strongest economic growth:  the Southwest. 
For example, in Phoenix, Arizona--where fares have fallen by 32
percent since deregulation--the average annual growth in population
between 1979 and 1993 was 3.0 percent; in personal income, 3.7
percent; and in employment, 3.7 percent.  Moreover, for rapidly
growing Las Vegas, Nevada--where fares also fell by 32 percent--the
average annual rate of growth exceeded 5.0 percent for all three
measures. 



                               Table 2.3
                
                     Average Annual Growth Rates in
                    Population, Personal Income, and
                Employment for Communities Experiencing
                Largest Declines in Fares Compared With
                  All Other Communities in Our Sample,
                                1979-93

                                 Average                       Average
                                  annual  Average annual        annual
                              percentage      percentage    percentage
                               change in       change in     change in
                             population,   income, 1979-   employment,
Category                         1979-93              93       1979-93
--------------------------  ------------  --------------  ------------
15 communities whose                 2.2             2.8           2.6
 airports had the largest
 fare decreases
All other airports in                0.9             2.0           1.5
 sample
----------------------------------------------------------------------
Source:  GAO's analysis of Bureau of Economic Analysis's data. 

By contrast, the largest fare increases occurred in the Southeast and
Appalachia, where competition has been lacking and economic growth
has been comparatively slower.  At all eight airports where fares
increased by more than 20 percent, Delta and USAir--airlines that
have historically had among the highest operating costs in the
industry--accounted for the overwhelming majority of enplanements in
1994 (see table 2.4). 



                               Table 2.4
                
                Airports for Which Fares Have Increased
                     by More Than 20 Percent Since
                Deregulation and Market Share of Higher-
                Cost Airlines at Those Airports in 1994

                              Percentage
                             increase in                    Percentage
                            fares, 1979-  Higher-cost          of 1994
Community                             94  carrier         enplanements
--------------------------  ------------  --------------  ------------
Small
----------------------------------------------------------------------
Charleston, WV                     +24.7  USAir                   72.4
Montgomery, AL                     +23.6  Delta                   79.8
Huntsville, AL                     +22.5  Delta                   50.7
                                           USAir                  10.9

Medium
----------------------------------------------------------------------
Augusta, GA                        +26.3  Delta                   73.5
                                           USAir                  15.1
Chattanooga,TN                     +26.2  Delta                   76.1
                                           USAir                  19.6
Knoxville, TN                      +25.1  Delta                   58.7
                                           USAir                  14.9
Jackson, MS                        +25.1  Delta                   86.8

Large\a
----------------------------------------------------------------------
Pittsburgh, PA                     +21.4  USAir                   90.2
                                           Delta                   2.4
----------------------------------------------------------------------
\a Like Pittsburgh, the six other large-community airports that
experienced increases in fares are large hub airports dominated by
one or two of the established carriers:  Atlanta (Delta), Dallas
(American and Delta), Detroit (Northwest), Minneapolis (Northwest),
Chicago (American and United), and Philadelphia (USAir). 

Source:  GAO's analysis of DOT's data from the O&D Survey and Form
41. 

In part, there has been little new entry at these eight airports
because of the slower growth rates for the communities these airports
serve.  The average annual rates of growth during this period were
only 0.1 percent for population, 1.3 percent for personal income, and
0.9 percent for employment. 


--------------------
\18 Before deregulation, Southwest provided intrastate air service
within Texas. 


      FARES ROSE AT MORE EASTERN
      AIRPORTS IN FIRST HALF OF
      1995, BUT RECENT ENTRY OF
      LOW-COST AIRLINES COULD
      REVERSE TREND
-------------------------------------------------------- Chapter 2:2.3

Overall, the average airfare rose slightly during the first 6 months
of 1995 compared with 1994 at all three categories of airports.  At
small-community airports, real fares rose by 2.6 percent; at
medium-sized-community airports, by 2.1 percent; and at
large-community airports, by 2.5 percent.  Despite these increases,
59 of the 112 airports in our sample continued to have lower real
airfares than they had in 1979.  Specifically, when the data on the
first half of 1995 were factored in, real fares since deregulation
were lower at 28 of the 49 small-community airports, 17 of the 38
medium-sized-community airports, and 14 of the 25 large-community
airports. 

The largest fare increases during the first 6 months of 1995 occurred
in the East, primarily at small- and medium-sized communities in
North Carolina and South Carolina.  These fare increases occurred
largely because of a loss of competition.  In early 1994, Continental
Airlines created a separate, low-cost service in the East similar to
the operations of the low-cost carriers in the West and Southwest. 
Continental's service--commonly referred to as "Calite"--failed and
was terminated in early 1995.  As table 2.5 shows, all 10 airports
that experienced the largest fare increases between 1994 and the
first 6 months of 1995 were either served by Calite during 1994 or
located near an airport served by Calite.  According to DOT analysts
and Continental representatives, the termination of Calite service at
three airports--Greensboro/High Point, North Carolina; Charleston,
South Carolina; and Greenville, South Carolina--greatly lessened
overall price competition in the geographical area within about 100
miles of those airports.  As a result of the higher fares caused by
the loss of Calite service or nearby competition from Calite, the
trend toward lower fares since deregulation was reversed at all but 1
of the 10 airports (see table 2.5). 



                                        Table 2.5
                         
                           The 10 Airports That Experienced the
                         Largest Fare Increases in First 6 Months
                                of 1995 Compared With 1994

                                                                        Airport served by
                                                                              Calite that
                                   Percentage  Percentage                  affected fares
                                    change in   change in        Lost             (within
                                       fares,      fares,     service   approximately 100
Community           Size              1979-94     1994-95  by Calite?              miles)
------------------  ------------  -----------  ----------  ----------  ------------------
Asheville, NC       Small               -18.4      + 23.8          No      Greenville, SC
Charleston, SC      Medium               -4.9      + 23.2         Yes                None
Greenville, SC      Medium               -0.4      + 19.5         Yes                None
Myrtle Beach, SC    Small                -9.0      + 19.1          No      Charleston, SC
Roanoke, VA         Small               -11.6      + 19.0          No      Greensboro, NC
Wilmington, NC      Small                -9.5      + 18.5          No      Charleston, SC
Savannah, GA        Small                -2.9      + 14.3          No      Charleston, SC
Cleveland, OH       Large                -8.7      + 13.3         Yes                None
Columbia, SC        Medium              + 8.1      + 13.3          No      Charleston, SC
Newark, NJ          Large               -14.9      + 11.9         Yes                None
-----------------------------------------------------------------------------------------
Note:  The airport serving Wilmington, North Carolina, is about 150
miles from Charleston, South Carolina, but is approximately 60 miles
from the airport serving Myrtle Beach, South Carolina, which was
affected by the loss of competition from Calite in Charleston. 

Source:  GAO's analysis of DOT's O&D Survey. 

According to Continental's representatives, Calite failed largely
because the airline could not successfully compete against the
dominant positions of Delta and USAir.  Other airline representatives
claimed that Calite overextended itself by growing too fast and by
attempting to challenge Delta and USAir in too many markets.  Since
the demise of Calite, however, several other low-cost carriers, such
as Valujet and Kiwi, have initiated service in the East.  Some
industry observers believe that these airlines might succeed because
they have focused on a smaller number of markets than Calite did. 

The most successful of these low-cost carriers to date has been
Valujet.  After starting service in late 1993 with two airplanes
serving three routes, Valujet has grown to 41 aircraft, as of
December 1995, serving 25 cities from Atlanta and 11 cities from
Washington, D.C.  In 1995, it had an operating profit of $107.8
million and an operating profit margin of 29 percent, compared with 9
percent for Delta and 6 percent for both American and United. 
However, Valujet has begun to experience some of the problems of
operating in the East.  For example, in late 1995 Valujet was unable
to obtain take-off and landing slots at New York's congested
LaGuardia Airport.  As a result, it could not begin its planned
low-cost, low-fare service between New York and Atlanta.\19

Valujet's growth has sparked competitive responses from the dominant
airlines in the East.  Delta, for example, plans to create a
separate, low-cost operation of its own in the East starting in mid-
to late 1996.  However, largely because (1) most of Valujet's growth
occurred in the second half of 1995 and (2) the competitive responses
of other airlines are only beginning to unfold, data are not yet
available to determine the extent to which Valujet has affected fares
in the East. 


--------------------
\19 Valujet is suing TWA and Delta claiming that TWA reneged on an
agreement to sell Valujet 10 slots.  Despite the agreement, according
to Valujet, TWA sold the slots to Delta--the only airline with
nonstop service between Atlanta and New York.  Separately, DOT and
the Department of Justice are currently investigating Valujet's
allegations.  Although still pursuing its lawsuit against TWA and
Delta, Valujet in March 1996 obtained 10 different slots from
Continental and plans to begin low-fare, nonstop service between
Atlanta and New York in May 1996. 


THE QUANTITY AND SAFETY OF AIR
SERVICE HAVE GENERALLY INCREASED,
BUT TRENDS IN QUALITY INDICATORS
ARE MIXED
============================================================ Chapter 3

Overall, the quantity of air service has increased since deregulation
at small-, medium-sized, and large-community airports.  The largest
growth has occurred at large-community airports.  Not all the
airports that we reviewed, however, shared in this general trend
toward more air service.  Some airports--particularly those serving
small and medium-sized communities in the Upper Midwest--have less
air service today than they did under regulation.  Measuring the
overall quality of air service is more problematic because there are
many dimensions of "quality" and not everyone agrees on the relative
importance of each.  In general, the factors that are usually
considered to be the primary factors in service quality suggest that
for small and medium-sized communities the results are mixed.  For
large communities, on the other hand, the trends are less ambiguous
and quality has improved in almost every dimension.  Finally, the
safety of air service has generally improved since deregulation at
all three categories of airports.  Indeed, because so few accidents
occur each year, an increase of just one or two accidents in a given
year can cause significant fluctuation in the accident rate for any
one airport group, making it difficult to reach conclusions about
relative safety between the groups. 


   THE NUMBER OF DEPARTURES AND
   AVAILABLE SEATS HAVE INCREASED
   AT MOST AIRPORTS SINCE
   DEREGULATION
---------------------------------------------------------- Chapter 3:1

The total number of scheduled commercial departures, which is an
important measure of the amount of air service at an airport, has
increased for all three airport groups in our sample (see fig.  3.1). 
Specifically, in May 1995 small-community airports as a group had 50
percent more scheduled commercial departures than they did in May
1978; medium-sized-community airports had 57 percent more departures;
and large-community airports had 68 percent more departures. 

   Figure 3.1:  Total Scheduled
   Commercial Departures at
   Airports Serving Small,
   Medium-Sized, and Large
   Communities, May 1978-May 1995

   (See figure in printed
   edition.)

Note:  Data include scheduled departures for large airlines, commuter
carriers, and air taxis. 

Source:  Illustration based on GAO's analysis of data in the Official
Airline Guide (OAG). 

Within each of the three airport groups, a substantial majority of
airports had more scheduled commercial departures in May 1995 than in
May 1978.  Seventy-eight percent of the small- and
medium-sized-community airports had an increase in the number of
departures, and every large-community airport in our sample had more
departures. 

A second measure of the quantity of air service--the number of
available seats--has also increased since deregulation for all three
airport groups.  (App.  IV provides data on departures and available
seats for each airport.) However, because of the increased use of
smaller, turboprop aircraft, the percentage change in available seats
has been less than the percentage change in the number of departures,
especially at small- and medium-sized-community airports.  (See fig
3.2.)

   Figure 3.2:  Comparison of
   Percentage Change in Number of
   Scheduled Departures and
   Available Seats at Airports
   Serving Small, Medium-Sized,
   and Large Communities, May
   1978-May 1995

   (See figure in printed
   edition.)

Source:  Illustration based on GAO's analysis of OAG data. 

In addition, because of the substitution of turboprops for jets, many
small- and medium-sized-community airports have experienced a
decrease in the number of available seats even though the number of
departures increased.  For example, because the average aircraft size
per departure at Fargo, North Dakota's airport decreased from 106
seats in 1978 to 67 seats in 1995, Fargo had 21 percent fewer
available seats in May 1995 than in May 1978 even though the number
of departures increased by 25 percent. 

Nevertheless, as table 3.1 shows, when both measures are considered,
a plurality of the small- and medium-sized-community airports and
every large-community airport have experienced an increase in the
quantity of air service they receive. 



                               Table 3.1
                
                  Breakdown of Airports by Changes in
                Number of Departures and Available Seats
                Within Each Airport Group, May 1978-May
                                  1995

                                Increase            Decrease
                      Increase        in  Decrease        in
                            in  departur        in  departur
                      departur    es and  departur    es and
                        es and  decrease    es and  increase
Size of community        seats  in seats     seats  in seats     Total
--------------------  --------  --------  --------  --------  --------
Small                       20        17        10         2        49
Medium                      18        13         7         0        38
Large                       25         0         0         0        25
Total                       63        30        17         2       112
----------------------------------------------------------------------
Source:  GAO's analysis of OAG data. 

The airports that have experienced an increase in the quantity of air
service are located throughout the country.  Large communities in
particular have experienced an increase in service quantity, in part
because of their relatively strong economic growth during this
period.  For example, between 1979 and 1993, the average annual
income growth for the large communities was 2.2 percent, compared
with 1.8 percent for both the small and medium-sized communities in
our sample.  On the other hand, the 17 airports that have experienced
an decrease in both departures and seats are primarily small- and
medium-sized-community airports located in the Upper Midwest, where
economic growth has been slower.  Figure 3.3 demonstrates the
widespread increase in service quantity since deregulation and
identifies where the sharpest decline in air service--a decline of at
least 20 percent--has occurred.  The three communities whose airports
have experienced the sharpest declines--Sioux Falls, South Dakota;
Lincoln, Nebraska; and Rochester, Minnesota--had relatively slow
economic growth during this period.  For these three communities, the
average annual growth rate was only 0.4 percent in population, 1.3
percent in personal income, and 1.4 percent in employment. 

   Figure 3.3:  Airports for Which
   Number of Both Departures and
   Seats Increased or Decreased by
   20 Percent, May 1978-May 1995

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of OAG data.

   (See figure in printed
   edition.)


   THE QUALITY OF AIR SERVICE HAS
   IMPROVED FOR LARGE COMMUNITIES,
   BUT INDICATORS ARE MIXED FOR
   SMALL AND MEDIUM-SIZED
   COMMUNITIES
---------------------------------------------------------- Chapter 3:2

The quality of air service a community receives is generally measured
by four variables:  the number of (1) departures and available seats,
(2) destinations served by nonstop flights, (3) destinations served
by one-stop flights and the efficiency of the connecting service, and
(4) jet departures compared with the number of turboprop departures. 
Largely because of their central role in hub-and-spoke networks,
large-community airports have experienced a substantial increase in
the number of departures and cities served via nonstop flights since
deregulation, a corresponding decrease in the number of cities served
by one-stop flights, and only a slight decline in the share of
departures involving jets.  For small- and medium-sized-community
airports, hub-and-spoke networks have resulted in more departures and
more and better one-stop service.  However, because much of this
service is to hubs via turboprops, small and medium-sized communities
have fewer destinations served by nonstop flights and relatively less
jet service.  In light of this mixed record, it is difficult to judge
the overall change in the quality of air service at airports serving
small and medium-sized communities because such an assessment
requires, among other things, a subjective weighting of the relative
importance of the four variables. 


      BECAUSE OF GREATER RELIANCE
      ON HUBS, SMALL AND
      MEDIUM-SIZED COMMUNITIES
      HAVE LESS NONSTOP SERVICE
      BUT BETTER ONE-STOP SERVICE
-------------------------------------------------------- Chapter 3:2.1

As discussed earlier, the number of departures has increased since
deregulation at airports serving small and medium-sized communities. 
However, airlines have generally directed these departures to hub
airports, often eliminating nonstop service to other small and
medium-sized communities.  Overall, we found that the average number
of cities served by nonstop flights has declined by 7 percent from
small-community airports and by 2 percent from medium-sized community
airports (see fig.  3.4).  However, because more flights from these
airports are destined for hubs, the number of destinations served on
a one-stop basis has increased by 9 percent at small-community
airports and by 26 percent at medium-sized-community airports.\20 As
figure 3.4 also shows, large-community airports, many of which serve
as hubs, have experienced a sizable increase since deregulation in
the number of nonstop destinations.  As a result, large communities'
need for one-stop service has decreased. 

   Figure 3.4:  Percentage Change
   in Number of Destinations
   Served by Nonstop and One-Stop
   Flights From Airports Serving
   Small, Medium-Sized, and Large
   Communities, May 1978-May 1995

   (See figure in printed
   edition.)

Source:  Illustration based on GAO's analysis of OAG data. 

The number of nonstop destinations has decreased at many airports
serving small and medium-sized communities:  55 percent of the
small-community airports and 42 percent of the medium-sized-community
airports have experienced decreases.  As figure 3.5 shows, the small-
and medium-sized-community airports experiencing the sharpest decline
in nonstop destinations were primarily located in the slower-growing
Upper Midwest and Southeast.  In some cases, the communities served
by these airports have contracted.  For example, Moline, Illinois'
average annual change in population between 1979 and 1993 was -0.5
and Bristol, Tennessee's was -0.1.  By contrast, those airports
experiencing the largest increases in the number of nonstop
destinations are located primarily in fast-growing cities in the
Southwest and Florida as well as in Upper New England, such as
Burlington, Vermont. 

   Figure 3.5:  Small- and
   Medium-Sized-Community Airports
   for Which the Number of
   Destinations Served by Nonstop
   Flights Increased or Decreased
   by More Than 30 Percent, May
   1978-May 1995

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of OAG data.

   (See figure in printed
   edition.)

For many small and medium-sized communities, the decline in nonstop
service options has been substantial.  For example, as shown in
figure 3.6, the number of cities served nonstop from Fayetteville,
North Carolina, decreased by 78 percent, from nine in May 1978 to two
in May 1995. 

   Figure 3.6:  Cities Served by
   Nonstop Flights From
   Fayetteville, North Carolina,
   May 1978 and May 1995

   (See figure in printed
   edition.)

Source:  Illustration based on GAO's analysis of OAG data. 

Nevertheless, most communities that experienced a decline in the
number of nonstop destinations experienced an increase in the number
of one-stop destinations.  This increase largely occurred because the
remaining cities served on a nonstop basis are often hubs for the
major airlines, thereby yielding a significant increase both in the
number of connections possible and the efficiency of that service. 
For example, the two destinations served nonstop from Fayetteville in
1995--Atlanta and Charlotte--are hub airports for Delta and USAir,
respectively.  As a result, the number of destinations served on a
one-stop basis from Fayetteville, as listed in the OAG, increased by
60 percent between May 1978 and May 1995. 

Moreover, we found that passengers flying from places like
Fayetteville were better connected to the entire domestic aviation
system in 1995 than they were in 1978.  For example, travelers from
Fayetteville had an average of nine daily flights to Atlanta and six
daily flights to Charlotte in May 1995, compared with three daily
flights to Atlanta and one daily flight to Charlotte in May 1978. 
This increased frequency of service expands passengers' choices and
reduces layover times between connections.  As figure 3.7
illustrates, a traveler from Fayetteville wanting to fly to San
Francisco in 1978 had no other choice but to fly through Atlanta. 
The passenger could take a morning, noon, or mid-afternoon flight
from Fayetteville to Atlanta and then take one of two flights from
Atlanta to San Francisco.  However, because the first flight from
Fayetteville to Atlanta did not arrive until 9:27 a.m.  and both
flights from Atlanta to San Francisco were in the morning (the first
flight leaving at 8:46 a.m.  and the second at 10:25 a.m.), the
passenger had only one real connection option.  Otherwise, the person
had to spend the night in Atlanta to catch the next morning's flight
to San Francisco at 8:46 a.m. 

In 1995, that same traveler from Fayetteville could fly to San
Francisco via either Atlanta or Charlotte.  The passenger would have
the choice of nine daily flights to Atlanta connecting to six daily
flights to San Francisco or six daily flights to Charlotte connecting
to three daily flights to San Francisco (see fig.  3.7).  For
example, the passenger could take a flight from Fayetteville to
Atlanta that arrives at 7:25 a.m.  and connect to a flight to San
Francisco that leaves Atlanta at 8:20 a.m.  Because of the increased
service frequency, during any given day in May 1995 the passenger
would have six real connection options at Atlanta, with an average
layover time of 82 minutes.  The passenger also had the option of
taking one of two night flights from Fayetteville to Atlanta,
spending the night in Atlanta, and catching the next morning's flight
to San Francisco at 8:20 a.m. 

   Figure 3.7:  Comparison of
   One-Stop Connection
   Possibilities to San Francisco,
   California, for Travelers from
   Fayetteville, North Carolina,
   May 1978 and May 1995

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of OAG data.

   (See figure in printed
   edition.)

Finally, as figure 3.8 shows, Fayetteville's access to the domestic
system has been expanded in terms of the geographic location of the
cities accessible through one-stop service.  For example, in 1978
Fayetteville had possible one-stop connecting service to six
different cities in West Virginia but no such service to such larger
cities as San Diego, California; Salt Lake City, Utah; and Seattle,
Washington; or such preferred vacation locations as Honolulu, Hawaii,
or St.  Thomas, Virgin Islands.  As a result of the hub-and-spoke
system, Fayetteville in 1995 had one-stop service to those cities as
well as one-stop service to four cities in West Virginia. 

   Figure 3.8:  Change in Number
   of Cities Accessible on a
   One-Stop Basis From
   Fayetteville, North Carolina,
   Between May 1978 and May 1995

   (See figure in printed
   edition.)

   Note:  Shaded dots represent
   new one-stop cities.

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of OAG data.

   (See figure in printed
   edition.)


--------------------
\20 App.  V provides the number of nonstop and one-stop destinations
served from each airport as listed in the OAG for May 1978 and May
1995. 


      PROPORTION OF FLIGHTS
      INVOLVING JETS HAS DECREASED
      FOR SMALL AND MEDIUM-SIZED
      COMMUNITIES
-------------------------------------------------------- Chapter 3:2.2

While the number of jet departures has declined slightly at
small-community airports and increased slightly at medium-sized-
community airports, the proportion of departures involving jets has
fallen substantially for both groups since deregulation, as shown in
fig.  3.9.  At small-community airports, the percentage of departures
involving jets fell from 66 percent in May 1978 (21,632 of 32,744
total departures) to 39 percent in May 1995 (18,968 of 48,960 total
departures).  As a result, the growth in turboprop departures
accounted for all of the growth in total departures since
deregulation at the small-community airports that we reviewed.  At
airports serving medium-sized communities, the percentage of
departures involving jets fell from 77 percent in May 1978 (31,126 of
40,561 total departures) to 56 percent in May 1995 (35,554 of 63,854
total departures).  By comparison, at large-community airports, the
number of jet departures increased by 47 percent, although with the
growing use of turboprops the share of departures involving jets
actually fell from 81 percent of all departures in May 1978 to 71
percent in May 1995.\21

   Figure 3.9:  Jet and Turboprop
   Departures at Airports Serving
   Small and Medium-Sized
   Communities, May 1978-May 1995

   (See figure in printed
   edition.)

Source:  Illustration based on GAO's analysis of OAG data. 

We found that the substantial growth in the use of turboprops since
deregulation has occurred at airports serving small and medium-sized
communities in all regions of the country.  Two factors have caused
this trend.  First, large airlines have used turboprops to link small
and medium-sized communities to their major hubs.  Airlines would be
unable to earn a profit on many of these routes if they deployed
jets, which are larger and more costly to operate than turboprops. 
Second, since 1978 the commuter and air taxi segments of the industry
have grown significantly.\22 Commuters, in particular, have emerged
as (1) affiliates of the large airlines to "feed" traffic traveling
from small and medium-sized communities to the airlines' hubs and (2)
key providers of air service between small and medium-sized
communities. 

DOT's data on total departures in 1978 and 1994 by large airlines at
the airports in our sample and FAA's estimates of commuter and air
taxi departures at those airports demonstrate the growth of the
commuter and air taxi segments of the industry.  Our analysis of
these data shows that commuter carriers and air taxis accounted for
56 percent of departures at small-community airports in 1994,
compared with 29 percent in 1978.  At medium-sized-community
airports, commuter carriers and air taxis accounted for 47 percent of
departures in 1994, compared with 25 percent in 1978.  Finally, at
large-community airports, commuter carriers and air taxis accounted
for 27 percent of departures in 1994, compared with 18 percent in
1978. 


--------------------
\21 App.  VI provides the number of jet and turboprop departures from
each airport in our sample in May 1978 and May 1995. 

\22 As of November 1995, over 95 percent of the commuter fleet and
100 percent of the air taxi fleet was made up of turboprops. 


      MIXED RECORD MAKES IT
      DIFFICULT TO JUDGE OVERALL
      CHANGES IN SERVICE QUALITY
      FOR SMALL- AND MEDIUM-SIZED
      COMMUNITIES
-------------------------------------------------------- Chapter 3:2.3

In evaluating overall changes in the quality of air service to small
and medium-sized communities since deregulation, the increased
service frequency and one-stop options must be weighed against the
decline in jet service and nonstop options.  While the substantial
gains in quantity and nonstop destinations for large-community
airports clearly outweigh the corresponding decline in one-stop
service and slight decrease in jet service relative to turboprops,
weighting the changes experienced by small and medium-sized
communities is more problematic for two reasons. 

First, the value placed on each factor depends on a subjective
determination that will vary by individual.  For example, DOT
analysts we interviewed stated that in their view the number of
departures was the most important factor because the increase in
flight frequency saves travelers time and increases their possible
connections.  These analysts noted that they believed that the type
of aircraft was the least important factor, largely because the size
and safety of turboprops and the service they provide have improved
dramatically over the last 17 years.  Thus, they believe that
turboprops provide a level of service equivalent in many cases to
that of jets.  Other industry analysts that we interviewed, however,
considered the loss of nonstop service to be the most important
change. 

Second, it is not possible to convert each factor into a common
measure, such as total travel time.  Although most of the factors can
be measured in terms of travel time, one cannot:  the perceived
levels of amenities and comfort that travelers associate with the
different types of turboprops and jets.  As a result, developing a
formula that combines the various factors to produce a single,
objective "quality score" is problematic.  The only such formula that
we identified during our review was developed in the 1960s by the
Civil Aeronautics Board (CAB).  The CAB's formula was weighted
heavily toward changes in the number of departures and did not
account for passengers' perceptions of the service quality associated
with the various types of jets and turboprops.  In providing us with
this formula, DOT analysts emphasized that it has never been updated
and should not be used to gauge changes in service quality since
deregulation.  We therefore declined to use it and did not attempt to
develop a new formula during our review. 

Nevertheless, when considering those airports in our sample that had
either (1) lower fares and positive changes in every quality
dimension or (2) higher fares and negative changes in every quality
dimension, clear geographical differences emerge.  In particular, as
figure 3.10 shows, fast-growing communities of all sizes in the West,
Southwest, Upper New England, and Florida have lower fares and better
service.  Nevertheless, as figure 3.10 also shows, some small and
medium-sized communities in the Southeast and Upper Midwest are
clearly worse off today.  These pockets of higher fares and worse
service stem largely from both a lack of competition and
comparatively slow economic growth over the past two decades.  (App. 
I provides an overall summary of the changes in fares and service at
each airport in our sample.)

   Figure 3.10:  Communities That
   Have Experienced Lower Fares
   and Better Service or Higher
   Fares and Worse Service Since
   Deregulation

   (See figure in printed
   edition.)

   Note:  We also included several
   large community airports that
   had lower fares and better
   service in all dimensions
   except one-stop service.  We
   did this because in these cases
   the decline in the number of
   one-stop destinations
   corresponded to a gain in the
   number of nonstop destinations
   for that community.

   (See figure in printed
   edition.)

   Source:  Illustration based on
   GAO's analysis of data from
   DOT's O&D Survey and OAG.

   (See figure in printed
   edition.)


   SAFETY HAS IMPROVED SINCE
   DEREGULATION FOR COMMUNITIES OF
   ALL SIZES, BUT COMPARISONS
   BETWEEN AIRPORT GROUPS ARE
   PROBLEMATIC
---------------------------------------------------------- Chapter 3:3

In general, the long-term decline in the rate of accidents has
continued since deregulation.  These safety gains are attributed to
advances in aircraft technology and improved pilot training in the
early and mid-1980s, especially for turboprops and commuter carriers. 
As noted in chapter 1, the overall accident rate for commuters has
fallen by over 90 percent since deregulation.  In our sample, the
rate of accidents at the airports in each group was lower in 1994
than in 1978.  At small-community airports, the rate fell from 0.47
accidents per 100,000 departures to 0.14 accidents per 100,000
departures in 1994.  At medium-sized-community airports, the rate
fell from 1.29 accidents per 100,000 departures in 1978 to 0.00 in
1994.  At large-community airports, the rate fell from 0.41 accidents
per 100,000 departures to 0.14 in 1994.  However, because there are
so few accidents each year, an increase of just one or two accidents
in a given year can cause a significant fluctuation in the accident
rates, as figure 3.11 shows. 

   Figure 3.11:  Accident Rates
   for Airports Serving Small,
   Medium-Sized, and Large
   Communities, 1978-94

   (See figure in printed
   edition.)

Note:  Data for 1978 are fiscal-year data. 

Source:  Illustration based on GAO's analysis of NTSB and FAA data. 

Attempts to discern trends between the airport groups by smoothing
the data--employing, for example, such common practices as
calculating a 3-year moving average--did not help to identify any
trends.  Our analysis of accidents on routes to and from the airports
in our sample were similarly inconclusive.  Thus, while commuter
carriers and turboprops generally do not have as good a safety record
as the larger jets they replaced in many markets serving small and
medium-sized communities, it is difficult to discern the impact of
the change on relative safety at the airports in our sample because
of the small number of annual accidents and the consequent wide swing
in rates from year to year. 


   AGENCY COMMENTS AND OUR
   RESPONSE
---------------------------------------------------------- Chapter 3:4

We discussed a draft of this report with senior DOT officials,
including the Director, Office of Aviation and International
Economics.  They agreed with our findings concerning the trends in
airfares, service, and safety and stated that the report provides
useful information.  They also noted that the 112 airports in our
sample account for a sizable majority of the nation's air travelers. 
These officials commented, however, that the small-community airports
in our sample represented the larger "small" airports in the United
States and therefore were not completely representative of the
nation's smallest airports.  They stated that they have recently
completed a study, which they expect to issue soon, on the trends in
fares and service at the smallest airports and that the conclusions
of their study are consistent with our findings.  They noted that
although the airports included in their study account for only about
3 percent of the total passenger enplanements in the United States,
they believe that it provides a valuable and necessary complement to
our report because it focuses on the very smallest airports. 

We agree that DOT's study could serve as a valuable complement to our
report.  As we state in appendix VII, we examined data on the same
112 airports that we examined in our 1990 report in order to provide
consistent, comparable information in updating that report.  In
selecting those airports, one of our criteria was that the airport
had to be among the largest 175 in the nation.  This criterion was
necessary because as an airport's traffic level falls, the number of
tickets from that airport listed in DOT's O&D Survey also declines. 
A smaller number of tickets increases the potential for sampling
error, leaving the true change in fares uncertain.  As a result, we
excluded the airports serving the nation's smallest communities. 


OVERALL CHANGES IN FARES AND
SERVICE SINCE DEREGULATION AT
AIRPORTS SERVING SMALL,
MEDIUM-SIZED, AND LARGE
COMMUNITIES, AS OF 1994
=========================================================== Appendix I

                                                    More
               Lower        More                 nonstop        More
               fares  departures  More seats     options   one-stops   More jets
--------  ----------  ----------  ----------  ----------  ----------  ----------
Small-community airports
--------------------------------------------------------------------------------
Amarillo         Yes          No          No          No          No          No
 (TX)
Appleton          No         Yes         Yes         Yes         Yes         Yes
 (WI)
Ashevill         Yes          No          No          No          No          No
 e (NC)
Kalamazo         Yes         Yes         Yes         Yes          No         Yes
 o
 County
 (MI)
Binghamt         Yes          No         Yes          No         Yes         Yes
 on (NY)
Bangor           Yes         Yes         Yes          No          No          No
 (ME)
Billings         Yes         Yes          No          No          No          No
 (MT)
Bismarck         Yes         Yes          No          No          No          No
 (ND)
Boise            Yes         Yes         Yes          No         Yes         Yes
 (ID)
Burlingt         Yes         Yes         Yes         Yes         Yes         Yes
 on (VT)
Cedar             No         Yes         Yes          No          No          No
 Rapids
 (IA)
Champaig         Yes         Yes          No         Yes         Yes          No
 n (IL)
Charlest          No         Yes          No          No          No          No
 on (WV)
Duluth           Yes          No          No          No          No          No
 (MN)
Elmira/           No         Yes          No         Yes          No         Yes
 Corning
 (NY)
Erie              No         Yes          No          No          No          No
 (PA)
Eugene           Yes         Yes         Yes          No          No          No
 (OR)
Evansvil          No         Yes          No         Yes         Yes          No
 le (IN)
Fargo            Yes         Yes          No          No         Yes          No
 (ND)
Fayettev         Yes          No          No          No         Yes          No
 ille
 (NC)
Sioux            Yes          No          No          No         Yes         Yes
 Falls
 (SD)
Grand            Yes         Yes          No          No          No          No
 Junction
 (CO)
Gainesvi          No         Yes          No         Yes         Yes          No
 lle
 (FL)
Green             No          No          No          No         Yes          No
 Bay
 (WI)
Great            Yes         Yes          No         Yes          No          No
 Falls
 (MT)
Harlinge         Yes         Yes         Yes          No         Yes         Yes
 n (TX)
Huntsvil          No         Yes         Yes          No         Yes          No
 le (AL)
Wilmingt         Yes         Yes          No          No         Yes         Yes
 on (NC)
Lubbock          Yes         Yes          No          No          No          No
 (TX)
Lafayett         Yes          No          No          No          No          No
 e (LA)
Lincoln          Yes          No          No          No          No          No
 (NB)
Midland          Yes         Yes         Yes          No          No          No
 (TX)
Montgome          No         Yes          No          No          No          No
 ry (AL)
Manchest         Yes         Yes         Yes         Yes         Yes         Yes
 er (NH)
Missoula         Yes         Yes         Yes         Yes          No          No
 (MT)
Myrtle           Yes         Yes         Yes         Yes         Yes         Yes
 Beach
 (SC)
Pasco             \a          No         Yes          No          No          No
 (WA)
Portland         Yes         Yes         Yes         Yes         Yes         Yes
 (ME)
Rapid            Yes          No          No          No          No          No
 City
 (SD)
Reno             Yes         Yes         Yes         Yes         Yes         Yes
 (NV)
Roanoke          Yes         Yes          No          No          No          No
 (VA)
Rocheste          No          No          No          No          No          No
 r (MN)
Fort             Yes         Yes         Yes         Yes         Yes         Yes
 Myers
 (FL)
Savannah         Yes         Yes         Yes          No          No         Yes
 (GA)
South            Yes         Yes         Yes          No         Yes          No
 Bend
 (IN)
Springfi         Yes         Yes          No          No         Yes          No
 eld
 (MO)
Sarasota         Yes         Yes         Yes         Yes         Yes         Yes
 (FL)
Sioux            Yes         Yes          No          No          No          No
 City
 (IA)
Tallahas          No         Yes         Yes         Yes         Yes          No
 see
 (FL)
================================================================================
Overall          Yes         Yes         Yes          No         Yes          No

Medium-sized-community airports
--------------------------------------------------------------------------------
Albuquer         Yes         Yes         Yes         Yes         Yes         Yes
 que
 (NM)
Augusta           No          No          No          No          No          No
 (GA)
Bakersfi          \a         Yes          No          No          No          No
 eld
 (CA)
Baton            Yes         Yes         Yes         Yes          No          No
 Rouge
 (LA)
Columbia          No          No          No          No          No         Yes
 (SC)
Chattano          No         Yes          No          No          No          No
 oga
 (TN)
Charlest         Yes          No          No          No          No          No
 on (SC)
Colorado         Yes         Yes         Yes         Yes         Yes         Yes
 Springs
 (CO)
Corpus           Yes         Yes         Yes          No          No          No
 Christi
 (TX)
Daytona          Yes         Yes          No         Yes          No          No
 Beach
 (FL)
Des               No         Yes          No          No         Yes          No
 Moines
 (IA)
El Paso          Yes         Yes         Yes         Yes         Yes         Yes
 (TX)
Fresno           Yes         Yes          No         Yes          No          No
 (CA)
Flint             No         Yes          No          No          No          No
 (MI)
Fort              No         Yes         Yes         Yes         Yes          No
 Wayne
 (IN)
Spokane          Yes         Yes         Yes          No         Yes         Yes
 (WA)
Greenvil          \a         Yes         Yes          No         Yes         Yes
 le (SC)
Wichita          Yes         Yes          No          No          No          No
 (KS)
Jackson           No         Yes          No          No          No          No
 (MS)
Lansing           \a         Yes          No         Yes         Yes          No
 (MI)
Las              Yes         Yes         Yes         Yes         Yes         Yes
 Vegas
 (NV)
Lexingto          No         Yes         Yes          No         Yes          No
 n (KY)
Little           Yes         Yes         Yes         Yes         Yes         Yes
 Rock
 (AR)
Saginaw/          No         Yes          No          No         Yes          No
 Midland
 (MI)
Harrisbu         Yes         Yes         Yes         Yes         Yes         Yes
 rg (PA)
McAllen/         Yes         Yes         Yes          No         Yes         Yes
 Mission
 (TX)
Melbourn         Yes         Yes         Yes         Yes         Yes          No
 e (FL)
Moline            No          No          No          No          No          No
 (IL)
Mobile            No         Yes          No         Yes          No          No
 (AL)
Monterey          No         Yes          No          No         Yes          No
 (CA)
Madison           \a          No          No          No          No          No
 (WI)
Peoria           Yes          No          No          No          No          No
 (IL)
Pensacol         Yes         Yes         Yes         Yes         Yes         Yes
 a (FL)
Santa            Yes         Yes         Yes         Yes          No          No
 Barbara
 (CA)
Shrevepo          \a          No          No          No          No          No
 rt (LA)
Bristol/          No         Yes          No          No          No          No
 Kingspo
 rt (TN)
Tucson           Yes         Yes         Yes         Yes         Yes         Yes
 (AZ)
Knoxvill          No         Yes         Yes          No          No          No
 e (TN)
================================================================================
Overall          Yes         Yes         Yes          No         Yes         Yes

Large-community airports
--------------------------------------------------------------------------------
Atlanta           No         Yes         Yes         Yes          No         Yes
 (GA)
Boston           Yes         Yes         Yes         Yes          No         Yes
 (MA)
Clevelan         Yes         Yes         Yes         Yes          No         Yes
 d (OH)
Washingt         Yes         Yes         Yes          No          No         Yes
 on
 Nationa
 l
 (D.C.)
Denver           Yes         Yes         Yes         Yes          No         Yes
 (CO)
Dallas/           No         Yes         Yes         Yes          No         Yes
 Fort
 Worth
 (TX)
Detroit           No         Yes         Yes         Yes          No         Yes
 (MI)
Newark           Yes         Yes         Yes         Yes          No         Yes
 (NJ)
Houston          Yes         Yes         Yes         Yes         Yes         Yes
 Hobby
 (TX)
Houston          Yes         Yes         Yes         Yes          No         Yes
 Interco
 ntinent
 al (TX)
New York         Yes         Yes         Yes          No          No          No
 JFK
 (NY)
Los              Yes         Yes         Yes         Yes          No         Yes
 Angeles
 (CA)
New York         Yes         Yes         Yes          No          No         Yes
 LaGuard
 ia (NY)
Kansas           Yes         Yes         Yes         Yes         Yes         Yes
 City
 (MO)
Miami            Yes         Yes         Yes         Yes          No         Yes
 (FL)
Minneapo          No         Yes         Yes         Yes         Yes         Yes
 lis
 (MN)
Chicago           No         Yes         Yes          No          No         Yes
 O'Hare
 (IL)
Philadel          No         Yes         Yes         Yes          No         Yes
 phia
 (PA)
Phoenix          Yes         Yes         Yes         Yes         Yes         Yes
 (AZ)
Pittsbur          No         Yes         Yes         Yes          No         Yes
 gh (PA)
San              Yes         Yes         Yes         Yes         Yes         Yes
 Diego
 (CA)
Seattle          Yes         Yes         Yes         Yes         Yes         Yes
 (WA)
San              Yes         Yes         Yes          No          No         Yes
 Francis
 co (CA)
St.              Yes         Yes         Yes         Yes          No         Yes
 Louis
 (MO)
Tampa            Yes         Yes         Yes         Yes         Yes          No
 (FL)
================================================================================
Overall          Yes         Yes         Yes         Yes          No         Yes
--------------------------------------------------------------------------------
\a We did not find a statistically significant increase or decrease
in fares from 1979 to 1994. 

Source:  GAO's analysis of data from DOT and OAG. 


FARE PER PASSENGER MILE AT
AIRPORTS SERVING SMALL,
MEDIUM-SIZED, AND LARGE
COMMUNITIES FOR 1979, 1984, 1988,
1991, AND 1994
========================================================== Appendix II


                                                              Percenta
                                                                    ge  Sampling
                                                               change,  error (+
                1979      1984      1988      1991      1994   1979-94     or -)
----------  --------  --------  --------  --------  --------  ========  ========
Small-community airports
--------------------------------------------------------------------------------
Amarillo        23.3      24.0      21.8      19.5      19.9     -14.8       1.1
 (TX)
Appleton        27.6      35.0      28.9      30.0      28.4       3.0       2.3
 (WI)
Asheville       27.9      34.8      26.4      28.1      22.7     -18.4       1.4
 (NC)
Kalamazoo       25.9      30.7      24.3      24.6      24.9      -3.6       1.4
 County
 (MI)
Binghamton      21.6      27.8      19.2      21.3      20.1      -7.0       1.9
 (NY)
Bangor          21.2      24.8      21.8      20.6      18.8     -11.4       1.3
 (ME)
Billings        23.5      27.5      20.9      20.7      20.4     -13.0       1.1
 (MT)
Bismarck        24.3      26.5      20.1      20.3      19.4     -20.4       1.6
 (ND)
Boise (ID)      20.8      26.3      20.1      21.5      19.0      -9.0       1.1
Burlington      21.7      23.9      17.2      18.9      18.9     -13.2       1.2
 (VT)
Cedar           20.9      25.5      20.4      19.3      21.8       4.3       1.2
 Rapids
 (IA)
Champaign       26.5      26.8      23.0      22.9      25.3      -4.2       2.0
 (IL)
Charleston      26.0      33.9      27.5      30.0      32.4      24.7       1.9
 (WV)
Duluth          24.3      27.4      19.8      22.3      20.9     -14.0       1.7
 (MN)
Elmira/         23.9      30.7      23.6      27.0      28.7      20.3       2.9
 Corning
 (NY)
Erie (PA)       24.3      33.0      22.9      25.2      26.5       9.1       1.8
Eugene          20.4      21.5      16.6      18.7      15.8     -22.4       1.7
 (OR)
Evansville      25.4      36.4      24.6      29.3      28.6      12.8       1.9
 (IN)
Fargo (ND)      23.0      26.8      20.1      21.7      19.1     -16.7       1.1
Fayettevil      25.3      26.0      23.2      21.7      24.3      -4.0       1.5
 le (NC)
Sioux           23.0      24.4      20.6      21.6      20.3     -11.7       1.1
 Falls
 (SD)
Grand           25.5      27.9      22.3      24.7      24.9      -2.4       2.3
 Junction
 (CO)
Gainesvill      23.4      31.5      23.1      25.6      25.9      10.8       5.4
 e (FL)
Green Bay       22.7      28.4      21.1      22.7      23.5       3.6       1.6
 (WI)
Great           21.7      24.1      17.7      18.1      18.5     -14.7       1.6
 Falls
 (MT)
Harlingen       21.2      19.1      20.6      16.8      16.9     -20.1       3.8
 (TX)
Huntsville      24.8      35.7      29.6      28.2      30.4      22.5       1.5
 (AL)
Wilmington      29.7      28.5      25.1      28.1      26.9      -9.5       1.9
 (NC)
Lubbock         26.2      24.2      17.3      18.0      20.7     -21.2       2.4
 (TX)
Lafayette       25.4      24.9      19.9      20.3      19.5     -23.2       1.3
 (LA)
Lincoln         20.9      24.0      18.6      20.0      19.1      -8.5       1.3
 (NB)
Midland         27.0      21.7      17.6      18.0      18.6     -31.1       1.5
 (TX)
Montgomery      24.0      35.4      30.2      28.5      29.7      23.6       1.5
 (AL)
Manchester      24.3      31.5      20.8      21.9      22.8      -6.4       2.0
 (NH)
Missoula        23.1      24.4      18.4      17.9      20.1     -13.1       2.5
 (MT)
Myrtle          28.6      32.9      27.5      27.6      26.0      -9.0       2.5
 Beach
 (SC)
Pasco (WA)      24.4      25.8      22.2      24.9      24.8       1.5       3.8
Portland        21.0      24.8      18.6      20.2      19.8      -5.8       1.0
 (ME)
Rapid City      24.8      28.4      22.2      21.2      21.6     -12.8       1.8
 (SD)
Reno (NV)       19.5      23.4      19.7      18.1      15.4     -21.1       0.9
Roanoke         26.3      31.8      24.9      27.5      23.3     -11.6       1.4
 (VA)
Rochester       22.5      28.1      20.0      25.7      23.6       4.9       2.2
 (MN)
Fort Myers      20.1      26.0      16.1      17.9      15.7     -21.8       0.8
 (FL)
Savannah        23.7      32.0      25.3      25.6      23.0      -2.9       1.2
 (GA)
South Bend      21.8      28.5      20.9      21.5      21.1      -3.4       1.3
 (IN)
Springfiel      23.2      25.2      20.6      22.5      20.6     -11.2       1.2
 d (MO)
Sarasota        20.6      26.4      17.3      19.1      16.6     -19.3       0.9
 (FL)
Sioux City      22.8      24.0      18.1      20.5      20.1     -11.8       2.4
 (IA)
Tallahasse      26.9      36.7      28.1      29.6      27.8       3.6       1.1
 e (FL)
================================================================================
Overall         23.0      27.2      20.8      21.7      21.0      -8.5       0.2

Medium-sized-community airports
--------------------------------------------------------------------------------
Albuquerqu      24.4      18.9      16.9      16.7      16.5     -32.4       0.4
 e (NM)
Augusta         23.5      33.3      29.9      28.1      29.7      26.3       1.6
 (GA)
Bakersfiel      20.9      24.4      20.4      20.6      20.9       0.3       3.3
 d (CA)
Baton           24.2      28.1      23.5      22.8      21.6     -10.7       0.9
 Rouge
 (LA)
Columbia        23.6      34.1      26.9      26.7      25.5       8.1       1.0
 (SC)
Chattanoog      25.6      37.1      32.4      32.5      32.3      26.2       1.4
 a (TN)
Charleston      23.4      32.8      24.7      25.9      22.3      -4.9       0.9
 (SC)
Colorado        25.7      19.3      19.3      19.8      19.6     -23.6       0.9
 Springs
 (CO)
Corpus          23.5      21.8      21.2      17.9      18.7     -20.3       0.8
 Christi
 (TX)
Daytona         21.2      28.0      18.8      20.8      18.7     -11.7       1.3
 Beach
 (FL)
Des Moines      20.9      24.3      20.0      19.5      22.8       9.3       0.9
 (IA)
El Paso         24.3      19.9      17.9      16.1      16.6     -31.5       0.6
 (TX)
Fresno          19.6      23.2      20.7      19.2      17.4     -11.4       1.2
 (CA)
Flint (MI)      21.1      23.4      17.7      19.2      22.9       8.1       2.1
Fort Wayne      21.9      29.9      23.7      24.6      22.8       4.2       1.1
 (IN)
Spokane         19.4      22.2      17.0      17.1      15.4     -20.6       1.0
 (WA)
Greenville      25.9      35.9      29.1      29.9      25.7      -0.4       0.9
 (SC)
Wichita         23.9      25.6      20.4      21.8      21.9      -8.4       0.9
 (KS)
Jackson         24.0      32.6      26.9      27.3      30.0      25.1       1.1
 (MS)
Lansing         21.4      27.1      19.2      20.2      21.1      -1.1       1.3
 (MI)
Las Vegas       22.5      21.3      16.8      16.3      15.3     -32.2       0.4
 (NV)
Lexington       24.6      34.6      27.6      28.9      28.7      16.6       1.2
 (KY)
Little          25.4      32.3      25.7      23.4      22.1     -12.8       0.6
 Rock (AR)
Saginaw/        20.3      31.2      22.2      22.6      22.3       9.5       1.4
 Midland
 (MI)
Harrisburg      22.3      28.4      21.8      23.2      21.4      -4.0       1.0
 (PA)
McAllen/        22.4      19.1      18.1      18.4      19.6     -12.8       2.0
 Mission
 (TX)
Melbourne       21.2      27.2      19.2      20.0      18.0     -14.8       1.3
 (FL)
Moline          20.9      26.1      20.6      20.0      21.3       2.3       1.1
 (IL)
Mobile          23.8      32.4      23.6      25.3      26.4      10.9       1.4
 (AL)
Monterey        19.3      25.8      22.3      21.0      21.2       9.9       2.4
 (CA)
Madison         21.9      25.4      20.9      21.3      21.7      -0.8       1.0
 (WI)
Peoria          23.8      27.3      21.8      20.5      22.2      -6.9       1.3
 (IL)
Pensacola       23.3      31.1      23.5      21.4      22.0      -5.6       1.1
 (FL)
Santa           19.2      23.6      18.6      18.9      18.7      -2.7       2.3
 Barbara
 (CA)
Shreveport      23.6      33.5      24.5      24.3      23.7       0.5       1.1
 (LA)
Bristol/        27.1      34.8      29.6      30.3      30.6      12.9       1.7
 Kingsport
 (TN)
Tucson          21.4      21.0      16.0      17.8      16.5     -22.7       0.6
 (AZ)
Knoxville       25.0      36.3      28.6      31.5      31.3      25.1       1.1
 (TN)
================================================================================
Overall         23.0      25.6      20.8      20.8      20.5     -10.9       0.2

Large-community airports
--------------------------------------------------------------------------------
Atlanta         23.7      34.7      30.2      31.6      25.0       5.6       0.3
 (GA)
Boston          19.6      21.3      18.7      20.1      18.7      -4.4       0.2
 (MA)
Cleveland       20.0      26.3      19.9      23.4      18.3      -8.7       0.3
 (OH)
Washington      24.3      26.1      23.4      25.0      23.6      -2.8       0.4
 National
 (D.C.)
Denver          21.1      19.8      21.3      23.4      20.3      -3.9       0.4
 (CO)
Dallas/         22.7      25.0      24.4      25.2      25.0      10.1       0.3
 Fort
 Worth
 (TX)
Detroit         20.2      23.4      18.1      20.8      21.3       5.3       0.3
 (MI)
Newark          20.5      20.0      18.5      21.6      17.5     -14.9       0.3
 (NJ)
Houston         22.3      19.3      19.6      17.9      16.0     -28.3       1.8
 Hobby
 (TX)
Houston         22.2      20.1      21.9      23.3      21.1      -4.7       0.3
 Intercont
 inental
 (TX)
New York        15.6      17.9      14.3      13.4      12.7     -18.7       0.4
 JFK (NY)
Los             17.4      18.1      15.1      14.6      14.0     -19.2       0.3
 Angeles
 (CA)
New York        22.7      23.6      21.9      24.4      21.4      -5.8       0.3
 LaGuardia
 (NY)
Kansas          22.0      21.5      16.5      18.3      16.5     -25.1       0.3
 City (MO)
Miami (FL)      18.0      20.0      16.1      16.9      15.9     -11.7       0.4
Minneapoli      21.3      24.2      21.3      24.5      25.0      17.4       0.4
 s (MN)
Chicago         20.8      26.9      22.7      23.3      21.1       1.2       0.3
 O'Hare
 (IL)
Philadelph      20.2      23.7      20.9      22.0      20.4       1.0       0.3
 ia (PA)
Phoenix         22.3      18.5      14.6      14.6      15.0     -32.4       0.2
 (AZ)
Pittsburgh      21.2      28.4      22.1      26.1      25.7      21.4       0.5
 (PA)
San Diego       18.6      18.0      14.9      14.6      14.1     -24.1       0.5
 (CA)
Seattle         18.2      18.8      14.9      15.5      13.3     -27.1       0.3
 (WA)
San             17.1      18.8      15.7      15.2      14.3     -16.0       0.4
 Francisco
 (CA)
St. Louis       22.7      27.7      23.3      21.8      19.7     -13.2       0.3
 (MO)
Tampa (FL)      19.9      22.7      19.0      20.3      16.6     -16.5       0.4
================================================================================
Overall         20.2      22.1      19.2      20.3      18.5      -8.3       0.1
--------------------------------------------------------------------------------
Note:  App.  III provides the sampling error for each specific fare
estimate. 

Source:  GAO's analysis of DOT's O&D Survey. 


SAMPLING ERRORS FOR ESTIMATES OF
FARES PER PASSENGER MILE FOR 1979,
1984, 1988, 1991, AND 1994
========================================================= Appendix III


            1979 (+ or -  1984 (+ or -  1988 (+ or -  1991 (+ or -  1994 (+ or -
                       )             )             )             )             )
----------  ------------  ------------  ------------  ------------  ------------
Small-community airports
--------------------------------------------------------------------------------
Amarillo            0.15          0.17          0.16          0.19          0.21
 (TX)
Appleton            0.49          0.51          0.54          0.35          0.37
 (WI)
Asheville           0.34          0.43          0.42          0.34          0.27
 (NC)
Kalamazoo           0.21          0.42          0.32          0.26          0.30
 County
 (MI)
Binghamton          0.23          0.36          0.31          0.36          0.34
 (NY)
Bangor              0.21          0.25          0.34          0.34          0.21
 (ME)
Billings            0.18          0.22          0.25          0.26          0.23
 (MT)
Bismarck            0.35          0.25          0.28          0.31          0.29
 (ND)
Boise (ID)          0.17          0.22          0.23          0.37          0.17
Burlington          0.20          0.37          0.16          0.18          0.20
 (VT)
Cedar               0.18          0.23          0.21          0.16          0.18
 Rapids
 (IA)
Champaign           0.28          0.27          0.33          0.28          0.47
 (IL)
Charleston          0.19          0.31          0.38          0.38          0.44
 (WV)
Duluth              0.23          0.33          0.35          0.35          0.35
 (MN)
Elmira/             0.31          0.39          0.51          0.48          0.58
 Corning
 (NY)
Erie (PA)           0.20          0.42          0.40          0.33          0.38
Eugene              0.39          0.21          0.24          0.25          0.22
 (OR)
Evansville          0.16          0.52          0.36          0.37          0.44
 (IN)
Fargo (ND)          0.20          0.22          0.24          0.27          0.21
Fayettevil          0.27          0.29          0.34          0.24          0.27
 le (NC)
Sioux               0.19          0.18          0.24          0.24          0.22
 Falls
 (SD)
Grand               0.44          0.39          0.38          0.43          0.43
 Junction
 (CO)
Gainesvill          0.20          0.36          0.35          0.39          1.25
 e (FL)
Green Bay           0.26          0.24          0.30          0.24          0.26
 (WI)
Great               0.25          0.28          0.30          0.27          0.27
 Falls
 (MT)
Harlingen           0.96          0.23          0.18          0.19          0.21
 (TX)
Huntsville          0.24          0.21          0.28          0.21          0.24
 (AL)
Wilmington          0.46          0.45          0.48          0.43          0.38
 (NC)
Lubbock             0.27          0.48          0.14          0.37          0.60
 (TX)
Lafayette           0.30          0.35          0.35          0.31          0.25
 (LA)
Lincoln             0.23          0.29          0.19          0.26          0.21
 (NB)
Midland             0.33          0.35          0.15          0.29          0.33
 (TX)
Montgomery          0.15          0.28          0.41          0.34          0.32
 (AL)
Manchester          0.43          0.87          0.31          0.22          0.27
 (NH)
Missoula            0.39          0.31          0.32          0.32          0.48
 (MT)
Myrtle              0.62          0.55          0.61          0.46          0.43
 Beach
 (SC)
Pasco (WA)          0.29          0.34          0.45          0.70          0.92
Portland            0.16          0.38          0.15          0.15          0.15
 (ME)
Rapid City          0.26          0.30          0.31          0.35          0.40
 (SD)
Reno (NV)           0.17          0.12          0.14          0.12          0.10
Roanoke             0.29          0.31          0.34          0.29          0.26
 (VA)
Rochester           0.26          0.41          0.35          0.43          0.41
 (MN)
Fort Myers          0.15          0.24          0.11          0.11          0.11
 (FL)
Savannah            0.17          0.24          0.30          0.24          0.22
 (GA)
South Bend          0.19          0.24          0.23          0.18          0.23
 (IN)
Springfiel          0.24          0.24          0.27          0.28          0.20
 d (MO)
Sarasota            0.15          0.23          0.13          0.14          0.14
 (FL)
Sioux City          0.36          0.71          0.28          0.44          0.46
 (IA)
Tallahasse          0.15          0.27          0.29          0.22          0.26
 e (FL)
================================================================================
Overall             0.04          0.05          0.04          0.04          0.04

Medium-sized-community airports
--------------------------------------------------------------------------------
Albuquerqu          0.11          0.06          0.06          0.08          0.06
 e (NM)
Augusta             0.18          0.26          0.43          0.30          0.31
 (GA)
Bakersfiel          0.37          0.61          0.43          0.30          0.59
 d (CA)
Baton               0.14          0.19          0.23          0.18          0.17
 Rouge
 (LA)
Columbia            0.14          0.20          0.26          0.20          0.19
 (SC)
Chattanoog          0.15          0.27          0.41          0.31          0.30
 a (TN)
Charleston          0.14          0.20          0.25          0.20          0.16
 (SC)
Colorado            0.26          0.13          0.12          0.14          0.13
 Springs
 (CO)
Corpus              0.15          0.15          0.18          0.17          0.16
 Christi
 (TX)
Daytona             0.19          0.37          0.22          0.23          0.21
 Beach
 (FL)
Des Moines          0.12          0.10          0.13          0.13          0.15
 (IA)
El Paso             0.17          0.13          0.07          0.07          0.07
 (TX)
Fresno              0.19          0.21          0.23          0.18          0.19
 (CA)
Flint (MI)          0.26          0.37          0.29          0.28          0.36
Fort Wayne          0.14          0.22          0.29          0.23          0.21
 (IN)
Spokane             0.14          0.15          0.15          0.17          0.16
 (WA)
Greenville          0.15          0.22          0.28          0.22          0.18
 (SC)
Wichita             0.18          0.12          0.14          0.16          0.15
 (KS)
Jackson             0.12          0.18          0.26          0.23          0.23
 (MS)
Lansing             0.17          0.29          0.25          0.20          0.21
 (MI)
Las Vegas           0.10          0.07          0.06          0.06          0.07
 (NV)
Lexington           0.14          0.21          0.30          0.24          0.25
 (KY)
Little              0.11          0.15          0.16          0.15          0.12
 Rock (AK)
Saginaw/            0.16          0.27          0.33          0.27          0.24
 Midland
 (MI)
Harrisburg          0.13          0.24          0.22          0.18          0.19
 (PA)
McAllen/            0.46          0.24          0.23          0.24          0.22
 Mission
 (TX)
Melbourne           0.19          0.31          0.23          0.24          0.23
 (FL)
Moline              0.13          0.21          0.23          0.18          0.18
 (IL)
Mobile              0.16          0.24          0.27          0.24          0.29
 (AL)
Monterey            0.27          0.26          0.43          0.27          0.39
 (CA)
Madison             0.14          0.14          0.19          0.23          0.16
 (WI)
Peoria              0.20          0.20          0.28          0.21          0.26
 (IL)
Pensacola           0.16          0.25          0.25          0.18          0.21
 (FL)
Santa               0.31          0.28          0.25          0.25          0.34
 Barbara
 (CA)
Shreveport          0.12          0.21          0.25          0.25          0.23
 (LA)
Bristol/            0.27          0.39          0.47          0.36          0.34
 Kingsport
 (TN)
Tucson              0.11          0.09          0.09          0.10          0.09
 (AZ)
Knoxville           0.13          0.27          0.27          0.21          0.21
 (TN)
================================================================================
Overall             0.03          0.03          0.03          0.03          0.03

Large-community airports
--------------------------------------------------------------------------------
Atlanta             0.04          0.06          0.08          0.06          0.05
 (GA)
Boston              0.03          0.04          0.04          0.04          0.04
 (MA)
Cleveland           0.05          0.07          0.07          0.07          0.05
 (OH)
Washington          0.07          0.06          0.07          0.06          0.06
 National
 (D.C.)
Denver              0.05          0.04          0.05          0.09          0.06
 (CO)
Dallas/             0.04          0.04          0.05          0.05          0.05
 Fort
 Worth
 (TX)
Detroit             0.04          0.08          0.05          0.05          0.05
 (MI)
Newark              0.06          0.04          0.04          0.04          0.03
 (NJ)
Houston             0.51          0.42          0.08          0.12          0.17
 Hobby
 (TX)
Houston             0.04          0.04          0.07          0.07          0.06
 Intercont
 inental
 (TX)
New York            0.06          0.06          0.05          0.05          0.05
 JFK (NY)
Los                 0.04          0.05          0.03          0.03          0.03
 Angeles
 (CA)
New York            0.06          0.04          0.05          0.05          0.04
 LaGuardia
 (NY)
Kansas              0.05          0.05          0.05          0.10          0.05
 City (MO)
Miami (FL)          0.04          0.05          0.05          0.05          0.06
Minneapoli          0.04          0.05          0.06          0.07          0.06
 s (MN)
Chicago             0.04          0.04          0.05          0.04          0.04
 O'Hare
 (IL)
Philadelph          0.04          0.04          0.06          0.05          0.04
 ia (PA)
Phoenix             0.06          0.04          0.03          0.04          0.04
 (AZ)
Pittsburgh          0.04          0.07          0.08          0.08          0.08
 (PA)
San Diego           0.10          0.05          0.04          0.05          0.05
 (CA)
Seattle             0.06          0.05          0.05          0.08          0.05
 (WA)
San                 0.05          0.04          0.04          0.05          0.04
 Francisco
 (CA)
St. Louis           0.05          0.07          0.08          0.07          0.05
 (MO)
Tampa (FL)          0.07          0.07          0.07          0.06          0.05
================================================================================
Overall             0.01          0.01          0.01          0.01          0.01
--------------------------------------------------------------------------------

NUMBER OF SCHEDULED DEPARTURES AND
SEATS AT SAMPLED AIRPORTS SERVING
SMALL-, MEDIUM-SIZED, AND LARGE
COMMUNITIES, MAY 1978-MAY 1995
========================================================== Appendix IV

                        Total       Total       Total       Total  Percentage  Percentage
                   departures  departures  seats, May  seats, May   change in      change
                   , May 1978  , May 1995        1978        1995  departures    in seats
-----------------  ----------  ----------  ----------  ----------  ==========  ==========
Small-community airports
-----------------------------------------------------------------------------------------
Amarillo (TX)             705         633      72,113      58,432       -10.2       -19.0
Appleton (WI)             482         801       9,158      36,128        66.2       294.5
Asheville (NC)            774         732      62,184      43,917        -5.4       -29.4
Kalamazoo County          480         908      36,277      52,049        89.2        43.5
 (MI)
Binghamton (NY)         1,051       1,013      29,527      38,226        -3.6        29.5
Bangor (ME)               579         926      33,800      39,431        59.9        16.7
Billings (MT)             836         982      78,386      69,298        17.5       -11.6
Bismarck (ND)             461         711      44,043      33,759        54.2       -23.3
Boise (ID)                978       2,360      90,470     171,384       141.3        89.4
Burlington (VT)           700       1,890      37,982      77,878       170.0       105.0
Cedar Rapids (IA)         716       1,224      65,283      69,123        70.9         5.9
Champaign (IL)            422         858      33,860      26,382       103.3       -22.1
Charleston (WV)           871       1,021      68,712      50,482        17.2       -26.5
Duluth (MN)               457         379      44,384      20,515       -17.1       -53.8
Elmira (NY)               371         392      18,821      18,042         5.7        -4.1
Erie (PA)                 321         347      28,393      23,164         8.1       -18.4
Eugene (OR)               587         942      41,245      46,657        60.5        13.1
Evansville (IN)           592       1,423      48,739      44,972       140.4        -7.7
Fargo (ND)                514         645      54,488      43,036        25.5       -21.0
Fayetteville (NC)         488         463      51,051      25,140        -5.1       -50.7
Sioux Falls (SD)          908         678      66,762      45,804       -25.3       -31.4
Grand Junction            360         679      24,166      20,916        88.6       -13.4
 (CO)
Gainesville (FL)          328         692      28,856      28,321       111.0        -1.8
Green Bay (WI)            987         926      86,360      50,514        -6.2       -41.5
Great Falls (MT)          395         483      43,004      39,213        22.3        -8.8
Harlingen (TX)            318         681      31,436      70,386       114.2       123.9
Huntsville (AL)           712         860      65,033      77,065        20.8        18.5
Wilmington (NC)           391         563      31,711      28,936        44.0        -8.7
Lubbock (TX)            1,082       1,099     107,235      95,229         1.6       -11.2
Lafayette (LA)            610         592      29,136      21,672        -3.0       -25.6
Lincoln (NB)              967         695      78,326      39,876       -28.1       -49.1
Midland (TX)              909         980      94,077      96,339         7.8         2.4
Montgomery (AL)           531         766      52,121      48,244        44.3        -7.4
Manchester (NH)           619       1,289      19,146      80,840       108.2       322.2
Missoula (MT)             248         510      29,698      34,964       105.6        17.7
Myrtle Beach (SC)         410         870      27,701      60,012       112.2       116.6
Pasco (WA)                846         838      32,778      33,795        -0.9         3.1
Portland (ME)             861       1,675      52,248      96,650        94.5        85.0
Rapid City (SD)           457         437      43,349      26,616        -4.4       -38.6
Reno (NV)               1,681       3,354     160,709     382,783        99.5       138.2
Roanoke (VA)            1,255       1,423     111,098      63,755        13.4       -42.6
Rochester (MN)            739         300      68,063      29,778       -59.4       -56.2
Fort Myers (FL)           507       2,210      48,429     213,255       335.9       340.3
Savannah (GA)             616         762      66,650      82,382        23.7        23.6
South Bend (IN)         1,006       1,368      54,173      73,009        36.0        34.8
Springfield (MO)          569       1,216      54,934      54,774       113.7        -0.3
Sarasota (FL)             778       1,437      78,830     115,510        84.7        46.5
Sioux City (IA)           616       1,009      47,304      26,615        63.8       -43.7
Tallahassee (FL)          653       1,918      56,840     103,616       193.7        82.3
=========================================================================================
Overall                32,744      48,960   2,639,089   3,046,502        49.5        15.4

Medium-sized-community airports
-----------------------------------------------------------------------------------------
Albuquerque (NM)        2,168       4,630     200,058     447,538       113.6       123.7
Augusta (GA)              627         589      62,507      39,641        -6.1       -36.6
Bakersfield (CA)          398         991      30,571      25,238       149.0       -17.4
Baton Rouge (LA)          711       1,135      67,079      77,533        59.6        15.6
Columbia (SC)           1,558         955     106,355     101,621       -38.7        -4.4
Chattanooga (TN)          763         830      80,509      47,870         8.8       -40.5
Charleston (SC)         1,120         941     112,485     108,072       -16.0        -3.9
Colorado Springs        1,065       1,226      73,277     130,358        15.1        77.9
 (CO)
Corpus Christi            838       1,029      59,072      70,562        22.8        19.4
 (TX)
Daytona Beach             635         715      76,357      63,268        12.6       -17.1
 (FL)
Des Moines (IA)         1,520       1,560     147,194     111,403         2.6       -24.3
El Paso (TX)            1,587       2,567     169,580     322,520        61.7        90.2
Fresno (CA)             1,114       2,613      93,867      79,858       134.6       -14.9
Flint (MI)                441         607      39,272      17,328        37.6       -55.9
Fort Wayne (IN)           800       1,192      62,971      65,041        49.0         3.3
Spokane (WA)            1,687       3,130     148,598     220,671        85.5        48.5
Greenville (SC)           724       1,449      69,483     110,106       100.1        58.5
Wichita (KS)            1,347       1,598     131,413     111,905        18.6       -14.8
Jackson (MS)            1,215       1,442     113,010      93,707        18.7       -17.1
Lansing (MI)              728       1,164      66,351      56,352        59.9       -15.1
Las Vegas (NV)          4,781      12,025     504,280   1,521,663       151.5       201.7
Lexington (KY)            709       1,324      72,153      90,537        87.0        25.5
Little Rock (AR)        1,466       2,359     132,555     213,086        60.9        60.8
Saginaw (MI)              503         593      49,878      44,027        17.9       -11.7
Harrisburg (PA)         1,217       1,566      56,397     120,818        28.6       114.2
McAllen (TX)              178         467      16,020      42,188       162.4       163.3
Melbourne (FL)            372         692      44,082      44,904        86.0         1.9
Moline (IL)               983         878      88,926      59,576       -10.7       -33.0
Mobile (AL)               852         859      84,355      76,825         0.8        -8.9
Monterey (CA)             405       1,165      41,343      38,671       187.6        -6.5
Madison (WI)            1,234       1,205     117,461      84,046        -2.3       -28.4
Peoria (IL)               863         858      77,697      39,996        -0.6       -48.5
Pensacola (FL)            364       1,883      43,955     110,479       417.3       151.3
Santa Barbara             782       1,694      36,912      57,873       116.6        56.8
 (CA)
Shreveport (LA)         1,399       1,348     135,214      75,464        -3.6       -44.2
Bristol (TN)              778         823      65,104      41,065         5.8       -36.9
Tucson (AZ)             1,630       1,986     167,022     224,521        21.8        34.4
Knoxville (TN)            999       1,456     100,017     111,286        45.7        11.3
=========================================================================================
Overall                40,561      63,854   3,754,122   5,318,123        57.4        41.7

Large-community airports
-----------------------------------------------------------------------------------------
Atlanta (GA)           20,397      28,512   2,572,539   3,450,058        39.8        34.1
Boston (MA)            10,023      16,037     915,009   1,388,962        60.0        51.8
Cleveland (OH)          5,253       8,288     562,089     762,207        57.8        35.6
Washington             10,524      10,758     989,939   1,198,268         2.2        21.0
 National (D.C.)
Denver (CO)            12,105      17,806   1,237,883   1,915,697        47.1        54.8
Dallas (TX)            15,117      33,285   1,628,184   3,617,888       120.2       122.2
Detroit (MI)            7,088      16,599     848,386   1,743,176       134.2       105.5
Newark (NJ)             5,889      14,236     672,297   1,599,474       141.7       137.9
Houston Hobby           1,457       5,434     135,080     646,109       273.0       378.3
 (TX)
Houston                 7,772      13,763     819,662   1,527,948        77.1        86.4
 Intercontinental
 (TX)
New York JFK (NY)       6,445       8,407     911,941     918,821        30.4         0.7
Los Angeles (CA)       15,467      26,437   2,123,927   2,742,623        70.9        29.1
New York               10,495      13,229   1,098,284   1,446,462        26.1        32.0
 LaGuardia (NY)
Kansas City (MO)        5,976       7,411     531,124     704,843        24.0        32.7
Miami (FL)              6,620      11,500     851,673   1,249,289        73.7        46.7
Minneapolis (MN)        5,944      16,147     690,937   1,623,772       171.6       135.0
Chicago O'Hare         26,772      32,871   3,163,510   3,854,441        22.8        21.8
 (IL)
Philadelphia (PA)       9,782      13,294     810,920   1,230,700        35.9        51.8
Phoenix (AZ)            4,217      15,832     470,034   1,923,889       275.4       309.3
Pittsburgh (PA)        10,260      16,560     830,352   1,459,255        61.4        75.7
San Diego (CA)          3,699       8,457     479,575     891,236       128.6        85.8
Seattle (WA)            5,931      13,283     641,926   1,391,609       124.0       116.9
San Francisco          10,804      15,411   1,423,889   1,836,621        42.6        29.0
 (CA)
St. Louis (MO)          8,855      19,766     875,540   1,931,205       123.2       120.6
Tampa (FL)              5,803       7,959     673,911     692,993        37.2         2.8
Overall               232,695     391,282  25,958,611  41,747,546        68.2        60.8
-----------------------------------------------------------------------------------------
Source:  GAO's analysis of OAG data. 


NUMBER OF DESTINATIONS SERVED BY
NONSTOP AND ONE-STOP FLIGHTS AT
SAMPLED AIRPORTS SERVING SMALL,
MEDIUM-SIZED, AND LARGE
COMMUNITIES, MAY 1978-MAY 1995
=========================================================== Appendix V

                             Nonstops,     Nonstops,    One-stops,    One-stops,
                              May 1978      May 1995      May 1978      May 1995
------------------------  ------------  ------------  ------------  ------------
Small-community airports
--------------------------------------------------------------------------------
Amarillo (TX)                       10             5            10             8
Appleton (WI)                        2             7             0             8
Asheville (NC)                      13             6            10            10
Kalamazoo County (MI)                4             7             6             6
Binghamton (NY)                     14            14             6            11
Bangor (ME)                          6             5             9             5
Billings (MT)                       16            14            16            16
Bismarck (ND)                        8             5            10             6
Boise (ID)                          16            16            15            19
Burlington (VT)                     12            17            13            18
Cedar Rapids (IA)                   11             8            13            13
Champaign (IL)                       6             8             4             6
Charleston (WV)                     15             9            15             9
Duluth (MN)                          6             4             8             7
Elmira/Corning (NY)                  5             6             8             5
Erie (PA)                            6             3             5             4
Eugene (OR)                          8             5             8             8
Evansville (IN)                     10            13             9            15
Fargo (ND)                           6             5             7             8
Fayetteville (NC)                    9             2             5             8
Sioux Falls (SD)                    16            10            14            16
Grand Junction (CO)                  7             6             8             2
Gainesville (FL)                     4             7             4             6
Green Bay (WI)                      11             8            11            13
Great Falls (MT)                     5             6             8             5
Harlingen (TX)                       5             5             3             5
Huntsville (AL)                     13             7            11            14
Wilmington (NC)                      7             3             6             7
Lubbock (TX)                        11             8            10             9
Lafayette (LA)                       7             4             5             1
Lincoln (NB)                        12             8            13            10
Midland (TX)                         9             8             9             9
Montgomery (AL)                      8             8            13             4
Manchester (NH)                      6            11             3            17
Missoula (MT)                        6             8             6             5
Myrtle Beach (SC)                    7             9             6            10
Pasco (WA)                          12             5            10             2
Portland (ME)                        9            11            11            19
Rapid City (SD)                      8             4             8             1
Reno (NV)                           14            21            16            19
Roanoke (VA)                        19            13            15            15
Rochester (MN)                       8             3            10             5
Fort Myers (FL)                      4            25             9            25
Savannah (GA)                        6             6            10             9
South Bend (IN)                     11             9             9            13
Springfield (MO)                     9             9             8             9
Sarasota (FL)                        7            14            11            17
Sioux City (IA)                     10             9             8             6
Tallahassee (FL)                     9            10            11            15
================================================================================
Average for small-                 9.0           8.4           9.0           9.8
 community airports

Medium-sized-community airports
--------------------------------------------------------------------------------
Albuquerque (NM)                    24            32            23            50
Augusta (GA)                         6             4             7             5
Bakersfield (CA)                     7             6             4             1
Baton Rouge (LA)                    10            11            10             5
Columbia (SC)                       18             7            15            13
Chattanooga (TN)                     9             5            10             8
Charleston (SC)                     10             8            16            16
Colorado Springs (CO)                6            10             5            26
Corpus Christi (TX)                  6             4            10             7
Daytona Beach (FL)                   6             8            11             9
Des Moines (IA)                     14            14            17            23
El Paso (TX)                        14            15            16            27
Fresno (CA)                         12            15             9             9
Flint (MI)                           6             6             6             4
Fort Wayne (IN)                      8             9             7            11
Spokane (WA)                        21            20            24            28
Greenville (SC)                     11            11            10            19
Wichita (KS)                        15            11            25            20
Jackson (MS)                        14            13            19             7
Lansing (MI)                         7            13            10            13
Las Vegas (NV)                      42            59            40            51
Lexington (KY)                      11            11            10            14
Little Rock (AK)                    15            17            18            28
Saginaw/Midland (MI)                 8             6             6            15
Harrisburg (PA)                     11            13             3            20
McAllen/Mission (TX)                 3             3             3            10
Melbourne (FL)                       4             5             9            10
Moline (IL)                         15             6            13             4
Mobile (AL)                          7            10            12             6
Monterey (CA)                        3             3             6             7
Madison (WI)                        14             8            15            14
Peoria (IL)                         12             5             8             1
Pensacola (FL)                       6            12             8            20
Santa Barbara (CA)                   6             7             9             6
Shreveport (LA)                     18            10            19             7
Bristol/Kingsport (TN)              15             7            13             9
Tucson (AZ)                         11            15            25            32
Knoxville (TN)                      18            15            15            15
================================================================================
Average for medium-               11.7          11.5          11.9          15.0
 sized-community
 airports

Large-community airports
--------------------------------------------------------------------------------
Atlanta (GA)                       106           119            99            84
Boston (MA)                         64            71            77            65
Cleveland (OH)                      49            52            49            45
Washington National                 71            58            90            52
 (D.C.)
Denver (CO)                         96           107           105            76
Dallas (TX)                         83           112            88            82
Detroit (MI)                        59            95            73            54
Newark (NJ)                         46            72            63            60
Houston Hobby (TX)                   8            24             4            37
Houston Intercontinental            48            71            53            54
 (TX)
New York JFK (NY)                   55            42            57            21
Los Angeles (CA)                    70            72            96            64
New York LaGuardia (NY)             74            64            90            62
Kansas City (MO)                    46            51            58            66
Miami (FL)                          43            50            61            48
Minneapolis/St. Paul                54           109            68            76
 (MN)
Chicago O'Hare (IL)                135           129           155            72
Philadelphia (PA)                   62            82            59            56
Phoenix (AZ)                        32            67            48            62
Pittsburgh (PA)                     68           112            53            35
San Diego (CA)                      26            36            40            46
Seattle (WA)                        38            55            54            59
San Francisco (CA)                  68            63            77            43
St. Louis (MO)                      67            96            73            67
Tampa (FL)                          41            50            38            51
================================================================================
Average for large-                60.3          74.3          69.5          57.5
 community airports
--------------------------------------------------------------------------------
Source:  GAO's analysis of OAG data. 


NUMBER OF SCHEDULED JET AND
NON-JET DEPARTURES AT SAMPLED
AIRPORTS SERVING SMALL,
MEDIUM-SIZED, AND LARGE
COMMUNITIES, MAY 1978-MAY 1995
========================================================== Appendix VI

                                   Jet           Jet       Non-jet       Non-jet
                           departures,   departures,   departures,   departures,
                              May 1978      May 1995      May 1978      May 1995
------------------------  ------------  ------------  ------------  ------------
Small-community airports
--------------------------------------------------------------------------------
Amarillo (TX)                      643           358            62           275
Appleton (WI)                        0           234           482           567
Asheville (NC)                     461           242           313           490
Kalamazoo County (MI)              217           221           263           687
Binghamton (NY)                     93           122           958           891
Bangor (ME)                        240           119           339           807
Billings (MT)                      620           455           216           527
Bismarck (ND)                      309           209           152           502
Boise (ID)                         806         1,536           172           824
Burlington (VT)                    302           339           398         1,551
Cedar Rapids (IA)                  627           452            89           772
Champaign (IL)                     302             0           120           858
Charleston (WV)                    542           289           329           732
Duluth (MN)                        368           155            89           224
Elmira/Corning (NY)                 62           120           309           272
Erie (PA)                          275           122            46           225
Eugene (OR)                        403           279           184           663
Evansville (IN)                    519            89            73         1,334
Fargo (ND)                         398           294           116           351
Fayetteville (NC)                  426           151            62           312
Sioux Falls (SD)                   393           456           515           222
Grand Junction (CO)                140             0           220           679
Gainesville (FL)                   236           120            92           572
Green Bay (WI)                     670           236           317           690
Great Falls (MT)                   372           275            23           208
Harlingen (TX)                     318           530             0           151
Huntsville (AL)                    712           640             0           220
Wilmington (NC)                    182           185           209           378
Lubbock (TX)                       974           549           108           550
Lafayette (LA)                     271             0           339           592
Lincoln (NB)                       600           331           367           364
Midland (TX)                       836           647            73           333
Montgomery (AL)                    531           212             0           554
Manchester (NH)                    178           522           441           767
Missoula (MT)                      248           247             0           263
Myrtle Beach (SC)                  155           390           255           480
Pasco (WA)                         248           122           598           716
Portland (ME)                      333           474           528         1,201
Rapid City (SD)                    372           217            85           220
Reno (NV)                        1,619         2,659            62           695
Roanoke (VA)                       732           298           523         1,125
Rochester (MN)                     561           300           178             0
Fort Myers (FL)                    341         1,407           166           803
Savannah (GA)                      461           592           155           170
South Bend (IN)                    403           292           603         1,076
Springfield (MO)                   538           182            31         1,034
Sarasota (FL)                      620           703           158           734
Sioux City (IA)                    368            62           248           947
Tallahassee (FL)                   607           534            46         1,384
================================================================================
Overall                         21,632        18,968        11,112        29,992

Medium-sized-community airports
--------------------------------------------------------------------------------
Albuquerque (NM)                 1,666         3,322           502         1,308
Augusta (GA)                       407           210           220           379
Bakersfield (CA)                   279            31           119           960
Baton Rouge (LA)                   596           393           115           742
Columbia (SC)                      744           761           814           194
Chattanooga (TN)                   763           299             0           531
Charleston (SC)                    848           773           272           168
Colorado Springs (C0)              453         1,064           612           162
Corpus Christi (TX)                503           356           335           673
Daytona Beach (FL)                 635           409             0           306
Des Moines (IA)                  1,354           871           166           689
El Paso (TX)                     1,367         2,513           220            54
Fresno (CA)                        625           184           489         2,429
Flint (MI)                         310            12           131           595
Fort Wayne (IN)                    527           292           273           900
Spokane (WA)                     1,240         1,803           447         1,327
Greenville (SC)                    631           777            93           672
Wichita (KS)                     1,015           835           332           763
Jackson (MS)                     1,038           428           177         1,014
Lansing (MI)                       523           217           205           947
Las Vegas (NV)                   4,030        10,619           751         1,406
Lexington (KY)                     620           599            89           725
Little Rock (AK)                 1,084         1,577           382           782
Saginaw/Midland (MI)               430           331            73           262
Harrisburg (PA)                    360           781           857           785
McAllen/Mission (TX)               178           363             0           104
Melbourne (FL)                     372           250             0           442
Moline (IL)                        805           395           178           483
Mobile (AL)                        852           445             0           414
Monterey (CA)                      405           119             0         1,046
Madison (WI)                     1,037           595           197           610
Peoria (IL)                        770            62            93           796
Pensacola (FL)                     364           574             0         1,309
Santa Barbara (CA)                 275           181           507         1,513
Shreveport (LA)                  1,185           390           214           958
Bristol/Kingsport(TN)              507           254           271           569
Tucson (AZ)                      1,453         1,658           177           328
Knoxville (TN)                     875           811           124           645
================================================================================
Overall                         31,126        35,554         9,435        28,300

Large-community airports
--------------------------------------------------------------------------------
Atlanta (GA)                    19,209        23,052         1,188         5,460
Boston (MA)                      6,600         8,280         3,423         7,757
Cleveland (OH)                   4,891         5,706           362         2,582
Washington National              7,952         8,052         2,572         2,706
 (D.C.)
Denver (CO)                      8,951        12,996         3,154         4,810
Dallas (TX)                     12,274        22,984         2,843        10,301
Detroit (MI)                     5,843        12,757         1,245         3,842
Newark (NJ)                      4,712         9,947         1,177         4,289
Houston Hobby (TX)               1,345         4,966           112           468
Houston Intercontinental         5,992        10,771         1,780         2,992
 (TX)
New York JFK (NY)                5,302         4,242         1,143         4,165
Los Angeles (CA)                12,607        15,827         2,860        10,610
New York LaGuardia (NY)          9,114         9,893         1,381         3,336
Kansas City (MO)                 4,069         5,228         1,907         2,183
Miami (FL)                       6,198         6,772           422         4,728
Minneapolis (MN)                 5,014        11,744           930         4,403
Chicago O'Hare (IL)             22,343        25,529         4,429         7,342
Philadelphia (PA)                5,585         8,430         4,197         4,864
Phoenix (AZ)                     3,754        13,775           463         2,057
Pittsburgh (PA)                  7,408        11,069         2,852         5,491
San Diego (CA)                   3,288         5,957           411         2,500
Seattle (WA)                     4,126         8,857         1,805         4,426
San Francisco (CA)               9,309        11,270         1,495         4,141
St. Louis (MO)                   7,354        14,771         1,501         4,995
Tampa (FL)                       5,374         4,231           429         3,728
================================================================================
Overall                        188,614       277,106        44,081       114,176
--------------------------------------------------------------------------------
Source:  GAO's analysis of OAG data. 


ADDITIONAL DETAILS ON OUR SCOPE
AND METHODOLOGY
========================================================= Appendix VII

To provide consistent, comparable information in updating our prior
report on trends in airfares since deregulation at airports serving
small, medium-sized, and large communities, we reviewed fare data on
the same 112 airports that we examined in the prior report.\23 For
further consistency, we also analyzed air service and safety data for
the same airports.  We selected the 49 small-community airports, 38
medium-sized-community airports, and 25 large community airports
using the following criteria: 

  -- Small communities were those with populations in a metropolitan
     statistical area of 300,000 or less, medium-sized communities
     were in an area of 300,001 to 600,000, and large communities
     were in an area of 1.5 million or more.\24

In the prior report, we used 1984 U.S.  Census data to provide
information on community size midway between the years reviewed
(1979, 1984, and 1988) for each airport location.  While keeping the
same sample of airports for this report, we reviewed U.S.  Census and
Bureau of Economic Analysis data to identify changes in community
population as well as income and employment.  We did this to examine
economic trends that may explain the changes in fares, service
quantity, and service quality that we observed. 

  -- All of the airports were among the largest 175 in the nation. 
     This criterion was necessary because as an airport's rank falls,
     the number of tickets from that airport in the Department of
     Transportation's "Passenger Origin-Destination Survey" (O&D
     Survey) declines.  A smaller number of tickets per route
     increases the potential for sampling error and may result in
     calculations that are not representative of the airport's
     overall traffic. 

  -- All of the airports were located within the 48 contiguous states
     because airports outside the contiguous states are often special
     cases.  Travel from airports located in Alaska, Hawaii, Puerto
     Rico, and the Virgin Islands is often for very short distances
     (between islands) and very long distances (between Alaska or
     Hawaii and the contiguous states) or may take the place of
     ground transportation (between cities in Alaska). 

In updating the airfare trends for each airport, we converted the
data in the previous report into 1994 dollars and then identified and
used the same routes (origin and destination airport combinations)
that we used in the previous report.  To verify the reliability and
validity of our results, we conducted a number of checks on the fare
data.  For example, to check the extent to which our results may have
been affected by routes that we examined in our prior report but
which are no longer served by airlines, we re-ran the data in the
previous report (1979, 1984, and 1988) using only those routes that
were served in 1994.  We found virtually no differences in fare
levels or trends.  In addition, we used a fare screen to eliminate
inaccurate fare data from the O&D Survey.  The fare screen, based on
data in the OAG, eliminated records from the O&D Survey showing
yields (fares per passenger mile) outside of allowable minimum and
maximum yields, such as a 0.0 cent yield for a trip between Los
Angeles and New York. 

Because the number of passengers traveling on the various routes can
change over time, examining fares at two different times could
reflect differences in the number of travelers going to various
destinations rather than fare changes.  Therefore, as we did in the
prior report, we held the distribution of passengers between routes
constant at the 1988 level to take this possibility into account. 
Finally, because we analyzed data that were drawn from a statistical
sample of tickets purchased, each estimate developed from the sample
has a measurable precision, or sampling error.  The sampling error is
the maximum amount by which the estimate obtained from a statistical
sample can be expected to differ from the true universe value. 
Sampling errors are usually stated at a certain confidence level--in
this case, at a 95-percent level.  This means the chances are 19 out
of 20 that if we reviewed all tickets purchased, the results would
differ from the estimates obtained from our sample by less than the
sampling errors of such estimates. 


--------------------
\23 GAO/RCED-91-13, Nov.  8, 1990. 

\24 Since our reviews focused on small and medium-sized communities,
we did not examine data on airports serving metropolitan statistical
areas of between 600,000 and 1.5 million people. 


MAJOR CONTRIBUTORS TO THIS REPORT
======================================================== Appendix VIII

RESOURCES, COMMUNITY, AND ECONOMIC
DEVELOPMENT DIVISION, WASHINGTON,
D.C. 

Gerald L.  Dillingham, Associate Director
Francis P.  Mulvey, Assistant Director
Timothy F.  Hannegan
Lynne L.  Goldfarb
Steven C.  Martin
Sara Ann W.  Moessbauer
Daniel G.  Williams
J.  Annette Wright



RELATED GAO PRODUCTS
============================================================ Chapter 1

Airline Competition:  Higher Fares and Less Competition Continue at
Concentrated Airports (GAO/RCED-93-171, July 15, 1993). 

Computer Reservation Systems:  Action Needed to Better Monitor the
CRS Industry and Eliminate CRS Biases (GAO/RCED-92-130, Mar.  20,
1992). 

Airline Competition:  Effects of Airline Market Concentration and
Barriers to Entry on Airfares (GAO/RCED-91-101, Apr.  26, 1991). 

Airline Competition:  Weak Financial Structure Threatens Competition
(GAO/RCED-91-110, Apr.  15, 1991). 

Airline Competition:  Fares and Concentration at Small-City Airports
(GAO/RCED-91-51, Jan.  18, 1991). 

Airline Deregulation:  Trends in Airfares at Airports in Small and
Medium-Sized Communities (GAO/RCED-91-13, Nov.  8, 1990). 

Airline Competition:  Industry Operating and Marketing Practices
Limit Market Entry (GAO/RCED-90-147, Aug.  29, 1990). 

Airline Competition:  Higher Fares and Reduced Competition at
Concentrated Airports (GAO/RCED-90-102, July 11, 1990). 

Airline Competition:  DOT's Implementation of Airline Regulatory
Authority (GAO/RCED-89-93, June 28, 1989). 

Airline Service:  Changes at Major Montana Airports Since
Deregulation (GAO/RCED-89-141FS, May 24, 1989). 

Airline Competition:  Fare and Service Changes at St.  Louis Since
the TWA-Ozark Merger (GAO/RCED-88-217BR, Sept.  21, 1988). 

Competition in the Airline Computerized Reservation Systems
(GAO/T-RCED-88-62, Sept.  14, 1988). 

Airline Competition:  Impact of Computerized Reservation Systems
(GAO/RCED-86-74, May 9, 1986). 


*** End of document. ***