Medicaid: Strategies to Help States Address Increased		 
Expenditures during Economic Downturns (18-OCT-06, GAO-07-97).	 
                                                                 
During economic downturns, states may struggle to finance	 
Medicaid, a federal-state health financing program for certain	 
low-income individuals. States receive federal matching funds for
their Medicaid programs according to a statutory formula based on
each state's per capita income (PCI) in relation to national PCI.
The number of individuals eligible for Medicaid can increase	 
during downturns as a result of rising unemployment. GAO	 
previously reported that any federal assistance to respond to	 
downturns should be well-timed and account for each state's	 
fiscal circumstances. GAO was asked to consider strategies to	 
help states offset increased Medicaid expenditures in the event  
of future economic downturns. GAO analyzed policy proposals and  
federal and state strategies to cope with downturns to identify  
and develop three potential strategies. GAO explored (1)	 
targeting assistance to states most affected by a downturn, (2)  
using 2 instead of 3 years of PCI data to compute federal	 
matching rates to more accurately reflect states' economic	 
circumstances, and (3) giving states the option to obtain	 
assistance based on their own determination of need. GAO	 
discussed the strategies with experts, identified design	 
considerations, and analyzed each strategy's potential effects.  
The Department of Health and Human Services received a draft of  
this report and did not comment.				 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-07-97						        
    ACCNO:   A62306						        
  TITLE:     Medicaid: Strategies to Help States Address Increased    
Expenditures during Economic Downturns				 
     DATE:   10/18/2006 
  SUBJECT:   Economic analysis					 
	     Federal aid to states				 
	     Federal funds					 
	     Federal/state relations				 
	     Health care costs					 
	     Health care planning				 
	     Medicaid						 
	     Needs assessment					 
	     Policy evaluation					 
	     Strategic planning 				 
	     Unemployment rates 				 
	     Medicaid Equitable Federal Medical 		 
	     Assistance Percentage Formula			 
                                                                 
	     Medicaid Program					 

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GAO-07-97

   

     * [1]Results in Brief
     * [2]Background
     * [3]Targeting Supplemental Federal Assistance to States Requires

          * [4]Design Considerations
          * [5]Effects

     * [6]Using Fewer Years of Data to Compute Matching Rates Would No

          * [7]Design Considerations
          * [8]Effects

     * [9]States Could Determine Their Own Needs for Assistance with M

          * [10]Design Considerations

               * [11]Direct Intergovernmental Loans
               * [12]Facilitated Private Lending
               * [13]National Rainy Day Fund

          * [14]Effects

     * [15]Concluding Observations
     * [16]Agency Comments
     * [17]Objectives and Scope
     * [18]Identifying and Evaluating the Strategies
     * [19]Illustrating the Range of Economic Conditions Affecting Stat
     * [20]Organizations GAO Contacted
     * [21]Data and Data Reliability
     * [22]Design Considerations for Starting and Stopping Assistance

          * [23]Choice of Unemployment as an Indicator
          * [24]Use of Unemployment as an Economic Indicator
          * [25]Alternative Indicators of Downturns and Increases in Medicai
          * [26]Starting and Stopping Supplemental Assistance
          * [27]Automatic Trigger Design Objectives and Issues
          * [28]An Illustrative Automatic Trigger
          * [29]Performance of the Automatic Trigger
          * [30]Use of Alternative Parameters in the Automatic Trigger
          * [31]Alternative Ways to Start and Stop Supplemental Assistance

     * [32]Determining the Level of Supplemental Assistance

          * [33]Level of Funding
          * [34]Funding and the Appropriations Process
          * [35]Allocation Model

     * [36]Deciding How to Distribute Supplemental Assistance

          * [37]Matching Assistance or Lump-sum Grants
          * [38]Calculation of Lump-sum and Matching Assistance Amounts

     * [39]Simulation Model Results
     * [40]Overview of Analysis
     * [41]Comparison of Changes in Matching Rates with Changes in PCI
     * [42]Comparison of Changes in PCI with Changes in the Simulated M
     * [43]Comparisons of Changes in the 3-Year and 2-Year Matching Rat
     * [44]Comparisons of 2-Year and 3-Year Matching Rates in Year-to-Y
     * [45]Selected Intergovernmental Loan Programs
     * [46]State Rainy Day Funds
     * [47]GAO Contacts
     * [48]Acknowledgments
     * [49]GAO's Mission
     * [50]Obtaining Copies of GAO Reports and Testimony

          * [51]Order by Mail or Phone

     * [52]To Report Fraud, Waste, and Abuse in Federal Programs
     * [53]Congressional Relations
     * [54]Public Affairs
     * [55]GAO's Mission
     * [56]Obtaining Copies of GAO Reports and Testimony

          * [57]Order by Mail or Phone

     * [58]To Report Fraud, Waste, and Abuse in Federal Programs
     * [59]Congressional Relations
     * [60]Public Affairs

United States Government Accountability Office

Report to Congressional Requesters

GAO

October 2006

MEDICAID

Strategies to Help States Address Increased Expenditures during Economic
Downturns

GAO-07-97

Contents

Letter 1

Results in Brief 5
Background 7
Targeting Supplemental Federal Assistance to States Requires Careful
Consideration to Address Differences in States' Downturns 13
Using Fewer Years of Data to Compute Matching Rates Would Not Consistently
Result in Assistance that Better Reflects States' Current Economic
Conditions 20
States Could Determine Their Own Needs for Assistance with
Medicaid-Specific Loans or a National Rainy Day Fund 23
Concluding Observations 26
Agency Comments 27
Appendix I Objectives, Scope, and Methodology 29
Appendix II Designing a Strategy of Targeted Supplemental Medicaid
Assistance 32
Appendix III Designing a Strategy to Better Reflect States' Current
Economic Conditions 55
Appendix IV Information on Selected Intergovernmental Loan Programs and
State Rainy Day Funds 65
Appendix V GAO Contacts and Staff Acknowledgments 69

Tables

Table 1: Average Annual State Medicaid Expenditures per Beneficiary, by
Population Group, 2003 11
Table 2: Key Design Decisions, Parameters of GAO's Model, and Alternative
Parameters that Could Be Applied for Targeting Supplemental Medicaid
Assistance to States 15
Table 3: Characteristics of Economic Downturns and Their Effect on States'
Receipt of Supplemental Assistance 19
Table 4: Analysis of Three Strategies to Help States Respond to Increased
Medicaid Costs during Economic Downturns 30
Table 5: Simulated Supplemental Assistance for Economic Conditions of the
2001 Downturn 49
Table 6: Matching Rates Used to Analyze Strategy 56
Table 7: Comparison of States' Year-to-Year Differences in 2-Year and
3-Year Matching Rates, 1990-2004 64

Figures

Figure 1: Medicaid Beneficiaries and Expenditures by Population Group,
Fiscal Year 2003 8
Figure 2: States' Percentage Point Change in Unemployment, March 2001 to
March 2002 10
Figure 3: Number of States Experiencing a 10 Percent or More Increase in
Their Unemployment Rate, 2000 to 2004 17
Figure 4: Timing of Data Used to Calculate States' Federal Matching Rates
for Fiscal Year 2006 21
Figure 5: Number of States with a 10 Percent or More Increase in Their
Unemployment Rate Compared to the Same Quarter 1 Year Earlier, 1979-2004
38
Figure 6: Total of States' Quarterly Increase in Unemployment Covered by
Simulation Model's Supplemental Assistance 40
Figure 7: Effects of Alternative Threshold Parameters on the Start and
Number of Quarters of Supplemental Assistance, 2000 through 2005 42
Figure 8: Simulated Supplemental Assistance for a State with an Early,
Long, and Deep Economic Downturn 51
Figure 9: Simulated Supplemental Assistance for a State with a Relatively
Early, Long-Lasting, and Shallow Downturn 52
Figure 10: Simulated Supplemental Assistance for a State with a Late,
Short, and Shallow Downturn 53
Figure 11: Simulated Supplemental Assistance for a State with a Short,
Deep Downturn 54
Figure 12: Correlations of the Changes in the 3-Year and 2-Year Matching
Rates with Changes in PCI 58
Figure 13: Correlations of the Changes in the 3-Year and 2-Year Matching
Rates with Changes in the Unemployment Rates 59
Figure 14: Correlations of the Changes in the Simulated Matching Rate with
the Changes in PCI, 1990 to 2004 60
Figure 15: Correlations of the Changes in 3-Year and 2-Year Matching Rates
with the Changes in the Simulated Matching Rate 62

Abbreviations

BCCA Breast and Cervical Cancer Act

BEA Bureau of Economic Analysis

BLS Bureau of Labor Statistics

CMS Centers for Medicare & Medicaid Services

CWSRF Clean Water State Revolving Fund

CDL Community Disaster Loan

EPA Environmental Protection Agency

FEMA Federal Emergency Management Agency

FMAP Federal Medical Assistance Percentage

FUA Federal Unemployment Account

GDP gross domestic product

JGTRRA Jobs and Growth Tax Relief Reconciliation Act of 2003

NASBO National Association of State Budget Officers

NBER National Bureau of Economic Research

NCSL National Conference of State Legislatures

PCI per capita income

TANF Temporary Assistance for Needy Families

UI Unemployment Insurance

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United States Government Accountability Office

Washington, DC 20548

October 18, 2006 October 18, 2006

The Honorable Susan M. Collins Chairman, Committee on Homeland Security
and Governmental Affairs United States Senate The Honorable Susan M.
Collins Chairman, Committee on Homeland Security and Governmental Affairs
United States Senate

The Honorable Gordon H. Smith Chairman, Special Committee on Aging United
States Senate The Honorable Gordon H. Smith Chairman, Special Committee on
Aging United States Senate

The Honorable Jeff Bingaman The Honorable Ben Nelson The Honorable John D.
Rockefeller, IV United States Senate The Honorable Jeff Bingaman The
Honorable Ben Nelson The Honorable John D. Rockefeller, IV United States
Senate

During economic downturns, states can experience difficulties financing
programs such as Medicaid, a joint federal-state health financing program
that covers medical costs for certain categories of low-income
individuals. Economic downturns result in rising unemployment, which can
lead to increases in the number of individuals who are eligible for
Medicaid coverage, and in declining tax revenues, which can lead to less
available revenue with which to fund coverage of additional enrollees. For
example, during a period of economic downturn, Medicaid enrollment rose
8.6 percent between 2001 and 2002, which was largely attributed to states'
increases in unemployment. During this same time period, state tax
revenues fell 7.5 percent. Further complicating the challenge of
responding to increased Medicaid expenditures during economic downturns is
the fact that Medicaid funding consumed a growing share of state general
fund or operating budgets, increasing from 15 percent in 1994 to 18
percent in 2004.1 During economic downturns, states can experience
difficulties financing programs such as Medicaid, a joint federal-state
health financing program that covers medical costs for certain categories
of low-income individuals. Economic downturns result in rising
unemployment, which can lead to increases in the number of individuals who
are eligible for Medicaid coverage, and in declining tax revenues, which
can lead to less available revenue with which to fund coverage of
additional enrollees. For example, during a period of economic downturn,
Medicaid enrollment rose 8.6 percent between 2001 and 2002, which was
largely attributed to states' increases in unemployment. During this same
time period, state tax revenues fell 7.5 percent. Further complicating the
challenge of responding to increased Medicaid expenditures during economic
downturns is the fact that Medicaid funding consumed a growing share of
state general fund or operating budgets, increasing from 15 percent in
1994 to 18 percent in 2004.1

Both the federal government and the states have responded to the demands
of Medicaid expenditure increases related to economic downturns. Following
the 2001 recession, Congress passed the Jobs and Growth Tax Relief
Reconciliation Act of 2003 (JGTRRA), which provided $10 billion in fiscal
relief through a temporary increase in federal Medicaid funding for all
states, as well as $10 billion in general assistance divided Both the
federal government and the states have responded to the demands of
Medicaid expenditure increases related to economic downturns. Following
the 2001 recession, Congress passed the Jobs and Growth Tax Relief
Reconciliation Act of 2003 (JGTRRA), which provided $10 billion in fiscal
relief through a temporary increase in federal Medicaid funding for all
states, as well as $10 billion in general assistance divided among the
states to be used for essential government services.2 States have
responded to downturns in various ways, such as by using cost-cutting
program modifications; budget stabilization, or "rainy day," funds; and
borrowing.

1In fiscal year 2004, total expenditures for the Medicaid program (federal
and state) were about $298 billion.

Problems that states face in financing Medicaid cost increases during an
economic downturn can be exacerbated because, by design, the formula used
to calculate the amount of federal assistance that states receive for
Medicaid includes data that are as much as 5 years old. The federal
government matches state Medicaid spending according to this formula,
which is based on each state's per capita income (PCI) in relation to
national PCI. The amount of federal assistance states receive for Medicaid
is determined by a statutory formula known as the Federal Medical
Assistance Percentage (FMAP), or federal matching rate. The statute
specifies that matching rates be calculated 1 year before the fiscal year
in which they are effective, using a 3-year average of the most recently
available PCI data reported by the Department of Commerce. For example,
fiscal year 2007 matching rates were calculated at the beginning of fiscal
year 2006 using a 3-year average of PCI for 2002 through 2004.3
Consequently, federal matching rates reflect economic conditions that
existed several years earlier.

Recognizing the complex combination of factors affecting states during
economic downturns--increased unemployment, declining state revenues, and
increased downturn-related Medicaid costs--policymakers and others have
considered the possibility of establishing a legislative response that
would help states better cope with Medicaid cost increases. Any potential
legislative response would need to be considered within the context of
broader health care and fiscal challenges--including continually rising
health care costs, a growing elderly population, and Medicare and
Medicaid's increasing share of the federal budget. Absent fundamental
Medicaid reform, legislative actions and proposals have generally focused
on targeting assistance to states, improving the timing of the assistance
provided, or helping states build financial reserves for Medicaid.4

2The $10 billion temporary increase in federal Medicaid funding made
available through JGTRRA provided supplemental Medicaid funding to states
for the last two calendar quarters (April through September) of fiscal
year 2003 and the first three calendar quarters (October through June) of
fiscal year 2004.

3The federal matching rate is intended to adjust for differences in state
fiscal capacity and reduce program benefit disparities across states by
providing more federal funds to states with weaker tax bases. For fiscal
year 2006, federal matching rates ranged from 50 to 76 percent of state
Medicaid expenditures.

In 2004, we reported on the assistance provided by the federal government
to the states through JGTRRA, noting that federal assistance is most
effective when it takes into account each state's fiscal circumstances as
well as when and how severely states are affected by an economic
downturn.5 On the basis of these findings, you asked us to consider
strategies to help states address the increased costs of Medicaid in any
future economic downturn. An underlying assumption was that, in the event
of any future nationwide economic downturn, Congress would act to
appropriate additional funds, as it did following the 2001 recession. Your
interest was in exploring strategies whereby any additional funds could be
accurately timed and targeted to respond to a downturn but could also be
established in advance so that Congress would not have to wait to act
until a nationwide economic downturn is clearly identified. Accordingly,
we reviewed prior GAO reports, policy proposals, and federal and state
strategies to cope with downturns to identify and develop three potential
strategies. In this report, we explore the design considerations and
possible effects of three potential strategies aimed at helping states
with their share of Medicaid expenditures during an economic downturn by
(1) targeting supplemental funds to specific states on the basis of the
relative depth and duration of their economic downturns (as measured by
changes in their unemployment rates) as well as the extent to which their
Medicaid costs are likely to increase during a downturn, (2) using 2
instead of 3 years of PCI data to compute federal matching rates in an
attempt to better reflect states' current economic conditions, and (3)
providing states with options for obtaining assistance through a
Medicaid-specific rainy day fund or loan based on their own determination
of need.

To do our work, we analyzed research, including prior GAO reports that
examined the effects of economic downturns on Medicaid enrollment and
expenditures, the responsiveness of federal matching rates to economic
cycles, and policy proposals to help states respond to increased program
costs during downturns. We discussed the three potential strategies with
technical experts and representatives of key research groups and state
associations to gain insights on the extent to which strategies could help
states cope with the Medicaid-related fiscal consequences of economic
downturns. These discussions provided an opportunity to evaluate our
selection of strategies and discuss their potential effects. Our analysis
of the strategies differed depending on the strategy. For the first
strategy, we identified factors to consider in developing the targeting
strategy and devised a model to illustrate the extent to which different
methods of targeting supplemental federal funds would help states with
their Medicaid programs during economic downturns.6 The assumptions built
into our model were based on our analysis of data indicators from the past
three recessions.7 We chose unemployment as the key variable because it
reflects the potential for increases in Medicaid enrollments as a result
of an economic downturn. For the second strategy, which focused on using 2
years of PCI data--instead of the 3 years currently required by
statute--to compute federal matching rates in an attempt to better reflect
states' economic conditions, we analyzed how closely the federal matching
rates approximated states' economic conditions and constructed statistical
simulations to compare the federal assistance states would receive under
the strategy with the assistance they would receive under current policy.8
To determine the potential of each of the first two strategies to help
states address increased Medicaid spending, we simulated how the
implementation of the strategy could differ depending on the timing,
depth, and duration of a state's economic downturn. For the third
strategy, which focused on providing states with options for obtaining
assistance through a Medicaid-specific national rainy day fund or loan, we
identified key factors that could be considered, such as the structure and
use of existing intergovernmental loan programs and state rainy day funds.
We determined that the unemployment, PCI, and Medicaid expenditure data
used in this report are sufficiently reliable for describing the three
strategies and illustrating their potential effects. (Appendixes I through
IV provide additional detail about our methodology for assessing the three
strategies.) We did our work from April 2005 through September 2006 in
accordance with generally accepted government auditing standards.

4See GAO, Federal Assistance: Temporary State Fiscal Relief,
[61]GAO-04-736R (Washington, D.C.: May 7, 2004); GAO, Medicaid Formula:
Differences in Funding Ability among States Often Are Widened,
[62]GAO-03-620 (Washington, D.C.: July 10, 2003); Miller and Schneider,
The Medicaid Matching Formula: Policy Considerations and Options for
Modification, #2004-09, AARP Public Policy Institute (Washington, D.C.:
September 2004); and GAO, Medicaid: Restructuring Approaches Leave Many
Questions, [63]GAO/HEHS-95-103 (Washington, D.C.: Apr. 4, 1995).

5 [64]GAO-04-736R .

6Throughout this report, the term state refers to the 50 states and the
District of Columbia.

7We analyzed the past three recessions--1981 through 1983, 1991 through
1992, and 2001--to understand differences in the timing, depth, and
duration of different economic downturns. However, similar economic
patterns may not repeat themselves in future economic downturns.

8Where we conducted simulations for the first and second strategies, we
asked experts in Medicaid financing issues to provide suggestions
regarding their construction.

Results in Brief

No single strategy or combination of strategies can meet the varied
economic needs of all states at all times. However, the following
strategies may be useful starting points for Congress as it deliberates
how to help states cope with increased Medicaid expenditures during any
future economic downturn. Having an automatic mechanism in place could
provide a targeted and predictable response. The three strategies we
explored are

           o target supplemental Medicaid assistance to states most affected
           by a downturn,

           o use 2 years of PCI data to compute federal matching rates in an
           effort to better reflect states' current economic circumstances,
           and

           o give states the option to obtain assistance through a
           Medicaid-specific national rainy day fund or loan.

First, a strategy that provides supplemental assistance to states based on
changes in their unemployment rates would target funds to states most
affected by a downturn, but the design of such a strategy would need to
address the different characteristics of states' downturns. To illustrate
this strategy, we constructed a simulation model that adjusts the amount
of funding a state would receive on the basis of each state's percentage
increases in unemployment and per person spending on Medicaid services.
Our simulation model captured about 90 percent of states' increases in
unemployment during the most recent (2001) recession. While all states
received some amount of assistance under the model, states that
experienced the largest percentage increases in unemployment within the
same period in which the national downturn occurred received the largest
proportion of supplemental assistance. A smaller number of states received
less assistance than others in our simulation model because their
increased unemployment occurred either earlier or later than the national
downturn. Adjustments to the strategy design, such as extending the period
of assistance, could be applied to ensure that states with earlier or
later increases in unemployment also receive a commensurate amount of
funding, but such adjustments would add to the overall cost of the
strategy. Targeted supplemental federal assistance to states most affected
by a downturn could assist states relative to the depth and duration of a
downturn as well as increased Medicaid expenditures while also reflecting
congressional policy choices.

Second, using 2 years of PCI data to compute federal matching rates
instead of the 3 years required under current law did not result in
matching rates that consistently reflected states' recent economic
circumstances as measured by PCI or changes in states' unemployment. To
illustrate this strategy, we analyzed matching rates that varied in the
number of years of data used and compared them with changes in PCI and
unemployment data. Our analysis of this strategy, however, did not result
in federal matching rates that consistently increased during economic
downturns. In some cases, reducing the number of years of data also skewed
rates farther away from current economic conditions. In addition, this
strategy would result in larger year-to-year changes in matching rates for
most states compared to the fluctuations experienced under current law.
For these reasons, eliminating a year of data from the current matching
formula does not present a feasible alternative to help states address
increased Medicaid expenditures during economic downturns.

Third, giving states the opportunity to decide whether and to what extent
they need federal assistance could take the form of a loan, either from
the federal government or from the private capital market (subsidized and
possibly guaranteed by the federal government), or a Medicaid-specific
national rainy day fund. A federal Medicaid loan or rainy day fund could
give states greater autonomy in determining their need for assistance, but
utilization of either approach would depend on states' own economic and
political constraints as well as the program's design. For example,
limitations on the use of a loan may exist because of a state's statutory
or constitutional debt restrictions as well as federal restrictions on the
obligation of federal funds. While a national rainy day fund could allow
states to pool their risk and thereby spend less than they would if they
chose to establish individual Medicaid rainy day funds at the state level,
representatives of some public policy and research organizations we
contacted believed that some states might be reluctant to contribute to a
national fund that other states or the federal government could draw from.
Federal funding required for this strategy would vary depending on design
factors such as the inclusion of federal subsidies or matching funds. A
loan or national rainy day fund strategy could help address states'
Medicaid funding challenges during downturns, but the feasibility and
utility of this strategy would depend on the design of the loan or fund,
among other possible constraints.

Background

Economic downturns are characterized by reductions in output and income as
well as increased unemployment--and an accompanying increase in Medicaid
enrollment. Generally, as unemployment rises, the number of households
with incomes low enough to qualify for Medicaid coverage also rises.
Across the four broad populations eligible for Medicaid--children;
nondisabled, nonelderly adults; the elderly; and individuals with
disabilities--increases in eligibility for Medicaid during an economic
downturn are most concentrated among children and nondisabled, nonelderly
adults. One analysis of the relationship between unemployment and Medicaid
enrollment found that a 1 percentage point increase in the unemployment
rate would result in a nationwide increase in Medicaid enrollment of more
than 857,000 individuals--about 470,000 children and 387,000 nondisabled,
nonelderly adults.9 While these two populations make up the largest share
of Medicaid beneficiaries, they represent a small share of total Medicaid
expenditures (see fig. 1).10 Nondisabled, nonelderly adults and children
make up 76 percent of beneficiaries but account for just 30 percent of
expenditures.11

9Stan Dorn, Barbara Markham Smith, and Bowen Garrett, Medicaid
Responsiveness, Health Coverage, and Economic Resilience: A Preliminary
Analysis, Prepared for the Health Policy Institute of the Joint Center for
Political and Economic Studies (Washington, D.C.: Joint Center for
Political and Economic Studies, Sept. 27, 2005).

10In contrast, 70 percent of Medicaid spending goes to elderly individuals
and individuals with disabilities, who are least affected by economic
downturns, as reported by Dorn et al.

11In some cases, expenditures could not be attributed to specific
beneficiary populations and thus were excluded from these calculations.

Figure 1: Medicaid Beneficiaries and Expenditures by Population Group,
Fiscal Year 2003

Note: Percentages are based on Centers for Medicare & Medicaid Services
(CMS) beneficiary and expenditure data for fiscal year 2003, the most
recent year for which data are available by type of beneficiary. Total
fiscal year 2003 expenditures for Medicaid were $276 billion. Expenditures
in figure 1 do not include administrative expenses, disproportionate share
hospital payments, and other expenses that could not be attributed to
specific beneficiary populations. Beneficiaries do not include women
covered under the Breast and Cervical Cancer Act (BCCA) or individuals
whose eligibility status is unknown.

Additionally, increases in Medicaid enrollment and expenditures that occur
during nationwide downturns are not distributed evenly among states
because of differences in states' economic conditions, Medicaid program
design, and health care costs. Among states, downturns vary widely in
their onset, depth, and duration. For example, in March 2001, the United
States entered a recession, as indicated by a significant decline in
overall business activity, including an increase in unemployment, over
several months.12 During the next year, the national unemployment rate
increased by 1.4 percentage points, from 4.3 percent to 5.7 percent.
During this same period, the unemployment rate increased by more than 2
percentage points in some states but actually decreased in others (see
fig. 2).

12The National Bureau of Economic Research (NBER) identifies recessions on
the basis of several indicators, including employment, sales in the
manufacturing and trade sectors, and industrial production. A recession is
a significant decline in economic activity spread across the economy,
lasting more than a few months, normally visible in real gross domestic
product (GDP), real income, employment, industrial production, and
wholesale-retail sales. A recession begins just after the economy reaches
a peak of activity and ends as the economy reaches its trough. Not all
economic downturns are recessions. Economic downturns would include--but
not be limited to--recessions identified by NBER.

Figure 2: States' Percentage Point Change in Unemployment, March 2001 to
March 2002

Note: Percentage point unemployment changes from GAO, Health Insurance:
States' Protections and Programs Benefit Some Unemployed Individuals,
[65]GAO-03-191 (Washington, D.C.: Oct. 25, 2002).

The Medicaid enrollment and expenditure increases associated with a given
increase in unemployment also vary across states because of differences in
the scope of states' coverage for groups most affected by the downturn.
For example, in 2003, average annual state expenditures for children and
nondisabled, nonelderly adults ranged from $1,258 per beneficiary to
$4,377, with a national average of $1,823. Table 1 shows the range in
states' Medicaid expenditures per beneficiary by population group in 2003.

Table 1: Average Annual State Medicaid Expenditures per Beneficiary, by
Population Group, 2003

State Medicaid Children and nondisabled, nonelderly                        
expenditures                                 adults Elderly Blind/disabled 
Average                                      $1,823 $14,540        $14,079 
Minimum                                       1,258   6,781          6,792 
Maximum                                       4,377  26,384         25,553 

Source: GAO analysis of CMS data.

Note: Data represent annual state expenditures per beneficiary.

The federal matching formula for Medicaid adjusts for differences in state
fiscal capacity and reduces program benefit disparities across states by
providing more federal funds to states with weaker tax bases.13 The
statutory matching formula calculates the federal matching rate for each
state on the basis of its PCI in relation to national PCI as follows.

Federal matching rate = 1.00 - 0.45*[(State PCI) / (U.S. PCI)]2

Relative PCI is included as a representation of states' funding ability,
as a combination of states' resources and people in poverty. Squaring PCI
has the effect of making PCI appear in the formula twice, to reflect both
states' resources and people in poverty. The formula uses a 3-year average
of PCI, the effect of which is to smooth out fluctuations in state PCI so
that it reflects longer-term trends rather than short-term fluctuations of
the business cycle. This smoothing effect helps minimize year-to-year
changes in federal matching funds, which could be disruptive to states'
budget planning.

13By statute, the federal share of Medicaid spending ranges from 50 to 83
percent. The 50 percent minimum federal share ("50 percent floor")
reflects a federal commitment to fund at least half the cost of each
state's Medicaid program. For 2006, 12 states received federal matching
rates of 50 percent.

The use of PCI as a measure of states' funding ability, however, is
problematic. Our prior work concluded that PCI is not a comprehensive
indicator of states' total available resources and thus does not
accurately represent states' funding ability. PCI also does not account
for the size and cost of serving states' poverty populations, which vary
considerably; for example, two states with low PCIs may have very
different proportions of elderly persons potentially eligible for Medicaid
and thus very different amounts of Medicaid spending. Moreover, concerns
have been raised regarding the age of the data used to calculate the
matching rate. In particular, the use of a 3-year PCI average to compute
matching rates, combined with a 1-year lag between computation and
implementation, means that the rates reflect economic conditions that
existed several years earlier.14

To cope with the difficulties of financing Medicaid and other programs
during an economic downturn, states have, among other actions, borrowed
from intergovernmental loan programs and drawn down state budget
stabilization funds, which are also referred to as rainy day funds.
Intergovernmental loan programs can generally be categorized as direct
loans or loan guarantees. Both require federal involvement and can include
a federal subsidy, but loan guarantees are administered by nonfederal
lending institutions. Federal credit programs can vary in their design and
purpose. While federal guidelines offer broad standards and principles for
administering credit programs, specific loan terms are set in statute or
by administering agencies based on the program's policy goals.15 According
to the National Association of State Budget Officers (NASBO), budget
stabilization funds exist in almost all states and allow states to set
aside surplus revenue during periods of economic growth for use during
downturns. States have different legislative requirements regarding the
amount of funds that can be accumulated, the process for releasing funds,
and the purposes for which funds can be used.

14See [66]GAO-03-620 .

15OMB Circular A-129 outlines guidelines on federal government loans.

Targeting Supplemental Federal Assistance to States Requires Careful
Consideration to Address Differences in States' Downturns

Providing supplemental federal assistance to states that is based on
changes in their unemployment rates would target additional Medicaid funds
to states most affected by a downturn, but the design of such a strategy
would need to address the different characteristics of states' downturns.
A strategy to target funds to states based on the duration and depth of
states' downturns assumes that, if authorized by Congress, supplemental
assistance could begin when predetermined thresholds are reached. This
approach is in contrast with the 2003 fiscal relief package, JGTRRA, which
provided assistance to states after the recession had ended. This
supplemental assistance strategy would leave the existing Medicaid formula
unchanged and add a new, separate assistance formula that would operate
only during times of economic downturn and use variables and a
distribution mechanism that differ from those used for calculating
matching rates. We identified key design considerations for a strategy
that would target funds based on states' downturns and devised a model to
illustrate the extent to which it could help target supplemental federal
Medicaid funds to states experiencing economic downturns of different
depths and durations. The design we simulated in our model would deliver
the most assistance to the group of states that experience increases in
unemployment within the same relative period of time. However, a smaller
number of states with relatively earlier or later increases in
unemployment would receive less assistance. Further adjustments to the
strategy design, such as methods to extend the period of assistance, could
be applied to ensure that states with earlier or later increases in
unemployment would receive more quarters of supplemental assistance
payments. Such extensions, however, would add to the overall cost of the
strategy.

Design Considerations

Development of a strategy to target funds based on differences in states'
economic downturns involves three key considerations: (1) deciding the
starting and ending points of assistance, (2) determining the amount of
additional federal Medicaid assistance that will be available, and (3)
determining how this additional assistance will be distributed to the
states. Using data from the past three recessions, we developed a model to
simulate targeted supplemental assistance to states experiencing increased
unemployment. The model focused on mechanisms to distribute supplemental
federal funds depending on the extent of a state's downturn and its
relative Medicaid expenditures.

To determine the amount of federal assistance that would be provided based
on this strategy, our model incorporated a retrospective assessment, which
would involve assessing the increase in each state's unemployment rate for
a particular quarter compared to the same quarter of the previous year.
The economic trigger for this strategy would be when 23 or more states had
increased unemployment of 10 percent or more compared to the unemployment
rate that existed for the same quarter 1 year earlier (such as from 5
percent to 5.5 percent unemployment). This is an increase of 10 percent
compared to the unemployment rate of the same quarter in the previous year
and not a 10 percentage point change in unemployment rates (such as from 5
percent unemployment to 15 percent). We chose these two threshold
values--23 or more states and increased unemployment of 10 percent or
more--to work in tandem to ensure that the national economy had entered a
downturn and that the majority of states were not yet in recovery from the
downturn.16 Table 2 summarizes the key design decisions, our model's
parameters, and some alternative parameters. (See app. II for additional
discussion of the key design decisions incorporated into the GAO model.)

16We chose both numbers based on a review of states' unemployment rates
over the past three recessions and determined that these levels would have
provided considerable certainty that the economic slowdown was nationwide.

Table 2: Key Design Decisions, Parameters of GAO's Model, and Alternative
Parameters that Could Be Applied for Targeting Supplemental Medicaid
Assistance to States

Key design                                                  
decision         Parameters of GAO modela   Alternative parametersb
Establish        Starting point             Starting point  
starting and                                                
ending point        o The starting point       o Varying numbers of states
                       would be when 23 or        and percentage changes in
                       more states show a         unemployment could be
                       quarterly state            applied.     
                       unemployment rate          o Indicators other than
                       increase of 10 percent     unemployment--or indicators
                       or more (the               used in conjunction with
                       retrospective              unemployment--could be used
                       assessment).c              to start the program.
                       o Once started, any        o Congressional action
                       state with any increase    could be required to start
                       in unemployment would      the program (rather than
                       be eligible to receive     establishing an automatic
                       assistance.                trigger based on threshold
                                                  values).     
                    Ending point               Ending point    
                                                               
                       o The ending point         o Varying numbers of
                       would be when fewer        states, percentage changes
                       than 23 states had         in unemployment, and
                       quarterly unemployment     quarters of assistance
                       increases of               could be applied.
                                                  o Other indicators could be
                       10 percent or more.        used to end the program.
                                                  o Congressional action
                       o The number of            could be required to end
                       quarters that              the program (rather than
                       assistance continued       establishing an automatic
                       would depend on the        stopping point based on
                       severity and duration      threshold values).
                       of the economic                         
                       downturn.                               
Determine amount    o The amount of federal    o The amount of federal
of federal          assistance would be        assistance could be set by
assistance to be    determined on the basis    Congress based on factors
available           of the relationship        other than changes in
                       between changes in         unemployment and increases
                       unemployment and           in Medicaid expenditures.
                       increases in Medicaid                   
                       expenditures.                           
                       o Based on the depth of                 
                       the 2001 recession, the                 
                       amount of federal                       
                       assistance would have                   
                       been                                    
                                                               
                       $4.2 billion.                           
Determine           o Funds would be           o Model could allow for a
distribution of     distributed quarterly      lump-sum grant distributed
assistance          through a targeted         on some schedule other than
                       supplement to states'      quarterly payments tied to
                       federal matching rates.    states' federal matching
                       o Distribution amount      rates.       
                       varies based on a          o Retroactive rebate
                       state's change in          payments could be provided
                       unemployment and its       to the states based on
                       average cost of            their actual increased
                       providing services to      expenditures.
                       children and               o Assistance could be
                       nondisabled, nonelderly    determined based on an
                       adults.                    alternative threshold
                                                  (other than a 10 percent or
                                                  more increase in
                                                  unemployment).

Source: GAO.

aOur model assumed that once enacted, the targeted assistance would
operate without the need for congressional action to initiate assistance
during an economic downturn.

bMost alternative parameters were not simulated in our model. Appendix II
provides additional details on alternative parameters that could be used.

cThe retrospective assessment is based on a quarterly moving average of
seasonally adjusted unemployment data for the 12 most recent months. The
GAO model included these parameters based on quantitative analysis of
prior recessions combined with subjective judgment. We chose these
threshold values based on evidence which indicated that 23 states
experiencing a 10 percent or more increase in unemployment provided
considerable certainty that an economic slowdown had extended nationwide
and that at least 23 states had not yet entered a recovery. These
parameters could be adjusted up or down to tighten or loosen the threshold
for providing supplemental assistance. The use of unemployment as an
indicator also reflects research establishing a connection between
increased unemployment and Medicaid enrollment.

To determine the amount of supplemental federal assistance needed to help
states address increased Medicaid expenditures during a downturn, we
relied on research that estimated a relationship between changes in
unemployment and changes in Medicaid spending while holding constant other
factors that influence Medicaid spending.17 Using data from the 2001 and
the 1991-1992 recessions and this research, our model assumes federal
assistance of approximately $4.2 billion, which would be less than 1
percent of Medicaid spending for a 2-year period.18 Depending on the fund
distribution method, budgeting sufficient amounts for the supplemental
federal funding would require estimating the potential economic effects of
a downturn because forecasting states' unemployment increases is
difficult. If the targeting strategy was designed to function as an
open-ended grant that provides states with an incremental increase to
their matching rates, then states' expenditures would be matched as the
downturn-induced growth of enrollments increased their Medicaid spending.
However, if the program was designed to provide a lump-sum amount of
assistance or to function as a closed-ended assistance program, then
setting a funding level would be necessary.

Within the key parameters that frame this strategy are many variations in
design that could be considered to achieve different policy goals. For
example, if it was deemed important to provide states with a longer period
of assistance, the retrospective assessment of the increase in the
unemployment rate could be extended in order to help states with
longer-lasting or late downturns. Additional criteria could be established
to accomplish other policy objectives, such as controlling federal
spending by limiting the number of quarters of payments or stopping
payments after predetermined spending caps are reached.

17See Dorn et al. (Sept. 27, 2005).

18For our model, we used Dorn et al.'s estimates to derive an average
increase in Medicaid expenditures per additional unemployed person of
$300, which could be adjusted over time by inflation and changes in
demographics of the Medicaid population. See Dorn et al. (Sept. 27, 2005).

Effects

Our simulation model showed that a retrospective assessment resulting in a
10 percent or more increase in unemployment in 23 or more states would
trigger supplemental assistance for 7 quarters, the period beginning with
the first quarter of 2002 and continuing through the third quarter of
2003.19 Overall, about 90 percent of state increases in unemployment from
the second quarter of 2000 through the fourth quarter of 2004 were
captured by our simulation, which began the assistance in the first
quarter of 2002 and continued it through the third quarter of 2003. If the
simulation model had been in effect during the 2001 recession, this
strategy's starting point would have provided assistance to states a full
year earlier than the enhanced matching rate implemented by Congress under
the previous fiscal assistance legislation, JGTRRA, which began providing
supplemental assistance in the third quarter of 2003. (See fig. 3.)

Figure 3: Number of States Experiencing a 10 Percent or More Increase in
Their Unemployment Rate, 2000 to 2004

aThe quarter in which payment begins under this strategy reflects a
two-quarter lag for data to become available. Therefore, the count of
states represents the count from the third quarter of 2001.

19This is an increase of 10 percent or more compared to the unemployment
rate that existed a year earlier and not a 10 percentage point change in
unemployment rates. Unless otherwise specified, all percentage changes are
stated in terms of a percentage increase over a base quarter.

bIn response to the 2001 recession, our model would have had the strategy
in operation from the first quarter of 2002 to the third quarter of 2003,
the period when 23 states had a 10 percent or more increase in
unemployment compared to the same quarter of the previous year.

cFor comparison purposes, the enhanced matching rate under the 2003 fiscal
relief package, JGTRRA, was implemented in the third quarter of 2003.

Under this strategy, our model's results show that the timing and depth of
a state's economic downturn can affect the amount of supplemental
assistance a state receives. In general, states with deep downturns that
occur coincident with the period in which supplemental assistance payments
would be made would receive the largest proportion of federal assistance.
States experiencing an earlier or later economic downturn--meaning more
than 1 year before or 1 year later than the start of the payments--would
not receive payments to cover the full period of their economic downturn,
regardless of the extent of the state's increased unemployment. With
regard to the depth of each state's downturn, the results of our model
simulation showed that all states would receive some amount of
supplemental federal Medicaid assistance, with the increased matching rate
ranging from 0 percent to 2.01 percent.20 (See table 3.) In contrast, the
previous fiscal assistance legislation, JGTRRA, provided the same matching
rate increase to all states.

20One state received a matching rate increase that was less than 0.005
percentage points.

Table 3: Characteristics of Economic Downturns and Their Effect on States'
Receipt of Supplemental Assistance

Downturn       Effect on states' receipt of                                
characteristic supplemental assistance             Results of GAO modela   
Timing         States with unemployment increases  37 states would have    
                  that are relatively earlier or      had increases in        
                  later than the strategy's starting  unemployment            
                  point may not receive the maximum   commensurate with the   
                  amount of supplemental federal      start of the            
                  assistance.                         supplemental federal    
                                                      assistance.             
                                                                              
                                                      12 states would have    
                                                      had increases in        
                                                      unemployment that began 
                                                      before the start of     
                                                      supplemental federal    
                                                      assistance.             
                                                                              
                                                      1 state would have had  
                                                      an increase in          
                                                      unemployment that       
                                                      started after the       
                                                      supplemental federal    
                                                      assistance ended.       
Duration       States with economic downturns      4 states had downturns  
                  lasting 7 or fewer quarters would   lasting 7 quarters.     
                  be most likely to receive the                               
                  maximum amount of supplemental      28 states had downturns 
                  federal assistance.                 lasting fewer than 7    
                                                      quarters.b              
                                                                              
                                                      18 states had downturns 
                                                      lasting more than 7     
                                                      quarters.               
Depth          The supplemental federal assistance 0.80 percent was the    
                  a state would receive is determined median increase in a    
                  in part by the depth of its         state's federal         
                  economic downturn and the amount of matching rate.          
                  its unemployment increase.                                  
                                                      0.00 percent was the    
                                                      lowest increase in a    
                                                      state's federal         
                                                      matching rate.c         
                                                                              
                                                      1.77 percent was the    
                                                      highest increase in a   
                                                      state's federal         
                                                      matching rate.          

Source: GAO simulation using data from BLS and CMS.

aBased on the first quarter of 2002 through the third quarter of 2003.

bOne state showed no indication of a downturn based on increases in
unemployment..

cOne state received a matching rate increase that was less than 0.005
percentage points.

Additionally, assistance provided to individual states would vary
depending on the relative size and composition of their expenditures for
cyclically sensitive Medicaid populations. Because economic downturns are
likely to increase Medicaid enrollment for children and nondisabled,
nonelderly adults--but generally not for the elderly or individuals with
disabilities--we adjusted the amount of supplemental federal Medicaid
assistance based on the characteristics of each state's Medicaid spending
by beneficiary population category in order to target the amount of
supplemental federal assistance. As a result, two states with similar
downturns in terms of percentage change in unemployment could receive
different amounts of supplemental assistance depending on their average
cyclically sensitive Medicaid expenditures per nonelderly person in
poverty. For example, Arizona and Wisconsin had an average quarterly
percentage change in unemployment of 41 percent and 52 percent during the
2001 recession, which would have resulted in lump sum amounts of
assistance of $86 million and $106 million, respectively. However,
applying a Medicaid expenditure index that we developed, which takes into
account each state's relative Medicaid spending per nonelderly person in
poverty, Arizona would have received $93 million in supplemental federal
Medicaid payments compared with $45 million for Wisconsin using the
parameters described for this strategy.21

Using Fewer Years of Data to Compute Matching Rates Would Not Consistently
Result in Assistance that Better Reflects States' Current Economic Conditions

A second strategy uses fewer years of data by eliminating the oldest data
from the computation of federal matching rates in an attempt to better
reflect states' current economic conditions. However, based on our
analysis of a 15-year period (1990 to 2004), we found that using fewer
years of data did not result in federal matching rates that better
reflected states' current economic conditions. In particular, the inherent
time lag necessary to obtain data and calculate the matching rates limited
the ability of this strategy to provide assistance to states that
reflected more recent economic conditions. In some cases, reducing the
number of years of data skewed rates farther away from current economic
conditions. This strategy would result in larger year-to-year changes in
matching rates for most states compared with the fluctuations experienced
under current law.22 Based on this analysis, eliminating a year of data
from the current matching formula would not help states address increased
Medicaid expenditures during economic downturns.

Design Considerations

This strategy would use fewer years of PCI data to compute federal
matching rates. This strategy relies on the current matching formula, with
the adjustment of using 2 years of PCI data instead of the 3 years
required under current law (see fig. 4). Implementation of this strategy
would require a statutory change to the federal matching formula and could
be made permanent. Unlike the first strategy, which would require that an
established number of states reach a certain percentage change in
unemployment, this strategy would not require monitoring of economic
conditions to trigger implementation. In addition, this strategy would not
distribute the supplemental Medicaid assistance required for
implementation of the first strategy but would instead adjust the relative
proportion of Medicaid funding distributed to the states.

21Appendix II provides details on the calculation of this index and how it
affects the amount of assistance a state would receive. We use poverty in
lieu of actual enrollments because states vary in terms of the services
provided and eligibility for those services.

22Changes in states' federal matching rates can have a significant effect
on the amount of federal funds available to a state. For example, a 0.25
percent increase in states' federal matching rates for 2004 would have
resulted in a minimum increase in federal funds of more than $0.9 million
in Wyoming and more than $102 million in New York.

Figure 4: Timing of Data Used to Calculate States' Federal Matching Rates
for Fiscal Year 2006

aUnder this strategy, 2001 data would be eliminated from the matching rate
calculation.

To analyze the effect of using fewer years of data to calculate the
matching rates, we used three matching rates that employed the current
statutory formula but varied in the years of data used. The first matching
rate mirrored the current statutory construction, using 3 years of PCI
data that are 3 to 5 years old. The second matching rate was based on the
statutory construction, except that it eliminated the oldest year of PCI
data and only used 2 years of data. The third matching rate used PCI data
for the current year (the year in which the calculations are made) and for
1 year prior, thus showing no time lag in the data used.23 We compared the
three matching rates with year-to-year percentage changes in PCI and
year-to-year percentage changes in the unemployment rate and analyzed the
extent to which the 3-year and 2-year matching rates fluctuated from year
to year. (Appendix III provides additional detail regarding our
methodology.)

Effects

Contrary to our expectations that eliminating the oldest year of data from
the computation of matching rates would make them more sensitive to
current economic conditions, our simulation results showed that using 2
years of PCI data instead of 3 did not consistently improve the
correlation of the rates with state PCI--one measure of state economic
conditions. In addition, rates based on 2 years of PCI data did not result
in rates that more closely correlated with states' PCI trends. We repeated
the same analysis using unemployment data and confirmed that matching
rates also did not correlate with state unemployment trends. These results
remained consistent during the full period of our analysis, 1990 through
2004.

23Although not feasible to implement because of lags in data publication,
we devised this simulated matching rate in order to evaluate whether
changing the years of data used to calculate the matching rate resulted in
a better approximation of states' current economic circumstances.

We found that using 2 years of data would result in larger average
fluctuations in matching rates from year to year than states currently
experience. Our simulation of matching rates from 1990 to 2004 showed that
when rates were computed using 2 years of PCI data instead of 3, the
average percentage point change in rates from year to year increased to
0.44, from 0.39 under current law. A small number of states experienced
substantially larger fluctuations (more than 0.5 percentage points larger)
under this strategy than they currently experience. The effects of these
fluctuations for individual states would depend on whether they
represented a substantial increase or decrease in federal funds. Depending
on the scope of a state's Medicaid program, a 0.5 percentage point
difference in the matching rate would have meant a difference of $1.7
million to $77.1 million in federal matching funds for a given state in
2003.24 In 8 of 14 years, fewer than 22 states would have experienced
larger fluctuations in their matching rates than they experienced under
current law,25 and in 9 of 14 years, fewer than 4 states would have
experienced fluctuations that were more than 0.5 percentage points
larger.26

24These amounts represented 0.08 to 0.29 percent of state own-source
revenues. Also referred to as general revenues from own sources, these
revenues are state and local total receipts, excluding federal
grants-in-aid. We excluded from this analysis the 14 states whose matching
rates in 2003 were at the 50 percent floor or had been established in
legislation. (As we have previously reported, because of the 50 percent
floor, some states receive higher federal matching rates than they would
if their rates were based only on their PCI.)

25Across all of the years of our analysis (1990-2004), the number of
states that would have experienced larger fluctuations under this strategy
than under current law ranged from 17 to 27.

26Across all years, the number of states that would have experienced
fluctuations more than 0.5 percentage points larger under this strategy
than under current law ranged from 0 to 8.

States Could Determine Their Own Needs for Assistance with Medicaid-Specific
Loans or a National Rainy Day Fund

Giving states the option to decide whether and to what extent they need
federal assistance could take the form of a loan, either from the federal
government or from the private capital market (subsidized and possibly
guaranteed by the federal government), or a Medicaid-specific national
rainy day fund. We considered the features of existing intergovernmental
loan programs and state rainy day funds to better understand how these
programs are structured and utilized by states. Implementation of this
strategy would require approval of legislation to authorize a
Medicaid-specific loan program or national rainy day fund as well as
appropriation of federal funds to cover any federal expenditures required
for either the loan program or national rainy day fund. While this
strategy would provide states with greater autonomy over their receipt of
additional federal assistance, their ability to utilize either broad
approach would depend on their debt restrictions, their borrowing costs,
the availability of future state revenues to repay loans, and their
willingness to participate in a Medicaid-specific loan or national rainy
day program. State participation also could depend on the depth and
duration of states' downturns (deep or shallow and short or long) and the
availability of state funds to fill funding gaps. Federal funding required
for this strategy could vary depending on factors such as whether federal
subsidies are included in a loan program or whether a national rainy day
fund includes federal matching funds as well as decisions on the overall
federal budget.

Design Considerations

To identify the factors likely to be involved in designing this strategy,
we considered the features of existing intergovernmental loan programs and
state rainy day funds to better understand how these programs are
structured, how they are utilized by states, and how they could contribute
to a conceptual model of this strategy.27 This strategy draws on the
features of existing programs to inform our understanding of ways to
increase the states' role in determining the timing and targeting of
increased federal assistance to the states during economic downturns. We
analyzed approaches to this strategy based on two broad methods of
providing federal credit: (1) a loan, administered directly from the
federal government or indirectly through the private capital market
(subsidized and possibly guaranteed by the federal government); and (2) a
Medicaid-specific national rainy day fund that could distribute federal
fiscal assistance during an economic downturn. Implementation of one or
more approaches to this strategy would require numerous decisions about
the use, structure, financing, and repayment of a loan or national rainy
day fund. Any new federal loan program would have to comply with the
Federal Credit Reform Act of 1990 requirements that budget authority
sufficient to cover the program's cost to the government be provided in
advance, before new direct loan obligations could be incurred or new loan
guarantee commitments could be made.

27Appendix IV includes background information on selected federal programs
that include intergovernmental loan components.

  Direct Intergovernmental Loans

Congress could authorize a new federal program so that states could borrow
funds directly from the federal government based on a rate-setting and
repayment process specified in law. For example, the law could specify
that rates be determined by the Treasury based partially on Treasury's
borrowing costs. CMS could be designated as the administering agency. This
approach could allow states that might otherwise face high interest rates
in the private capital market access to federal funds that reflect a lower
interest rate subsidy. The administering agency would have to develop a
method to estimate any subsidy costs (e.g., the estimated long-term cost
to the federal government on a net-present value basis of all cash flows
to and from the government, such as interest rate subsidies and defaults
over the life of the loan) in order to conform with the Federal Credit
Reform Act of 1990.28 The administering agency would have to analyze and
control the risk and cost of the program, obtain budget authority and
record outlays to cover the subsidy cost of the program, and could also
specify loan repayment terms. States would have to designate funding
sources to repay the loans.

  Facilitated Private Lending

Under this approach, instead of lending money directly to states, the
federal government could facilitate private lending, such as through a
guaranteed loan.29 The federal government could help offset the risk of
lending money to states by covering all or part of the risk of loan
defaults and by providing an interest subsidy to states. This approach
would enable the federal government to minimize direct involvement with
the loan process by placing the burden of loan administration on
third-party nonfederal lenders. However, the administering agency would
still have to analyze and control the risk and cost of the program and
obtain budget authority to cover the subsidy costs. States would still
have to identify repayment sources. State-managed capital access programs,
in which state governments provide a fixed share of lenders' loan loss
reserves, provide another model for possible consideration and adaptation
to facilitate private lending.

28The Federal Credit Reform Act of 1990, P.L. 101-508, requires that
credit subsidy costs be financed from new budget authority and be recorded
as budget outlays at the time direct or guaranteed loans are disbursed.
Agencies must have appropriations for the subsidy cost before they can
enter into direct loan obligations or loan guarantee commitments. Subsidy
costs include the estimated long-term cost to the federal government on a
net-present value basis of all cash flows to and from the government, such
as interest rate subsidies and defaults over the life of the loan.

29Specific examples of facilitated lending include The Federal Family
Education Loan Program and the Health Center Loan Guarantees.

  National Rainy Day Fund

Legislative approval of a Medicaid-specific national rainy day fund would
allow states to pool their resources to help cope with the increased costs
of Medicaid during economic downturns. We previously found that the
adequacy of states' own rainy day funds is unknown and that choices on
competing priorities would have to be made in a fiscal crisis.30
Furthermore, some states have placed caps and restrictions on the use of
these funds.31 States could capitalize a national rainy day fund in whole
or in part, depending on whether the program design included matching
contributions from the federal government. Determining the amount of money
that each state should pay into a national rainy day fund would present an
additional design challenge, given that state Medicaid programs vary
widely in the population groups and services covered.

Effects

States' decisions about whether to access any new federal Medicaid loans
or a national rainy day fund could depend on the nature of the economic
downturn in terms of when and to what extent states experience increased
unemployment, each state's own resources, and the design features of the
program. States generally have resources available to weather short-term
economic downturns but may be more likely to utilize a loan or national
rainy day fund approach when they are affected by a deeper downturn.
States with a 50 percent federal matching rate could also view federal
loans or a national rainy day fund as an additional tool for increasing
funding on a short-term basis during an economic downturn, filling gaps
created by a matching rate that does not necessarily rise when additional
funds are needed. However, some states also face constraints on their
ability to borrow because of statutory or constitutional debt restrictions
and most states have some form of balanced budget requirements.32
Consequently, states might not be able to take advantage of a loan
program.

30GAO, Welfare Reform: Challenges in Saving for a "Rainy Day",
[67]GAO-01-674T (Washington, D.C.: Apr. 26, 2001).

31GAO, Budgeting for Emergencies: State Practices and Federal
Implications, [68]GAO/AIMD-99-250 (Washington, D.C.: Sept. 30, 1999).

The effects of either a loan or national rainy day fund approach would
also depend on the numerous technical decisions required, including, but
not limited to, interest rates, repayment terms, allowable uses of funds,
borrowing limits, and any requirements governing maintenance of states'
efforts in providing their own funds or Medicaid eligibility. A direct or
guaranteed loan could give states greater autonomy in determining their
need for assistance but would also result in a requirement to repay the
loans (an additional financial burden for states) as they try to recover
from an economic downturn. States would have to consider the availability
of future revenues to repay loans and their borrowing costs, as well as
statutory debt restrictions that could limit their loan access. A national
rainy day fund could allow states to pool risk and thereby spend less than
they would if they chose to establish individual Medicaid rainy day funds
or address economic downturn-related Medicaid cost increases on an
as-needed basis. However, representatives of public policy and research
organizations we contacted cautioned that states may be reluctant to
contribute to a national fund that could be drawn down by other states or
tapped by the federal government. The impact on federal outlays of this
strategy could depend on subsidy costs as well as whether the federal
government provided matching funds for a national rainy day fund. Unless
mandated, state participation in a loan or national rainy day fund would
likely depend on the terms of the program as well as state economic
circumstances.

Concluding Observations

Economic downturns, typically accompanied by increases in unemployment,
can leave states with increased demand for Medicaid program services and
spending, decreased revenues to help states finance the increased demand,
and few strategies for grappling with difficult fiscal circumstances that
will not place them in worse financial positions in the future. Current
federal and state approaches to help states cope with the increased cost
of Medicaid during economic downturns present temporary solutions to a
recurring combination of circumstances. Having an automatic mechanism in
place to address significant downturns in the economy could provide for a
more predictable and targeted response to states' situations. The targeted
supplemental assistance and loan or national rainy day fund strategies
considered in this report illustrate potentially more responsive measures
that could help states adjust to economic downturns similar to the last
three national recessions. However, each also presents challenges.

32 [69]GAO/AIMD-99-250 .

No single strategy or combination of strategies for providing federal
financial assistance could fully meet the varied economic needs of all
states at all times. Any strategy also is inhibited by the lags inherent
in the collection and publication of data, thus limiting its ability to
have a real-time effect. However, the first and third
strategies--targeting supplemental assistance to states most affected by a
downturn and allowing states to determine their own need for assistance
from a national rainy day fund or loan--could potentially better address
some of the difficulties faced by states during downturns in a more timely
and cost-efficient manner than the JGTRRA, which provided assistance to
all states. Additionally, these two strategies are not mutually exclusive
and could be used in combination.

Any strategy to help states cope with increased Medicaid costs during
economic downturns requires trade-offs as Congress seeks to provide
assistance to states that have the greatest financial need and the least
capacity to meet those needs while balancing the federal government's own
long-term fiscal challenges. While none of the strategies may fully
satisfy all dimensions of targeting, timing, and increasing states' own
options, Congress may find one or more of these strategies useful as
starting points in considering whether and how to provide supplemental
Medicaid assistance during the most difficult economic times faced by
states.

Agency Comments

We provided the Secretary of Health and Human Services (HHS) with a draft
of this report. HHS stated that it did not have comments.

As agreed with your offices, we plan no further distribution of this
report until 28 days from its date, unless you publicly announce its
contents earlier. At that time, we will send copies of this report to the
Secretary of Health and Human Services and the Administrator of the
Centers for Medicare & Medicaid Services. We will also make copies
available to others upon request. In addition, the report will be
available at no charge on the GAO Web site at [70]http://www.gao.gov .

If you or your staffs have any questions about this report, please contact
Kathryn G. Allen at (202) 512-7118 or Stanley J. Czerwinski at (202)
512-6806. Contact points for our Offices of Congressional Relations and
Public Affairs may be found on the last page of this report. GAO staff who
made major contributions to this report are listed in appendix V.

Kathryn G. Allen Director, Health Care

Stanley J. Czerwinski Director, Strategic Issues

Appendix I: Objectives, Scope, and Methodology

This appendix describes our objectives and the scope and methodology of
the work we did to address them, including how we illustrated the range of
economic conditions affecting states during economic downturns. We include
a list of the organizations we contacted during the course of our work.

Objectives and Scope

We explored the design considerations and potential effects of strategies
aimed at helping states with their share of Medicaid expenditures during
an economic downturn by (1) targeting supplemental funds to specific
states on the basis of the relative depth and duration of their economic
downturns as well as the extent to which their Medicaid enrollment and
expenditures are likely to increase during a downturn, (2) using 2 years
of per capita income (PCI) data instead of the 3 years of data required by
statute to compute federal matching rates in an attempt to better reflect
states' current economic conditions, and (3) providing states with options
for obtaining assistance from a Medicaid-specific national rainy day fund
or loan based on their own determination of need.

Identifying and Evaluating the Strategies

To address the objectives, we

           o analyzed research, including prior GAO reports and other policy
           proposals, that assessed the effects of economic downturns on
           Medicaid enrollment and expenditures across states, the
           responsiveness of the current Medicaid formula to the effects of
           economic downturns, and differences in Medicaid expenditures
           across states;

           o simulated the potential effects of the strategies to use fewer
           years of data to compute federal matching rates and target
           supplemental federal assistance; and

           o analyzed the features of existing intergovernmental loan
           programs and state rainy day funds as potential models for
           providing states with discretion in determining the timing and
           targeting of assistance through a federal government-sponsored
           Medicaid-specific loan program or rainy day fund.

To evaluate the strategies identified, we

           o conducted statistical simulations of the strategies by comparing
           the actual matching rates in states during recessionary times with
           the matching rates that could exist under the strategies to
           provide targeted supplemental Medicaid assistance and have
           Medicaid matching rates better reflect states' current economic
           conditions,

           o consulted with experts in Medicaid financing issues on our
           targeting simulation in terms of its design and suggestions to
           refine it, and

           o discussed the strategies with key research groups and state
           associations to discern the potential utility of the strategies as
           well as the feasibility of states' implementing different
           strategies.

           Table 4 summarizes the three strategies considered for this
           report. Appendixes II, III, and IV provide additional detail
           regarding the analyses of these strategies.

Table 4: Analysis of Three Strategies to Help States Respond to Increased
Medicaid Costs during Economic Downturns

Goal of strategy     Approach               Analysis                       
Provide targeted     Target supplemental       o Identify design           
supplemental         funds to states based     considerations involved in  
Medicaid assistance  on projected Medicaid     defining national downturns 
                        spending increases and    and distributing            
                        depth and duration of     supplemental federal funds. 
                        economic downturn.        o Estimate amounts states   
                                                  would receive based on      
                                                  economic conditions present 
                                                  during three prior          
                                                  recessions.                 
Have Medicaid        Use 2 years of PCI        o Compare matching rates    
matching rates       data in the statutory     computed using 2 years of   
better reflect       formula used to           PCI data to rates based on  
states' current      compute federal           the 3 years of PCI data     
economic conditions  matching rates.           required under current law. 
                                                  o Analyze extent to which   
                                                  existing matching rates and 
                                                  matching rates based on 2   
                                                  years of PCI data were      
                                                  consistent with states'     
                                                  economic circumstances.     
Provide states with  Allow states to           o Identify considerations   
options to improve   determine whether and     involved in designing loans 
timing and targeting when they need            or a national rainy day     
of increased         increased assistance      fund.                       
Medicaid assistance  in response to            o Identify potential        
                        economic downturns.       effects based on structure  
                                                  and use of existing         
                                                  intergovernmental loan      
                                                  programs.                   

Source: GAO.

Illustrating the Range of Economic Conditions Affecting States during Economic
Downturns

To illustrate the potential ability of each strategy to help states
address increased expenditures during economic downturns, we analyzed how
implementation of each strategy might differ with respect to the varied
economic effects of downturns, including (1) early onset of a shallow
downturn, (2) early onset of a deeper downturn, (3) later onset of a
shallow downturn, and (4) later onset of a deeper downturn. We also
reviewed examples of states whose matching rates generally remained at the
lowest level allowable by federal statute.

Organizations GAO Contacted

We contacted representatives of public policy and research organizations
to (1) gain insights into various issues, such as the extent to which
strategies could help states cope with the Medicaid-related fiscal
consequences of economic downturns; (2) obtain referrals to related
research; (3) validate our selection of strategies; and (4) obtain views
regarding the feasibility and utility of the three strategies, as well as
to discuss the potential effects of these strategies. The organizations we
contacted were as follows:

American Enterprise Institute Cato Institute Center on Budget and Policy
Priorities Heritage Foundation National Association of State Budget
Officers National Conference of State Legislatures National Governors
Association

In addition, we consulted with technical experts from Federal Funds
Information for States and The Urban Institute regarding our simulations
for the strategies to target supplemental Medicaid assistance to specific
states based on the depth and duration of their economic downturns as well
as their Medicaid expenditures and to use 2 instead of 3 years of PCI data
to calculate federal matching rates.

Data and Data Reliability

We obtained and analyzed data on personal income and state population from
the Bureau of Economic Analysis, data on unemployment from the Bureau of
Labor Statistics, and data on Medicaid expenditures from the Centers for
Medicare & Medicaid Services. We discussed our use of these data with
agency officials and reviewed relevant documentation. On the basis of
these efforts and our use of the data to illustrate potential policy
strategies and their simulated effects, we determined that the data were
sufficiently reliable for this report.

Appendix II: Designing a Strategy of Targeted Supplemental Medicaid
Assistance

This appendix describes the design decisions and policy considerations
involved in creating a strategy aimed at targeting supplemental funds to
states based on the extent to which their Medicaid expenses increase
during an economic downturn. This supplemental assistance strategy would
leave the existing Medicaid formula unchanged and add a new, separate
assistance formula that would operate only during times of economic
downturn and use variables and a distribution mechanism that differ from
those used for calculating matching rates. The strategy would require
policy decisions on three basic steps: (1) deciding when to start and stop
the supplemental assistance to states, (2) determining the level of
assistance provided (including defining the formula for distributing
funds), and (3) deciding how to distribute the assistance (principally,
deciding whether assistance should be an incremental increase in federal
matching rates or provided as a lump-sum grant payment). To illustrate
these design considerations, we developed a model to simulate supplemental
assistance. The following sections describe the choices made to simulate
and illustrate the resulting supplemental assistance as well as some
possible alternatives.

Design Considerations for Starting and Stopping Assistance

This section presents information about how we chose unemployment as the
indicator for an economic downturn and how we selected the rules for
starting and stopping the provision of supplemental assistance. We
reviewed how these rules would have applied to the past three recessions
(2001, 1991-1992, and 1981-1983) using our simulation model.

Choice of Unemployment as an Indicator

We used unemployment as the key variable because it reflects the potential
for increases in Medicaid enrollment as a result of an economic downturn.
Although other indicators of economic downturn are widely reported and
important in other contexts,1 experts consider increases in unemployment
to be an indicator of the likely increase in Medicaid enrollments of
adults and children.2 To simulate how supplemental assistance could be
provided, we used Bureau of Labor Statistics (BLS) unemployment data by
state. Monthly BLS unemployment data by state become available with a lag
of less than one quarter.3

1For example, in its retrospective determination of the dates of
nationwide economic peaks and troughs, the Business Cycle Dating Committee
of the National Bureau of Economic Research (a private, nonprofit,
nonpartisan research organization) relies primarily on real gross domestic
product (GDP), real income, employment, industrial production, and
wholesale-retail sales. The Committee views real GDP as the single best
available measure. These data are not all available at the state level.

Use of Unemployment as an Economic Indicator

Ideally, the indicator used should reflect the economic downturn and
exclude other influences such as long-term trends, seasonal influences,
and other shorter fluctuations. In order to minimize the influence of
seasonality and the month-to-month fluctuations on the unemployment data
used in our model simulations, we used a quarterly average of seasonally
adjusted unemployment data for the 12 most recent months.4 Because the
level of unemployment is driven by trends in the structure of a state's
economy, we used increases in unemployment during a period of economic
downturn as our measure of the effects of the economic cycle.5 (The
problem of deciding on a base period from which to calculate those
increases in unemployment was a key issue that is discussed later in this
appendix.) This is an inexact method for isolating the effects of cyclical
downturn on unemployment, especially if the trend should change along with
the economic downturn. For example, if an economic downturn is a
precipitating event that leads to long-lasting declines in a state's
manufacturing industries, at some point the state's increases in
unemployment are attributable to structural change in its economy. When
the increases in unemployment are long term rather than cyclical, this may
be a policy consideration in deciding when to stop the supplemental
assistance.

2Centers for Medicare & Medicaid Services (CMS) data on Medicaid
enrollments would not be useful for this purpose because they reflect both
changes in enrollments due to changes in state policies affecting
eligibility as well as increases in enrollment that are attributable to
economic downturn.

3More specifically, we used monthly, seasonally adjusted unemployment data
and unemployment rates from BLS Local Area Unemployment Statistics by
state.

4Month-to-month fluctuations are dampened by using a quarterly rolling
average of the 12 most recent months, though it also somewhat dampens the
indicator's sensitivity to turns in the economy. However, we retained some
degree of sensitivity by recomputing these 12-month averages for each
quarter. For this strategy, when referring to unemployment or the
unemployment rate, we are referring to the average of the 12 most recent
months.

5More sophisticated statistical methods could perhaps better isolate
cyclical change from trends and other noncyclical factors causing changes.
We chose this quarterly moving average method because it offers greater
simplicity that helps make the assistance formula mechanism easier to
explain and understand.

Alternative Indicators of Downturns and Increases in Medicaid Enrollments

Economists generally prefer indicators other than unemployment to signal
economic downturns. Unemployment sometimes lags behind the cyclical turns
in the economy; it can be both slow to increase when the downturn begins
and slow to return to pre-downturn levels when other indicators show the
economy is recovering. In general, other indicators show an earlier and
briefer downturn than unemployment.

For example, researchers at the Philadelphia Federal Reserve Bank
developed a monthly index of four state economic indicators intended to
coincide with the economic cycle.6,7 Such a broad index of economic
conditions could provide a more reliable and timely indication of a
state's cyclical downturn than unemployment. Furthermore, if the purpose
of supplemental assistance was to include the provision of some
countercyclical stimulus--that is, provide incentives to increase spending
to boost macroeconomic activity--rather than to help states address the
impacts of the downturn on increased Medicaid expenditures, then an
alternative to unemployment as a variable for triggering funding would
have better prospects for providing well-timed assistance.

However, there is some leeway in providing supplemental assistance to
compensate states for the impact of a downturn on their Medicaid
enrollments and spending. According to experts, states have budget
resources and financial management techniques to temporarily sustain them
for a year or two with downturn-driven increases in Medicaid expenditures.
To assist states with the costs of Medicaid enrollment increases, the
relatively brief lags caused by using unemployment rates to trigger
supplemental assistance payments would not present a problem.

Starting and Stopping Supplemental Assistance

Supplemental federal assistance could be set to begin payments to states
when economic evidence shows a significant number of states are in an
economic downturn. For example, when a certain number of states have each
exceeded a specified increase in their unemployment rate, supplemental
assistance could be authorized to begin for the next quarter. A similar
criterion could be used to stop payments. Such a rule could be designed to
provide a high degree of certainty that the nation had entered a downturn
and that states were not all in recovery. For our simulation model, we
chose the rule that payments to states would begin when 23 or more had an
increase in their unemployment rate of 10 percent or more from the
comparable quarter a year earlier, and payments would stop when fewer than
23 states had increases of 10 percent or more.8 We chose 23 states and a
10 percent or more increase in unemployment on the basis of a review of
states' unemployment rates over past economic cycles and made a judgment
that these levels would provide considerable certainty that an economic
slowdown was nationwide. Other thresholds could be selected to tighten or
loosen the parameters to start and stop supplemental federal assistance.

6Theodore M. Crone, "What a New Set of Indexes Tells Us About State and
National Business Cycles," Federal Reserve Bank of Philadelphia Business
Review (2006, Q1): pp. 11-24.

7The National Bureau of Economic Research establishes widely used dates of
the start and end of expansions and contractions of the U.S. business
cycle. These dates are determined retrospectively and would not be
available on a timely basis for use in an automatic trigger.

Automatic Trigger Design Objectives and Issues

An automatic trigger would need to specify several key parameters or rules
that together would control when assistance payments would begin, how long
they would last, and when they would stop. Though the trigger would
control all supplemental assistance payments, it should utilize
state-by-state data rather than national aggregates because it involves
assistance to state Medicaid programs. The trigger should distinguish
between small up-and-down movements in unemployment, which could be
associated with an economy that is basically stagnant, from those
movements that clearly show a state whose economy has entered a downturn.
The trigger must clearly identify the duration of the period of economic
downturn because of the previously mentioned difficulty of separating a
state's trend in unemployment from its cyclical changes. Furthermore, the
design decision should involve consideration of potential risks. A trigger
that is too sensitive could provide more payments than are reasonably
justified by the economic downturn, while a trigger with standards that
are too rigorous would penalize states whose downturns are exceptionally
long-lasting, early or late. Also, an automatic trigger for supplemental
assistance would need to be designed with some degree of simplicity and
transparency.

8This 10 percent threshold is used as a criterion for beginning federal
supplemental assistance to states. As explained later in this appendix, it
does not restrict an individual state's eligibility. In other words, a
state with a 2 percent increase in unemployment would receive assistance,
but its supplemental increase to its matching rate would be smaller.

An Illustrative Automatic Trigger

For our simulation model, state payments would be triggered when 23 or
more states had an increase of 10 percent9 or more in the state's
unemployment rate compared to the same quarter in the previous year, and
payments would stop when those conditions were no longer present. This
trigger consists of three key elements:

           o a threshold number of states (23),

           o a threshold percentage increase in the unemployment rate (10
           percent or more), and

           o a "retrospective assessment" used to derive the percentage
           increase in the unemployment rate compared to the same quarter in
           the previous year.

We chose the two threshold values of 23 states and 10 percent or more to
work in tandem to ensure that when the program starts, the national
economy has entered a downturn and that many states (at least 23 and
probably more) are not yet in recovery.10 We chose both numbers based on a
review of states' unemployment rates over past economic cycles and made a
judgment that these levels would provide considerable certainty that the
economic slowdown was nationwide.

To illustrate the application of this trigger, figure 5 shows the number
of states with a 10 percent or greater increase in their unemployment rate
from the same quarter a year earlier for the period from 1979 through the
third quarter of 2004.11 This period covers three recessions and offers
supplemental assistance as follows:

9This is an increase of 10 percent compared to the unemployment rate for
the same quarter in the previous year and not a 10 percentage point change
in unemployment rates. Unless otherwise specified, all percentage changes
in unemployment or unemployment rates for this strategy are expressed in
terms of a percentage increase over a base quarter, and not percentage
points. (However, supplemental increases to states' matching rates are
reported in percentage points because that is the common way to present
that information.)

10This is the percentage increase in a state's unemployment rate compared
to the same quarter in the previous year (the retrospective assessment).
We do not use the national unemployment rate as a reference point because
many states usually remain well above or below the national unemployment
rate. The use of state-by-state unemployment rates is also appropriate
because supplemental assistance is intended for individual states, whose
Medicaid programs vary.

           o for the 2001 recession, 7 quarters of assistance is provided
           beginning in the first quarter of 2002 and ending as of the fourth
           quarter of 2003;
           o for the 1991-1992 recession, 6 quarters of assistance is
           provided beginning with the fourth quarter of 1991 and ending as
           of the second quarter of 1993; and
           o for the 1981-1983 recession, 11 quarters of assistance is
           provided in two phases, with the first phase beginning in the
           fourth quarter of 1980 and ending as of the second quarter of
           1982, and the second phase resuming assistance in the fourth
           quarter of 1982 and ending as of the first quarter of 1984.

Each recessionary period has different characteristics. For example, the
1991-1992 recessionary period shows a more gradual increase in
unemployment compared to the other recessions--and fewer states are
affected.12

11Note that in all the data displays in this appendix, a 2-quarter
administrative lag is assumed between the date of the increase in
unemployment data and the date the supplemental assistance could be
provided. Such an administrative lag would reflect time for data to become
available, for allocations to be computed, and for other administrative
purposes. For example, on a table or figure showing unemployment for the
third quarter of 2002, those are actually unemployment data as of the
first quarter of 2002, with the difference due to the assumed 2-quarter
administrative lag.

12If the onset of the downturn is very gradual, it is more likely that
fewer states will have the requisite 10 percent increase over the
unemployment rate from the prior year.

Figure 5: Number of States with a 10 Percent or More Increase in Their
Unemployment Rate Compared to the Same Quarter 1 Year Earlier, 1979-2004

Performance of the Automatic Trigger

A rough method of evaluating the performance of the automatic trigger is
the degree to which the period it identifies encompasses states' increases
in unemployment in that period.13 The trigger must delineate a period of
payments that coincides well with most states' increases in the number of
unemployed, in order for the supplemental federal assistance calculated on
the basis of those unemployment increases to also be well targeted.
Overall, about 90 percent of the unemployment increases in the period from
the second quarter of 2000 through the fourth quarter of 2004 are captured
by the time period of the trigger plus the 1-year retrospective assessment
used by the simulation model. When the trigger identifies the start of the
first quarter of the program of supplemental federal assistance, then the
process of computing each state's assistance for that first quarter and
each subsequent quarter of assistance takes place. As part of that
process, the simulation model calculates each state's increase in
unemployment, which is the increase in unemployment compared to the base
quarter. For each state, the base quarter is whatever quarter had the
lowest unemployment within the preceding 4 quarters. Thus, though the
program begins in the first quarter of 2002, it could use states'
increases in unemployment that occurred as early as the first quarter of
2001. Figure 6 shows the sum of states' increases in unemployment over the
previous quarter for the first quarter of 2000 through the fourth quarter
of 2005. While the trigger in the first quarter of 2002 appears late
relative to when some states actually experienced an increase in
unemployment, the simulation model's retrospective assessment captures
much of the preceding unemployment.

13Note that this is an increase in the number of persons unemployed and
not the unemployment rate.

Figure 6: Total of States' Quarterly Increase in Unemployment Covered by
Simulation Model's Supplemental Assistance

Use of Alternative Parameters in the Automatic Trigger

A lower threshold for the increase in the unemployment rate or requiring a
smaller number of states to pass that threshold could trigger supplemental
assistance somewhat sooner and provide more quarters of payments
(especially for states that may enter a downturn much earlier or later
than others). These parameters would also have potential disadvantages:
(1) they could provide less certainty that there has been a nationwide
downturn, and (2) with more quarters of supplemental assistance, the
overall cost could be greater (other things remaining the same).

To show the way in which the threshold parameters included in our
simulation model work together, figure 7 displays the effects of choosing
alternative combinations of these parameters for the period 2000 through
2005. For example, if we use 21 rather than 23 states, supplemental
assistance would be triggered with the same first quarter but last for 8
rather than 7 quarters. Many adjoining cells of the figure have the same
first quarter and number of quarters because small changes in the
threshold parameters may not change when supplemental assistance is
triggered. However, over the broad ranges shown in the figure, the clear
pattern is that lowering the percentage increase or lowering the number of
states generally moves in the direction of an earlier first quarter and a
greater number of quarters of payments.

Figure 7: Effects of Alternative Threshold Parameters on the Start and
Number of Quarters of Supplemental Assistance, 2000 through 2005

Note: Numbers in bold font are those used in GAO's simulation.

The trigger for our simulation is based on the increase in the
unemployment rate over the same quarter of the previous year. Depending on
congressional preferences, the period could instead be longer than 1 year,
or it could be based on the increase from the pre-downturn levels. Because
unemployment is slower to recover than other economic indicators, it may
be a number of years into the national recovery before unemployment rates
return to the levels immediately preceding the downturn. Therefore, the
effect of a longer retrospective assessment would be to provide
supplemental assistance for more quarters and also to provide more
assistance to the states with longer-lasting or late downturns. Using a
shorter period reflects a policy judgment that the program should be
temporary and, in particular, that after 1 year the states should then
adjust their budgets and programs to reflect changed economic
conditions.14

Alternative Ways to Start and Stop Supplemental Assistance

An alternative way to start and stop supplemental assistance is through
legislation. Congress could consider other indicators and criteria to
start or stop assistance with the intention of implementing other policy
objectives. For example, decisions could be made regarding limiting the
number of quarters of payments or stopping payments after spending caps
are reached. Additionally, instead of an automatic trigger, supplemental
assistance could begin when Congress enacted legislation. However,
enacting appropriately funded and timely legislation under the pressure of
worsening national and state economies presents its own challenges.
Studies of the past performance of discretionary federal fiscal policy
actions in response to recession have shown instances of enactment of
belated and inappropriate levels of fiscal stimulus.15 Also, some of the
groups we contacted for this study believed that an "automatic trigger"
based on economic criteria would be the most likely method of implementing
assistance in a consistent and timely manner.16

Determining the Level of Supplemental Assistance

There are three important aspects to determining the level of supplemental
assistance. First, a level of funding must be developed. The level of
funding in our model is based on the average costs to states attributable
to increases in unemployment. Second, the estimates and allocations of
quarterly funding must be consistent with the annual appropriations
process. Third, assistance needs to be targeted to states on the basis of
the impact of increases in unemployment on their Medicaid programs.

14The choices are not merely limited to the choice between a longer and
shorter retrospective assessment. For example, the retrospective
assessment could be a weighted average of long and short periods, with
less weight on the long periods.

15For example, see John Taylor, "Reassessing Discretionary Fiscal Policy,"
Journal of Economic Perspectives, v. 14, n. 3 (Summer 2000): pp. 21-36.

16Congressional action could override any approach in place. For example,
if there were signs of an incipient national economic downturn,
supplemental assistance could be enacted ahead of an automatic trigger.
Alternatively, supplemental assistance could be blocked if funding of
other budget priorities was deemed more important.

Level of Funding

Several studies in the economics literature have estimated a relationship
between changes in unemployment rates and changes in Medicaid spending
while holding constant other factors that influence Medicaid spending.17
While these models cannot provide state-by-state estimates of enrollment
increases, they provide national average estimates from which we can
calculate an average amount of additional federal Medicaid spending per
additional unemployed person. We have chosen to use the estimate of $300
per additional unemployed person derived from a recent econometric study
of the responsiveness of Medicaid enrollments and spending to changes in
unemployment rates and other factors, such as states' spending on certain
Medicaid populations.18 Based on the depth of the 2001 recession, the
amount of federal assistance would have been $4.2 billion.

Funding and the Appropriations Process

Given the difficulties of forecasting the depth and duration of a
downturn, as well as the pace of the recovery, estimating the cost of
supplemental assistance can be difficult. However, within the context of
the overall Medicaid program, the amount of supplemental assistance
provided in our simulation ($4.2 billion) is relatively small--less than 1
percent of total Medicaid spending for a 2-year period. As an open-ended
matching grant that provides states with an incremental increase to their
matching rates, funding may need to be appropriated.19 Similarly,
supplemental assistance designed to provide a lump-sum grant or to be
closed-ended, could also require an appropriation amount. The funding
would need to be apportioned across quarters of the fiscal year in order
to provide proportionately equal treatment between the states that enter a
downturn early and those that enter late, presuming equal treatment is
defined as providing states with equal funding for equal increases in
unemployment and commensurate with state Medicaid populations (all other
factors remaining the same). Past economic data show that the middle
quarters of the supplemental assistance are certain to have much greater
increases in unemployment than the earlier and later quarters (see fig.
5).20 Therefore, a policy of spending until funds are gone would seem to
leave the states with late-starting downturns, or prolonged contractions,
at risk of receiving little or no supplemental funding.

17John Holahan and Bowen Garrett, "Rising Unemployment and Medicaid,"
Urban Institute Health Policy Online (Oct. 16, 2001). This description
somewhat oversimplifies the econometric methods of these studies. For
instance, these studies rely on several estimating equations, and they
also estimate increases in Medicaid enrollments from which the impact on
Medicaid spending is calculated.

18Stan Dorn, Barbara Markham Smith, and Bowen Garrett, Medicaid
Responsiveness, Health Coverage, and Economic Resilience: A Preliminary
Analysis, prepared for the Health Policy Institute of The Joint Center for
Political and Economic Studies (Washington, D.C.: The Joint Center for
Political and Economic Studies, Sept. 27, 2005).

19Open-ended matching grants increase the capacity of state and local
governments to provide services, but because of difficulty in predicting
expenditures, they create a degree of fiscal uncertainty at the federal
level.

Allocation Model

Our simulation model targets funds to states in proportion to the product
of two factors. The first is the state's increase in the number of
unemployed persons in that quarter compared to the number of unemployed in
the base quarter.21 The second factor is a Medicaid spending index
intended to adjust the first factor for the relative size of the states'
Medicaid programs for the nonelderly. The first factor is intended to
gauge the impact of the economic downturn on Medicaid enrollment in the
state. The factor is the amount by which unemployment for the most recent
quarter exceeds the number of unemployed in the base quarter. The base
quarter is the quarter with the lowest number of unemployed in the year
immediately preceding the first quarter in which assistance is triggered.
However, if the state's number of unemployed decreased after the first
quarter, that lowest quarter would then become the base quarter
unemployment. If a state has a decrease in the number of unemployed
compared to the base quarter, it would not receive funding because of a
lack of discernible impact from the economic downturn. However, states
with even small increases in the number of unemployed would receive some
assistance, in proportion to the increase in unemployment.22 We excluded
increases in the number of unemployed that predated this retrospective
assessment. Presumably, such increases would be small and possibly
unrelated to the nationwide economic downturn.

20This variation by quarter is one reason why calculating quarterly
supplemental assistance payments could better target funds than
calculating payments on an annual basis.

21We used the number of unemployed persons rather than the unemployment
rate because state size must be taken into account. Two states with
identical unemployment rate increases may have different increases in
their numbers of unemployed persons. The state with a larger increase in
the number of unemployed persons would have greater resulting Medicaid
spending, assuming everything else remained the same. This increase in the
number of unemployed could be adjusted to take into account the change in
the labor force from the base period. However, we chose not to take this
approach to avoid complicating the simulation model.

The purpose of the second factor is to adjust the number of unemployed for
the relative cost of state Medicaid programs. Two states with an equal
increase in the number of unemployed could have very different increases
in Medicaid expenditures, depending on their rate of Medicaid spending.
The Medicaid index is calculated for each state as its average Medicaid
spending per nonelderly poor person relative to the national average.
Thus, a state whose Medicaid spending per nonelderly person in poverty was
equal to the national average would have an index value equal to one
(1.00). CMS spending data are used to approximate each state's Medicaid
spending for the cyclically sensitive population. Census Bureau data
provide an estimate of adults and children in poverty, who are the
potential beneficiaries of such Medicaid spending. The Medicaid index
factor would not be updated quarterly because it is intended to supply
relative positions of the states and not quarterly impacts of the economic
cycle.23

The Medicaid index varies widely among the states because of differing
Medicaid program characteristics and funding efforts. If Congress did not
want supplemental assistance funding to reflect the full magnitude of
variations in Medicaid spending, constraints could be designed to moderate
this factor, or it could be eliminated from the methodology for allocating
supplemental assistance.

22While states could cope with the impact of small increases in the number
of unemployed, it could be problematic to specify a level of increase that
is small enough for states to cope without federal aid. Furthermore,
because of our inability to separate trends from the effects of economic
cycles, a fast-growing state that has a small increase in the number of
unemployed could claim to be significantly affected by the national
downturn, considering how large its decrease in the number of unemployed
might have been without the downturn.

23CMS does not make these data available frequently enough to permit their
use on a quarterly basis by states. For our simulation model, we used 2003
expenditure data, which were the most recent data available at the time we
did our work.

Deciding How to Distribute Supplemental Assistance

Matching Assistance or Lump-sum Grants

Assistance could be provided either as an incremental increase to states'
federal matching rates or as a lump-sum grant. Representatives of one
organization we contacted preferred matching assistance on the grounds
that it would better ensure maintenance of state contributions to the
Medicaid program, in contrast to lump-sum grant payments that could more
readily allow states to reduce their own Medicaid spending effort and thus
use state funds for other purposes. Supplemental federal assistance as
described in this appendix could be provided as a targeted incremental
increase in each state's matching rate or targeted lump-sum grant to
states. Either approach could provide a state with a comparable amount of
funding.

Calculation of Lump-sum and Matching Assistance Amounts

Supplemental assistance could provide either a lump-sum grant to each
state or a comparable level of funding through an incremental increase in
the state's matching rate. The lump-sum formula would provide funds in
proportion to the state's increase in the number of unemployed, with that
increase adjusted by the index of relative Medicaid cost. The increase in
the Medicaid matching rate is calculated by dividing the lump-sum grant
amount by a state's total Medicaid spending. Thus, if a state left its
Medicaid spending unchanged, it would receive the full assistance amount.

Simulation Model Results

This section highlights results from our supplemental targeted assistance
simulation model for the 1998 through 2004 time span.24 Individual states
vary in different recessions in terms of unemployment levels and
supplemental federal assistance that would result from changes in the
number of unemployed. A state with minimal unemployment increases in one
recession can experience much greater increases in the number of
unemployed in another recession. The widely differing nature of states'
experiences suggests that simulated supplemental assistance is unlikely to
reflect what a particular state would receive in a future economic
downturn.

24Similar targeting was displayed in other recessionary periods. That is,
the targeted assistance was proportional to the increases in unemployment.
In addition, a relatively small number of states (usually different states
in each period) would receive small payments because their recessions
began either earlier or later compared with the national downturn.

Table 5 shows data related to the factors used in the formula and the
resulting supplemental assistance, by state. As shown in table 5, the
average percentage increase in the number of unemployed ranged from 0.1 to
about 80 percent. With a few exceptions, every state would begin receiving
assistance during the first quarter of 2002 and would receive 7 quarters
of payments. The next column shows the Medicaid index used, and the final
two columns show the average increase in each state's matching rate during
the 7 quarters, with and without the Medicaid expenditure index factor.
Because of the importance of the Medicaid expenditure index in determining
assistance (especially to those states with relatively large or small
indexes), we present the assistance computed with and without the Medicaid
factor. In general, the simulated increases in matching rates show the
targeting with respect to the variations in the increases in unemployment
that the formula is designed to provide. This targeting is especially
apparent for the supplemental matching rates that exclude the Medicaid
index. For some states, the Medicaid index is an important determinant of
the supplemental assistance, but much less important to those states whose
index value is closer to the U.S. average of 1.00. For example, table 5
shows that Alaska's average percentage point increase in matching rate
would more than triple by including the Medicaid expenditure index,
increasing from 0.26 to 0.86. In contrast, Oregon's average percentage
point increase in matching rate experienced a minimal change by including
the Medicaid expenditure index, increasing from 1.68 to 1.70.

Table 5: Simulated Supplemental Assistance for Economic Conditions of the
2001 Downturn

                                                           Average   
                                                         percentage  
                                                Index of    point    
                                                Medicaid increase in 
                                            expenditures  matching   
                                                     per    rate     
                   Average                    nonelderly   Excluding   Including 
                percentage Initial   Number    person in    Medicaid    Medicaid 
               increase in payment       of     povertya expenditure expenditure 
State         unemployment quarter quarters (U.S.=1.000)       index       index 
Alabama               22.6  2002Q1        7        0.654        0.65        0.43 
Alaska                 9.8  2002Q1        7        3.272        0.26        0.86 
Arizona               40.9  2002Q1        7        1.078        1.00        1.08 
Arkansas              19.8  2002Q1        7        0.685        0.49        0.33 
California            27.4  2002Q1        7        0.933        0.88        0.83 
Colorado              80.3  2002Q1        7        0.682        2.36        1.61 
Connecticut           68.9  2002Q1        7        1.576        1.12        1.77 
Delaware              16.8  2002Q1        7        2.429        0.34        0.83 
District of           12.7  2002Q1        7        1.553        0.24        0.37 
Columbia                                                                         
Florida               40.2  2002Q1        7        0.705        1.13        0.80 
Georgia               29.2  2002Q1        7        1.059        0.74        0.78 
Hawaii                 8.8  2002Q1        6        2.309        0.27        0.63 
Idaho                 15.1  2002Q1        7        0.852        0.59        0.50 
Illinois              33.8  2002Q1        7        0.813        1.16        0.95 
Indiana               61.0  2002Q1        7        1.075        1.37        1.48 
Iowa                  36.4  2002Q1        7        1.033        0.84        0.87 
Kansas                29.3  2002Q1        7        0.665        1.02        0.68 
Kentucky              30.5  2002Q1        7        0.908        0.74        0.67 
Louisiana             18.7  2002Q1        7        0.581        0.44        0.26 
Maine                 28.4  2002Q1        7        2.589        0.49        1.28 
Maryland              24.0  2002Q1        7        1.467        0.62        0.91 
Massachusetts         67.2  2002Q1        7        1.225        0.85        1.05 
Michigan              57.9  2002Q1        7        0.712        1.57        1.11 
Minnesota             46.5  2002Q1        7        1.948        0.84        1.63 
Mississippi           17.1  2002Q1        7        0.821        0.43        0.35 
Missouri              62.4  2002Q1        7        1.192        1.11        1.32 
Montana                0.1  2002Q4        4        0.675       0.00b       0.00b 
Nebraska              26.0  2002Q1        7        0.973        0.57        0.56 
Nevada                33.5  2002Q1        7        0.703        1.78        1.25 
New Hampshire         51.5  2002Q1        7        1.539        1.01        1.55 
New Jersey            40.8  2002Q1        7        0.735        0.96        0.71 
New Mexico             8.9  2002Q1        7        1.286        0.20        0.26 
New York              28.7  2002Q1        7        1.796        0.34        0.61 
North                 77.4  2002Q1        7        0.915        1.70        1.55 
Carolina                                                                         
North Dakota          16.3  2002Q2        6        0.595        0.39        0.23 
Ohio                  28.5  2002Q1        7        1.041        0.69        0.72 
Oklahoma              39.7  2002Q1        7        0.667        0.98        0.66 
Oregon                39.1  2002Q1        7        1.011        1.68        1.70 
Pennsylvania          26.3  2002Q1        7        1.035        0.57        0.59 
Rhode Island          18.1  2002Q1        7        1.106        0.30        0.33 
South                 53.1  2002Q1        7        0.972        1.17        1.14 
Carolina                                                                         
South Dakota          24.9  2002Q1        7        1.122        0.57        0.64 
Tennessee             27.0  2002Q1        7        1.431        0.53        0.75 
Texas                 34.4  2002Q1        7        0.749        1.16        0.87 
Utah                  61.0  2002Q1        7        0.752        2.20        1.65 
Vermont               41.0  2002Q1        7        1.992        0.55        1.10 
Virginia              69.3  2002Q1        7        0.610        1.77        1.08 
Washington            41.6  2002Q1        7        0.971        1.41        1.37 
West Virginia          6.3  2002Q3        5        1.345        0.16        0.22 
Wisconsin             52.3  2002Q1        7        0.422        1.38        0.58 
Wyoming                8.1  2002Q1        7        1.267        0.27        0.34 

Source: GAO calculations based on BLS, CMS, and Census data.

aExpenditures for categories that would be cyclically sensitive such as
spending for children and nondisabled, nonelderly adults.

bLess than 0.005.

Next are figures showing changes in states' matching rates resulting from
the supplemental assistance and changes in unemployment for selected
states with widely varying economic downturns in order to illustrate
patterns of simulated supplemental assistance in relation to changes in
unemployment. These states provide a broader picture to illustrate the
different economic circumstances that states can experience during the
same economic downturn. On each of the next four figures, the trend line
shows the percentage increase in unemployment from the base quarter and is
plotted with respect to the percentage change in unemployment. The bars
show supplemental matching rate increases, and relate to the increased
matching rate. Figure 8 depicts a downturn in a state that had increasing
unemployment from the first quarter of 2000 and shows an increase in
unemployment that continues through the third quarter of 2004. The bars
show that the supplemental assistance would be responsive to the increase
in unemployment during the 7 quarters the state received the assistance.

Figure 8: Simulated Supplemental Assistance for a State with an Early,
Long, and Deep Economic Downturn

In figure 9, the state experiences a "double dip" with increasing, then
decreasing, and again increasing unemployment. The first increase in
unemployment is 3 years before the start of simulated supplemental
assistance in the first quarter of 2002. The second increase begins in the
second quarter of 2002, so the state misses the first quarter of
assistance entirely, and the assistance received in the second quarter of
2002 would be relatively small. The first increase in unemployment is
relatively small, so it could be considered a transitory economic event
rather than a real economic contraction. By the final quarter in which
supplemental assistance would be provided, unemployment has leveled off.

Figure 9: Simulated Supplemental Assistance for a State with a Relatively
Early, Long-Lasting, and Shallow Downturn

Figure 10 shows a state with a particularly late and short economic
downturn, in which unemployment was leveling off by the final quarter of
the supplemental assistance provided and declining thereafter.
Nevertheless, the state would have received 5 quarters of supplemental
assistance.

Figure 10: Simulated Supplemental Assistance for a State with a Late,
Short, and Shallow Downturn

Figure 11 shows a state with a short and relatively deep recession.
Supplemental assistance would have been provided through 7 quarters of
increased unemployment and would have been phased out about the time when
unemployment peaked.

Figure 11: Simulated Supplemental Assistance for a State with a Short,
Deep Downturn

Appendix III: Designing a Strategy to Better Reflect States' Current
Economic Conditions

This appendix presents additional detail about the development and
analysis of our strategy to use fewer years of per capita income (PCI)
data to compute Medicaid matching rates. As currently constructed, the PCI
data in the Medicaid formula reflect economic conditions that existed
several years earlier.1 The age of the data used to calculate the matching
rate can result in states not receiving a matching rate consistent with
their current economic situation because state PCI for a particular year
becomes available nearly 2 years after the start of the calendar year for
which the data are reported.2 For example, the United States entered a
recession in 2001, but matching rates for 2001 were based on PCI data from
1996 to 1998, when the national economy was expanding. Efforts to use
fewer years of data to calculate the matching rate assume that eliminating
the oldest year of data would more accurately reflect a state's current
economic circumstances. We tested this assumption by analyzing the effects
of using fewer years of data to calculate states' federal matching rates.
To develop and analyze this strategy, we reviewed a similar proposal
published in a 2004 AARP Public Policy Institute report3 and our previous
work on the Medicaid matching formula.4

Overview of Analysis

To analyze the effect of using fewer years of data to calculate the
matching rates, we used three matching rates that employed the current
statutory formula but varied in the years of data used (see table 6). The
first matching rate ("the 3-year matching rate") mirrors the current
statutory construction of the Medicaid matching rate calculation, using 3
years of PCI data that are 3 to 5 years old. The second matching rate
("the 2-year matching rate") is based on the statutory construction,
except that it eliminates the oldest year of data and uses 2 years of PCI
data. The third matching rate ("the simulated matching rate") only uses
PCI data for the current year (the year in which the calculations are
made) and for 1 year prior, thus showing no time lag in the data used.
Although not feasible to implement because of lags in data publication, we
devised the simulated matching rate in order to evaluate whether changing
the years of data used to calculate the matching rate resulted in a better
approximation of states' current economic circumstances.

1For example, the fiscal year 2006 matching rate includes a 3-year average
of PCI data from 2001 to 2003.

2The age of the data used to calculate the matching rate results from both
a data reporting lag and an announcement lag. The reporting lag occurs
because the Bureau of Economic Analysis reports state PCI amounts about 9
to 12 months after the end of a calendar year. For instance, state PCI for
2004 was reported toward the end of 2005. The announcement lag occurs
because matching rates are announced 1 year before the year in which they
become effective. This is referred to as the announcement period, because
it gives states time to plan their budgets based on Medicaid matching
rates for the upcoming fiscal year.

3Vic Miller and Andy Schneider, The Medicaid Matching Formula: Policy
Considerations and Options for Modification, #2004-09, AARP Public Policy
Institute (Washington, D.C.: September 2004).

4GAO, Medicaid Formula: Differences in Funding Ability among States Often
Are Widened, [71]GAO-03-620 (Washington, D.C.: July 10, 2003).

Table 6: Matching Rates Used to Analyze Strategy

                                                    Years of PCI data used to 
                                                      calculate matching rate 
Matching rate Description                                         for 2001 
3-year        Uses 3 years of PCI data, as                       1996-1998 
                 outlined in federal statute                                  
2-year        Removes the oldest year of PCI                     1997-1998 
                 data from the current statutory                              
                 matching rate calculation                                    
Simulated     Uses current year and 1 prior year                 2000-2001 
                 of PCI data to calculate matching                            
                 rate                                                         

Source: GAO analysis using Bureau of Economic Analysis (BEA) PCI data.

We calculated these matching rates for the period from 1990 through 2004,
which covers the last two national recessions.5 We then compared (1) the
annual percentage point changes in the three matching rates with annual
percentage changes in PCI and annual percentage point changes in the
unemployment rate, (2) the simulated matching rate with changes in PCI,
and (3) the 3-year and 2-year matching rates with the simulated matching
rate. Finally, we analyzed the extent to which the 3-year and 2-year
matching rates fluctuated from year to year.

Comparison of Changes in Matching Rates with Changes in PCI and Unemployment

To measure the extent to which the 3-year and 2-year matching rates can
assist states throughout the economic cycle, we did a correlation analysis
that compared the annual changes in matching rates with the changes in
PCI6 and the unemployment rate, two commonly used indicators of economic
performance. A negative correlation coefficient would mean that when
current PCI decreased, matching rates would increase, and vice versa. A
positive correlation coefficient would mean that when the current
unemployment rate increased, matching rates would increase, and vice
versa. For example, it would indicate that the matching rates would
increase assistance provided to the states during an economic downturn.

5The first recession occurred in 1990-1991. The second recession occurred
in 2001.

6State PCIs were deflated using the price index for personal consumption
expenditures from BEA.

Specifically, we examined the correlation between the annual changes in
the 3-year matching rate and the percentage change in PCI and the annual
changes in the 2-year matching rate and the percentage change in PCI. For
the 3-year and 2-year matching rates, to offer states relief during an
economic downturn, the correlation should be negative. In other words, a
decline in PCI would be associated with an increased matching rate.
(Similarly, in an economic upturn the matching rates would decline.)
However, we found that the correlation between the changes in the 3-year
and 2-year matching rates, and the changes in PCI fluctuated (see fig.
12). Changes in current economic conditions were essentially uncorrelated
with changes in matching rates during this time period.7 For example,
while a moderate positive correlation existed in 1990 (+0.54 and +0.47 for
the respective 3-year and 2-year matching rates), the correlation became
negative for both the 3-year and 2-year matching rates 4 years later. For
most years, correlations between 3-year and 2-year matching rates followed
similar patterns, but occasionally they diverged. For example, in 1993,
the 3-year matching rate had a negative correlation (-0.25), while the
2-year matching rate essentially showed no correlation (0.04).
Importantly, during the recession years 1990 through 1991 and 2001, the
correlation coefficients were positive. Therefore, this indicated a
declining current PCI associated with a declining matching rate.
Consequently, the 3-year and 2-year matching rates do not tend to assist
the states during economic downturns.

7However, in fig. 12, positive correlations were more prevalent than
negative correlations.

Figure 12: Correlations of the Changes in the 3-Year and 2-Year Matching
Rates with Changes in PCI

We also examined the relationship between the changes in the 3-year and
2-year matching rates and changes in the unemployment rate. If the
matching rates assisted the states during periods of increased
unemployment, the relationship between the change in matching rates and
the change in the unemployment rate would be positive. In other words,
increases in the unemployment rate would be associated with increases in
the matching rates, and vice versa. Similar to the results with PCI, the
relationship is mixed--in some years, the relationship is positive and in
some it is negative (see fig. 13). In the 1990-1991 recession, the
relationship was negative, indicating that increases in the unemployment
rate were associated with decreased matching rates. In the 2001 recession,
the relationship was positive: increases in unemployment were associated
with increased matching rates.

Figure 13: Correlations of the Changes in the 3-Year and 2-Year Matching
Rates with Changes in the Unemployment Rates

Note: A positive correlation coefficient would show that when unemployment
increased, matching rates would also increase.

Comparison of Changes in PCI with Changes in the Simulated Matching Rate

To assess whether the simulated matching rate provided a better
approximation of states' current economic conditions as measured by
changes in PCI, we did a correlation analysis of the changes in PCI with
the changes in the simulated matching rate, which is based on the current
and prior year's PCI. Comparing changes in PCI with the simulated matching
rates allowed us to assess whether (1) the time lag in the data affected
the correlation between matching rates and changes in PCI or (2) the
construction of the matching rate formula itself affected the correlation
between matching rates and changes in PCI. The correlation between the
changes in PCI and the changes in the simulated matching rate is uniformly
negative during the period from 1990 through 2004 (see fig. 14),
suggesting that the matching formula structure is not the cause of the
mixed relationship.

Figure 14: Correlations of the Changes in the Simulated Matching Rate with
the Changes in PCI, 1990 to 2004

Overall, the changes in the simulated matching rate provided a more
consistent link to changes in states' PCI than did the changes in the
2-year and 3-year matching rates. Decreases in PCI were consistently
associated with increases in the simulated matching rates. Conversely,
increases in PCI were associated with decreases in the matching rates. The
correlation coefficients ranged from -0.79 to -0.31, thus indicating
variations in the strength of the relationship during the time period. The
relationship between matching rates and PCI reflects that the simulated
matching rate is constrained by the 50 percent floor in some states,
whereas changes in PCI do not reflect this constraint.8 This reduces the
correlation. For example, although Connecticut's PCI fluctuated more than
the majority of the states, its matching rate remained at the 50 percent
floor during the entire 1990 to 2004 time period. The number of states
affected by the 50 percent floor during this time period varied from 10 to
12. In addition, the simulated matching rate used a 2-year average of PCI,
whereas the changes in PCI reflected year-to-year differences in PCI. The
matching rate formula also squares PCI, thus reducing the correlation
between PCI and the simulated matching rate. (PCI changes are linear. The
squared PCI values in the simulated matching rate resulted in nonlinear
changes.)

The 2-year PCI average in the simulated matching rate reduced the annual
PCI fluctuations. As a result, the annual correlations between the
simulated matching rate and PCI fluctuated depending on the underlying
volatility of PCI across states.

Comparisons of Changes in the 3-Year and 2-Year Matching Rates with Changes in
the Simulated Matching Rate

We also compared changes in the 3-year and 2-year matching rates with
changes in the simulated matching rate to determine whether a 2-year
matching rate better approximated states' current economic conditions.
Figure 15 shows the annual correlation coefficients of the 3-year and
2-year matching rates compared with the simulated matching rate. A higher
positive correlation coefficient for the 2-year matching rate would
indicate that the 2-year matching rate is more sensitive to changes in
current economic conditions than the 3-year matching rate. The generally
negative correlation indicates that the 3-year and 2-year matching rates
do not track the current economic conditions reflected in the simulated
matching rate. In general, the correlations of the 3-year and 2-year
matching rates with the simulated matching rate were practically identical
during the entire period, 1990 to 2004 (on average, -0.130 and -0.135,
respectively). These correlations fluctuated during the period of analysis
and ranged from -0.58 (1991) to 0.28 (1993). The correlations were
negative during the 1990-1991 recession, indicating that the matching
rates would not have assisted states during this economic downturn.
However, in the 2001 recession, the correlations were essentially zero.

8By statute, the federal share of Medicaid spending ranges from 50 to 83
percent. The 50 percent minimum federal share ("50 percent floor")
reflects a federal commitment to fund at least half the cost of each
state's Medicaid program. For 2006, 12 states received federal matching
rates of 50 percent.

Figure 15: Correlations of the Changes in 3-Year and 2-Year Matching Rates
with the Changes in the Simulated Matching Rate

Note: A positive correlation coefficient would mean that when PCI
increased, matching rates would decrease.

The lack of substantial positive correlations during either recession is
of particular concern because it indicates that when the states are under
the most economic stress, the matching rates for states decline or, at
best, remain on average unchanged. These correlation results occur because
when PCI declines, the 3-year and 2-year matching rates depend upon PCI
data that reflect economic conditions of several years earlier.

Comparisons of 2-Year and 3-Year Matching Rates in Year-to-Year Fluctuations

We analyzed the extent to which the 2-year and 3-year matching rates
differed in year-to-year percentage point changes by comparing annual
differences in matching rates to understand whether a reduction in the
number of years of PCI data in the matching rate formula (from 3 years to
2 years of PCI data) yielded changes that differed from the year-to-year
percentage point changes resulting from the current, statutory matching
rate. We compared year-to-year percentage point changes in matching rates
for the 2-year matching rate and the 3-year matching rate. As expected,
the 3-year PCI average produced a smoother time trend than a 2-year
average. In general, the 2-year matching rates showed slightly larger
year-to-year fluctuations compared with the 3-year matching rates.

Specifically, from 1990 through 2004, we found that

           o 43 percent of the annual changes in 2-year matching rates
           exceeded the changes in the 3-year matching rates,

           o 33 percent of the annual changes in the 3-year matching rates
           exceeded the changes in the 2-year matching rates, and

           o 24 percent of the annual changes were identical (reflecting
           those states at the 50 percent matching rate floor).

(See table 7.)

Table 7: Comparison of States' Year-to-Year Differences in 2-Year and
3-Year Matching Rates, 1990-2004

                        Number of                     Number of Percentage of 
Differences in       instances   Percentage of     instances     instances 
the changes in          2-year       instances        3-year        3-year 
the matching     matching rate 2-year matching matching rate matching rate 
rates                 exceeded   rate exceeded      exceeded      exceeded 
(percentage             3-year 3-year matching        2-year        2-year 
points)          matching rate            rate matching rate matching rate 
1 or more                    7             1.0             0           0.0 
0.5 to less than                                                           
1                           31             4.3            22           3.1 
0.25 to less                                                               
than 0.5                    87            12.2            51           7.1 
Greater than 0                                                             
to less than                                                               
0.25                       182            25.5           165          23.1 

Source: GAO analysis of changes for current 3-year matching rate and
proposed 2-year matching rate.

Notes: Differences represent differences in the absolute-value annual
changes in 3-year matching rates with absolute-value annual changes in
2-year matching rates.

The second and fourth columns represent the number of instances any state
experienced a variation within this range during 1990 to 2004.

The third and fifth columns represent the percentage of states
experiencing a variation within this range between 1990 and 2004.

There were 169 instances with no state differences between the 2-year and
3-year matching rate changes. This lack of variation reflects states whose
matching rates were at the 50 percent matching rate floor and thus had no
annual changes.

In those years in which the 2-year matching rate exceeded the 3-year
matching rate, it occasionally did so by a wide margin. For example, the
2-year matching rates in a few states--in several years--had an annual
change 1 percentage point greater than the annual change in the 3-year
matching rate.9 The changes in the 3-year matching rates never exceeded
the changes in the 2-year matching rates by more than 1 percentage point.

9The standard deviations for the annual changes in the 3-year and 2-year
matching rates, respectively, were 0.52 and 0.60 percent.

Appendix IV: Information on Selected Intergovernmental Loan
Programs and State Rainy Day Funds

This appendix contains information about some of the existing programs we
reviewed to understand the design decisions and policy considerations
involved in a strategy to allow states to determine whether and when to
access increased federal Medicaid assistance in response to economic
downturns. These programs provided a conceptual framework for reviewing
existing design alternatives that could inform consideration of a
potential Medicaid-specific loan or national rainy day fund. We examined
features of existing federal programs that include intergovernmental loan
components.1 In addition, we examined state rainy day funds as well as
prior GAO work to inform our understanding of some of the issues likely to
be involved in creating a Medicaid-specific national rainy day fund.2

Selected Intergovernmental Loan Programs

The Environmental Protection Agency's (EPA) Clean Water State Revolving
Fund (CWSRF) program provides an independent, permanent, low-cost source
of financing for a wide range of efforts to protect or improve water
quality.3 Through the CWSRF, EPA provides annual grants to the states to
capitalize state-level CWSRFs. States must match these EPA grants with a
minimum of 20 percent of their own contributions. States loan their CWSRF
dollars to local governments and other entities for various water quality
projects, and loan repayments are cycled back into the state-level
programs to fund additional projects. In June 2006, we reported that,
since 1987, the 50 states as well as Puerto Rico have used 96 percent
(about $50 billion) of their CWSRF dollars to build, upgrade, or enlarge
conventional wastewater treatment facilities and conveyances. Although the
CWSRF is primarily a low-interest loan program, states can also use it to
refinance, purchase, or guarantee local debt and purchase bond insurance.
States may customize their loan terms, including interest rates (from 0
percent to market rates) and repayment periods (up to 20 years), depending
on the financial and environmental needs of potential borrowers. All
programs are also subject to annual independent financial audits.

1Other loan programs included in our background research were the Student
Loan Program, the Drinking Water Revolving Loan Program, and state Capital
Access Programs. Any new federal loan program would have to comply with
the Federal Credit Reform Act of 1990 requirements that agencies have
budget authority to cover the program's cost to the government in advance,
before new direct loan obligations are incurred and new loan guarantee
commitments are made.

2GAO, Medicaid: Restructuring Approaches Leave Many Questions,
[72]GAO/HEHS-95-103 (Washington, D.C.: Apr. 4, 1995).

3GAO, Clean Water: How States Allocate Revolving Loan Funds and Measure
Their Benefits, [73]GAO-06-579 (Washington, D.C.: June 5, 2006).

The Federal Emergency Management Agency (FEMA) provides Community Disaster
Loans (CDL) to local governments in designated disaster areas that have
suffered a substantial loss of tax and other revenue. The state's governor
requests a presidential declaration of an emergency or disaster through
the FEMA Regional Director. Once the president has made the declaration,
loans can be provided up to a maximum of $5 million. Loans are not to
exceed 25 percent of the local government's annual operating budget for
the fiscal year in which the major disaster occurs. The CDL program
provides for loan forgiveness (cancellation) when it is determined that
the affected government will not be able to repay the loan for 3 fiscal
years following a disaster. A total of 55 CDLs were made from the
initiation of the program in August 1976 through September 30, 2005. Of
the 55 loans made, 36 were paid back in part or in full.4

The Temporary Assistance for Needy Families (TANF) program offers block
grants under which states receive federal funds to design and operate
their own welfare programs within federal guidelines. TANF also offers a
direct loan program to provide assistance to states. This program is
funded though a permanent appropriation of $1.7 billion. States can access
direct loan funds for any purpose for which TANF grants can be used, such
as welfare assistance, but states must repay any loans within 3 years.
However, in 2001, we reported that the TANF loan program is likely the
wrong mechanism to provide assistance during a fiscal crisis because
states are eligible for better financing terms in the tax-exempt municipal
bond market and because officials in some states had indicated that
borrowing specifically for social welfare programs in times of fiscal
stress would not incur popular support.5 No state had applied for a TANF
loan prior to 2005. In 2005, Congress made a TANF loan available to three
states affected by Hurricane Katrina--Alabama, Louisiana, and
Mississippi--and included language stating that penalties would not be
imposed against these states for failure to repay the loan or interest on
the loan.

4The Community Disaster Loan Act of 2005 (CDLA), provided for up to $750
million of disaster funds to be used to subsidize "special" community
disaster loans, up to a total of $1 billion, for local governments to
provide essential services. For purposes of these special loans, the new
law removed the $5 million per loan limit but prohibited their
cancellation. As of May 3, 2006, 59 special CDL applications had been
approved for local governments in Louisiana and 47 for those in
Mississippi, for a total of 106 loans.

5GAO, Welfare Reform: Challenges in Saving for a "Rainy Day,"
[74]GAO-01-674T (Washington, D.C.: Apr. 26, 2001).

Unemployment Insurance (UI), administered by the U.S. Department of Labor
in partnership with the states, provides temporary cash benefits to
eligible workers who become involuntarily unemployed. Eligibility for UI
benefits, benefit amounts, and the length of time benefits are available
are determined by state law, within broad federal guidelines. The UI
system is funded through federal and state taxes levied on employers.
States deposit their taxes with the U.S. Treasury, which maintains one
trust fund with a separate account for each state. States are responsible
for ensuring the solvency of their individual trust funds, which they use
to pay benefits to UI claimants in their states. To ensure solvency,
states may choose to build trust fund reserves during good economic times
so that if unemployment rises they will have reserves sufficient for
paying UI claims without raising taxes or borrowing money from the federal
government. If states have insufficient reserves for paying claims, they
may request a loan from the federal government.6 The federal government
maintains a loan trust fund, which is built up using a portion of the
federal UI tax. The Federal Unemployment Account (FUA) funds loans to
state unemployment compensation programs. If states fail to repay any
loans within the time frame specified in statute,7 the federal taxes on
employers in a state increase each year the debt is not paid. As of July
2006, the FUA had a balance of about $13 billion, and one state had an
outstanding loan totaling about $238 million.8 States utilize the loan
program periodically.

State Rainy Day Funds

According to the National Association of State Budget Officers (NASBO),
almost all states have established rainy day funds as one way to cope with
fiscal constraints that states experience. These fiscal constraints can be
imposed either by law, such as balanced budget requirements and borrowing
restrictions, or by bond markets, which encourage states to provide
funding in advance for particular budgetary uncertainties.9 Without
adequate reserves available to mitigate a fiscal crisis, states without
short-term borrowing capabilities would have little choice but to reduce
spending, increase revenue, or make other short-term budget adjustments.
Even if a state is permitted to borrow short-term to fund unanticipated
needs, the practice may be viewed unfavorably by bond-rating agencies that
establish credit ratings for states and therefore play a role in
determining a state's borrowing costs.

6 They may also choose to increase taxes on employers or raise funds
through other means such as municipal bonds, which potentially offer a
lower interest rate.

7If a state has an outstanding balance on January 1 for 2 consecutive
years, it has until November 10 of the second year to repay the loan.

8These data were the most recent available balances as of Aug. 2006.

State rainy day fund requirements vary in a number of ways.10 Some state
rainy day funds can be used only in years of economic downturn (determined
through formulas) or in the case of a revenue shortfall or a deficit.
State rainy day funds also may include requirements specifying whether
funds can be used for general purposes, agency-specific purposes, or in
the event of natural disasters or other emergencies. States may also
require a minimum rainy day fund balance. The National Conference of State
Legislatures (NCSL) recommends a minimum rainy day fund balance of 5
percent.

9GAO, Budgeting for Emergencies: State Practices and Federal Implications,
[75]GAO/AIMD-99-250 (Washington, D.C.: Sept. 30, 1999).

10NASBO, Budget Processes in the States (Washington, D.C.: January 2002).

Appendix V: GAO Contacts and Staff Acknowledgments

GAO Contacts

Kathryn G. Allen, (202) 512-7118 Stanley J. Czerwinski, (202) 512-6806

Acknowledgments

Major contributors included Assistant Directors Michael Springer and
Carolyn L. Yocom; and Meghana Acharya, Robert Dinkelmeyer, Greg Dybalski,
Nancy Fasciano, Jerry Fastrup, Summer Lingard, Romonda McKinney, Donna
Miller, Elizabeth T. Morrison, and Michelle Sager.

(450407)

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[82]transparent illustrator graphic

www.gao.gov/cgi-bin/getrpt? [83]GAO-07-97 .

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and methodology, click on the link above.

For more information, contact Kathryn G. Allen at (202) 512-7118 or
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Highlights of [84]GAO-07-97 , a report to congressional requesters

October 2006

MEDICAID

Strategies to Help States Address Increased Expenditures during Economic
Downturns

During economic downturns, states may struggle to finance Medicaid, a
federal-state health financing program for certain low-income individuals.
States receive federal matching funds for their Medicaid programs
according to a statutory formula based on each state's per capita income
(PCI) in relation to national PCI. The number of individuals eligible for
Medicaid can increase during downturns as a result of rising unemployment.
GAO previously reported that any federal assistance to respond to
downturns should be well-timed and account for each state's fiscal
circumstances. GAO was asked to consider strategies to help states offset
increased Medicaid expenditures in the event of future economic downturns.

GAO analyzed policy proposals and federal and state strategies to cope
with downturns to identify and develop three potential strategies. GAO
explored (1) targeting assistance to states most affected by a downturn,
(2) using 2 instead of 3 years of PCI data to compute federal matching
rates to more accurately reflect states' economic circumstances, and (3)
giving states the option to obtain assistance based on their own
determination of need. GAO discussed the strategies with experts,
identified design considerations, and analyzed each strategy's potential
effects.

The Department of Health and Human Services received a draft of this
report and did not comment.

No single strategy or combination of strategies can meet the varied
economic needs of all states at all times, but one or more of the
following strategies GAO analyzed may be useful for Congress as it
deliberates how to help states cope with Medicaid expenditure increases
during economic downturns. Any potential strategy would need to be
considered within the context of broader health care and fiscal
challenges, including continually rising health care costs, a growing
elderly population, and Medicaid's increasing share of the federal budget.

Supplemental federal assistance provided to states based on changes in
states' unemployment rates would target funds to states most affected by
downturns. GAO used unemployment as the key variable because it reflects
the potential for increases in Medicaid enrollment resulting from an
economic downturn. GAO created a simulation model to illustrate this
strategy, which also adjusts the amount of funding relative to each
state's per person spending on Medicaid services. The model captured about
90 percent of states' increases in unemployment during 2001, and all
states would have received some federal assistance. A few states with
relatively earlier or later increases in unemployment would not have
received a commensurate amount of funding because a portion of their
downturns was outside the period of the simulation.

Using 2 years of PCI data to compute federal matching rates instead of the
3 years required under current law did not result in matching rates that
consistently reflected current economic circumstances, as measured by PCI
or changes in states' unemployment. Under certain conditions, reducing the
number of years of data also skewed rates farther from current economic
conditions. This strategy would also result in greater annual fluctuations
in matching rates for most states. For these reasons, eliminating 1 year
of PCI data is not a feasible alternative to help states address increased
Medicaid expenditures.

States could be given the option to decide whether and to what extent they
need federal assistance, through a loan, either from the federal
government or from the private capital market (subsidized and possibly
guaranteed by the federal government), or a Medicaid-specific national
"rainy day" fund. This strategy's viability would depend on states'
willingness to pay into a national fund or assume additional
Medicaid-specific debt and on states' accepting the terms of the loan or
rainy day fund. Federal funding required for this strategy would vary
depending on design factors such as whether federal loan subsidies or
Medicaid rainy day matching funds are included.

References

Visible links
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  62.http://www.gao.gov/cgi-bin/getrpt?GAO-03-620
  63.http://www.gao.gov/cgi-bin/getrpt?GAO/HEHS-95-103
  64.http://www.gao.gov/cgi-bin/getrpt?GAO-04-736R
  65.http://www.gao.gov/cgi-bin/getrpt?GAO-03-191
  66.http://www.gao.gov/cgi-bin/getrpt?GAO-03-620
  67.http://www.gao.gov/cgi-bin/getrpt?GAO-01-674T
  68.http://www.gao.gov/cgi-bin/getrpt?GAO/AIMD-99-250
  69.http://www.gao.gov/cgi-bin/getrpt?GAO/AIMD-99-250
  70.http://www.gao.gov/
  71.http://www.gao.gov/cgi-bin/getrpt?GAO-03-620
  72.http://www.gao.gov/cgi-bin/getrpt?GAO/HEHS-95-103
  73.http://www.gao.gov/cgi-bin/getrpt?GAO-06-579
  74.http://www.gao.gov/cgi-bin/getrpt?GAO-01-674T
  75.http://www.gao.gov/cgi-bin/getrpt?GAO/AIMD-99-250
  76.http://www.gao.gov/
  77.http://www.gao.gov/
  78.http://www.gao.gov/fraudnet/fraudnet.htm
  79. file:///home/webmaster/infomgt/d0797.htm#mailto:[email protected]
  80. file:///home/webmaster/infomgt/d0797.htm#mailto:[email protected]
  81. file:///home/webmaster/infomgt/d0797.htm#mailto:[email protected]
  83.http://www.gao.gov/cgi-bin/getrpt?GAO-07-97
  84.http://www.gao.gov/cgi-bin/getrpt?GAO-07-97
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