Credit Reform: Current Method to Estimate Credit Subsidy Costs Is More Appropriate for Budget Estimates Than a Fair Value Approach
Published: 2016-01-29T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: Federal direct loans and loan guarantees outstanding have nearly doubled from $1.5 trillion at the end of fiscal year 2008 to $2.9 trillion at the end of fiscal year 2014. For the past several years, concerns have been raised by some experts both in and out of the federal government that FCRA may understate credit program subsidy costs. Some of these experts have suggested that FCRA be modified with an approach—referred to as the fair value approach—to include certain market risk not currently considered under FCRA.
GAO was asked to examine the budgetary treatment of the cost of federal credit programs. This report addresses (1) whether trends exist in subsidy cost reestimates and what factors, if any, help explain any significant trends in reestimates and (2) the implications of using the fair value approach to estimate subsidy costs in the budget and whether GAO believes such concepts should be incorporated into subsidy cost estimates for the budget.
GAO analyzed reestimate data from fiscal years 2001 to 2014 as reported in the President's Budgets and conducted interviews with 30 experts.
section_title: What GAO Found
paragraphs: The Federal Credit Reform Act of 1990 (FCRA) requires agencies to estimate the cost to the government of extending or guaranteeing credit. This cost, referred to as subsidy cost, equals the net present value of estimated cash flows from the government (e.g., loan disbursements and claim payments to lenders) minus estimated cash flows to the government (e.g., loan repayments, interest payments, fees, and recoveries on defaulted loans) over the life of the loan, excluding administrative costs. Discount rates that reflect the federal government's cost of financing are used to determine the net present value of estimated cash flows. Agencies generally update—or reestimate—subsidy costs annually to reflect both actual loan performance and changes in expected future loan performance.
Based on GAO's analyses of credit program reestimates for direct loans and loan guarantees obligated or committed from fiscal years 2001 through 2014 and considering various factors to identify trends, GAO did not identify any overall consistent trends in under- or overestimates of subsidy costs across federal credit programs government-wide. Overall, both direct loan and loan guarantee programs government-wide underestimated costs by $3.1 billion and $39.0 billion, respectively, over the 14-year period. These amounts represent less than 1 percent of the amounts disbursed or guaranteed during the period. Annual reestimates fluctuated from year to year, indicating both under- and overestimates of subsidy costs. Further, significant lifetime reestimates could generally be explained by specific events affecting a few large programs. For example, the Department of Housing and Urban Development's Mutual Mortgage Insurance Program reported underestimating costs over this period because of a variety of factors, including long-term housing prices and interest rate changes stemming from the mortgage and financial crises in the late 2000s.
While subsidy cost estimates under the fair value approach may provide useful information to decision makers for evaluating the costs against the benefits of credit programs, GAO does not support the use of the fair value approach to estimate subsidy costs for the budget. Proponents of the fair value approach have asserted that beyond the cash flows associated with a direct loan or loan guarantee, costs are imposed on taxpayers who would, in a similarly risky private market transaction, require compensation for bearing the risk associated with making the loan or guarantee. Taxpayers as investors with diversified portfolios would still demand compensation, or a premium, for bearing the risk that the macroeconomy—the national or global economy—may falter. This risk—referred to as aggregate risk (a portion of overall market risk)—arises from the possibility of significant economic downturns, when even a well-diversified portfolio of financial investments will decrease in value. To incorporate the cost of bearing aggregate risk into subsidy cost estimates for the budget, the fair value approach adds an aggregate risk premium to the discount rate used in FCRA calculations, which is based on interest rates of Treasury securities. Including the aggregate risk premium incorporates a noncash cost into the subsidy cost estimate. The actual cash flows to and from the federal government associated with a credit program are the same under the fair value approach and FCRA. The debate over the fair value approach rests on whether the cost associated with aggregate risk should be considered in the subsidy cost estimates for the budget of the federal government.
Reflecting a different concern, some proponents of the fair value approach cited as motivation the perceived overreliance on federal credit programs as a policy tool and the desire to correct any bias toward underestimates of costs under FCRA. Raising the subsidy cost would likely result in fewer loans being made. In contrast, some proponents of FCRA stated that any overreliance on credit programs should be addressed as a policy decision, and that to the extent that agencies were underestimating subsidy costs under FCRA, improvements in the subsidy estimation process should be pursued.
The additional market risk recognized under the fair value approach does not reflect additional cash costs beyond those already recognized by FCRA. The introduction of market risk into subsidy costs under the fair value approach would (1) be inconsistent with long-standing federal budgeting practices primarily based on cash outlays; (2) be inconsistent with the budgetary treatment of similarly risky programs; (3) introduce transparency and verification issues with respect to inclusion of a noncash cost in budget totals; and (4) involve significant implementation issues, such as the need for additional agency resources. Consequently, GAO does not support the use of the fair value approach to estimate subsidy costs for the budget and believes the current FCRA methodology is more appropriate for this purpose as it represents the best estimate of the direct cost to the government and is consistent with current budgetary practices.
section_title: What GAO Recommends
paragraphs: GAO supports maintaining the current FCRA method for estimating credit subsidy cost for the budget and therefore is not making any recommendations. The Congressional Budget Office and the Office of Management and Budget provided technical comments on a draft of this report, which have been incorporated as appropriate.

section_title: Letter
paragraphs: The federal government uses credit programs that extend direct loans  and loan guarantees as tools to support specific social and public policy  objectives, such as those for housing, education, and small businesses.  Twenty-five years ago, the enactment of the Federal Credit Reform Act of  1990 (FCRA) changed the method used to budget for the cost of federal  credit programs. Before fiscal year 1992, when FCRA took effect, the  cost of credit programs was recorded in the budget on a cash basis (the  expected amount of cash paid out minus the cash received in a given  year). As a result, the budget cost associated with a loan guarantee was  not recorded until a default occurred, which may have been many years  after the guarantee was made. Further, direct loans appeared to cost the  same as grants because the total amount of a loan was recorded as a  cost when the loan was made and loan repayments were not recorded  until the year received. Under FCRA, the budget records the federal  government’s estimated net long-term cost—referred to as the subsidy  cost—in the year the direct loan or loan guarantee is made. Agencies  generally update—or reestimate—these subsidy costs annually to reflect  both actual loan performance and changes in expected future loan  performance, which could be based on economic changes.
For the past several years, concerns have been raised by experts both in  and out of the federal government that subsidy costs may be  underestimated under FCRA procedures. Some of these experts have  suggested that FCRA be modified to include an approach—referred to as  the fair value approach in this report—that would account for certain  market risk not currently considered in FCRA subsidy cost estimates.  Specifically, taxpayers as investors with diversified portfolios would still  demand compensation, or a premium, for bearing the risk that the  macroeconomy—the national or global economy—may falter. This risk— referred to as aggregate risk (a portion of overall market risk)—arises  from the possibility of significant economic downturns, when even a well- diversified portfolio of financial investments will decrease in value. The  fair value approach would increase initial subsidy cost estimates for direct  loan and loan guarantee programs because of the added market risk. As  a result, because of the higher estimated initial subsidy cost, less federal  credit would be available, assuming the same level of spending was  provided for in the budget. Other experts, both in and out of the federal  government, did not agree that the fair value approach would be  beneficial in estimating credit subsidy costs for the budget.
Since the 2008 financial crisis, the amount of federal credit outstanding,  consisting of direct loans and loan guarantees, has nearly doubled from  $1.5 trillion at the end of fiscal year 2008 to $2.9 trillion at the end of fiscal  year 2014. In light of this growing portfolio of outstanding direct loans and  loan guarantees, as well as concerns about underestimates of subsidy  costs and the suggestions to modify FCRA, you asked us to review  issues related to the budgetary treatment of the cost of federal credit  programs. Our objectives were to determine (1) the extent to which trends  exist in the size and direction of subsidy cost reestimates across, or  within, federal credit programs and, based on this analysis of reestimates,  what factors, if any, help explain any significant trends in reestimates and  (2) the implications of using subsidy cost estimates developed under the  fair value approach in the budget and whether we believe such concepts  should be incorporated into subsidy cost estimates for the budget. Also  at your request, we will issue a follow-up report addressing the factors  agencies should consider when developing subsidy cost estimates and to  what extent selected agencies are using those factors.
To analyze trends in subsidy cost reestimates, we used direct loan and  loan guarantee reestimate data for fiscal years 2001 through 2014, which  are reported in the fiscal years 2003 through 2016 President’s Budgets as  presented in the Federal Credit Supplement. We categorized these  programs by seven loan purposes (e.g., housing or education) and by the  type of budget spending. We examined reestimate trends by agency,  program, purpose, cohort fiscal year (the fiscal year of obligation for direct  loans or commitment for loan guarantees), and the type of budget  spending (discretionary or mandatory). We focused on identifying trends  in lifetime reestimate amounts, annual reestimate amounts, and a  comparison of original subsidy rates to reestimated subsidy rates. We  encountered some limitations with the data reported in the President’s  Budgets, which we individually evaluated based on professional  judgment. For each data limitation, we adjusted the data, identified  alternative data calculation methods when available, or determined that  the data were reliable for our purposes. Our conclusions about possible  trends were based on our professional judgment in assessing the data  and not based on a statistical analysis. To evaluate implications of using  subsidy cost estimates developed under the fair value approach for the  budget, we reviewed literature related to FCRA, the purpose and uses of  the federal budget, and the fair value approach. We also conducted  semistructured interviews with 30 individuals with expertise in one or  more of the following: FCRA; financial economics; and federal budgeting,  auditing, and accounting. See appendix I for additional details on our  scope and methodology.
We conducted this performance audit from June 2014 to January 2016 in  accordance with generally accepted government auditing standards.  Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives.
subsections: section_title: Background
paragraphs: Federal credit programs provide assistance to borrowers through two  principal methods: direct loans and loan guarantees. Direct loans are a  disbursement of funds by the government to a nonfederal borrower under  a contract that requires the repayment of such funds with or without  interest. Loan guarantees are any guarantees, insurance, or other  pledges with respect to the payment of all or a part of the principal or  interest on any debt obligation of a nonfederal borrower to a nonfederal  lender. As shown in figure 1, since the 2008 financial crisis, the amount  of federal direct loans and loan guarantees outstanding has nearly  doubled from $1.5 trillion at the end of fiscal year 2008 to $2.9 trillion at  the end of fiscal year 2014.
As of September 30, 2014, 21 federal agencies reported that they had  direct loans or loan guarantees outstanding. As shown in figure 2, the  Department of Education (Education) (largely through its direct student  loan program) and the Department of Housing and Urban Development  (HUD) (largely through its single-family mortgage guarantee program)  held the largest share of federal direct loans and loan guarantees  outstanding, respectively.
subsections: section_title: The Federal Credit Reform Act of 1990
paragraphs: Prior to the enactment of FCRA, credit programs—like most other federal  programs—were recorded in budgetary accounts on a cash basis (the  expected amount of cash paid out minus the cash received in a given  year). Because a loan guarantee does not require a cash outlay at the  time the guarantee is issued, guarantees initially appeared to be of no  cost to the federal budget; conversely, because the entire amount of a  direct loan is disbursed and recognized as a budget cost when the loan is  made, the cost of direct loans was recorded the same as grants in the  federal budget. Both were inaccurate and provided policymakers with  distorted information for comparing credit programs to noncredit programs  and to each other. This created a bias in favor of loan guarantees over  direct loans because loan guarantees appeared to be less expensive than  direct loans regardless of the actual lifetime cost to the government.
FCRA was enacted with the intent of improving the accuracy of the cost  of federal credit programs reported in the budget by requiring agencies to  measure the government’s net long-term cost of federal credit programs  to permit better cost comparisons both among credit programs and  between credit and noncredit programs. The policies enacted under  FCRA, sometimes referred to simply as credit reform, recognized that the  actual cost of a direct loan or loan guarantee was not captured by its cash  flows in any one year, but rather is the net present value—worth in terms  of money paid immediately—of its cash flows over the life of the loan.  Therefore, FCRA specified an approach using estimates of expected  cash flows, including future loan repayments and defaults as elements of  the cost to be recorded in the budget.
section_title: Subsidy Cost Estimates and Reestimates
paragraphs: FCRA requires agencies to estimate the cost to the government of  extending or guaranteeing credit. This cost, referred to as subsidy cost,  equals the net present value of estimated cash flows from the  government minus estimated cash flows to the government over the life of  the loan and excluding administrative costs. This approach puts direct  loans and loan guarantees on an equal footing in terms of cost in the  federal budget and permits the costs of credit programs to be compared  with each other and with the costs of noncredit programs. Figure 3  illustrates the types of cash flows that affect the subsidy cost for direct  loans and loan guarantees. If the present value of estimated cash  outflows exceeds cash inflows, there is a subsidy cost. If the present  value of estimated cash inflows exceeds cash outflows, there is a  negative subsidy cost, referred to as subsidy income.
To calculate subsidy costs, agencies begin by estimating the expected  cash outflows and inflows over the life of the loans for each cohort of  direct loans obligated or loan guarantees committed in the cohort year.  Agencies use historical information and various assumptions, including  the probabilities of default, borrower prepayments, or recoveries, and the  projected timing of these events, to make informed predictions about  expected future cash flows. These expected cash flows are then  discounted to the point of loan disbursement to determine the net present  value. A credit subsidy rate—the cost per dollar of credit assistance—is  then determined by dividing the subsidy cost by direct loan obligations or  loan guarantee commitments estimated to be made in that year.
The subsidy cost represents the net present value cost of making or  guaranteeing new loans and is included in the President’s Budget. FCRA  requires that agencies have budget authority to cover a program’s  subsidy cost to the government in advance—before new direct loan  obligations are incurred and new loan guarantee commitments are made.
The subsidy cost of credit programs may be categorized as either  discretionary or mandatory. Discretionary spending is provided for  through annual appropriations acts, typically in definite amounts.  Mandatory spending, however, is provided for in laws other than  appropriations acts. Often, these mandatory programs are entitlement  programs wherein the Congress controls spending indirectly by defining  eligibility and setting payment rules, with indefinite budget authority  provided by law to pay for the entitlements of all qualifying beneficiaries.
The data used for budgetary subsidy cost estimates are generally  updated—or reestimated—annually after the end of the fiscal year to  reflect actual loan performance and to incorporate any changes in  assumptions about future loan performance. Reestimates that increase  subsidy costs are referred to as upward reestimates (an agency would  need additional funds), while reestimates that decrease subsidy costs are  referred to as downward reestimates (an agency would return funds).  Regardless of whether the credit programs are discretionary or  mandatory, agencies do not need to request additional appropriations to  cover upward reestimates because FCRA provides permanent indefinite  budget authority for this purpose. Accordingly, an upward reestimate  does not use up room under any discretionary spending caps and a  downward reestimate does not “free up” room under such caps.
section_title: Program and Financing Accounts under FCRA
paragraphs: FCRA established a special budgetary accounting system to record the  cash flows and budget information necessary to implement credit reform.  Direct loans and loan guarantees made on or after October 1, 1991—the  effective date of credit reform—use program and financing accounts to  handle credit transactions (see fig. 4). The program account is included  in budget totals, receives appropriations for the subsidy cost of a credit  program, and records the budget authority and outlays for these costs.  The program account is used to pay the associated subsidy cost to the  financing account when a direct or guaranteed loan is disbursed. The  financing account, which is nonbudgetary, is used to (1) collect the  subsidy cost from the program account, (2) borrow from the Department  of the Treasury (Treasury) to provide financing for loan disbursements,  and (3) record the cash flows between the government and the borrower  or lender associated with direct loans or loan guarantees over the life of  the loan. These cash flows include loan disbursements, default payments  to lenders, loan repayments, interest payments, recoveries on defaulted  loans, and fee collections.
section_title: Discount Rates under FCRA
paragraphs: When calculating the net present value of expected cash flows, FCRA  requires that discount rates be based on interest rates of marketable U.S.  Treasury securities with similar maturities as the cash flows being  discounted. In addition, FCRA requires that the rate of interest charged  on financing account transactions with Treasury be the same as the final  discount rate used to calculate the net present value of cash flows when  estimating the subsidy cost of a credit program. Figure 5 illustrates how  the discount rate would affect the value of future loan repayments and the  subsidy cost for a direct loan.
The final discount rate for a cohort of direct loans or loan guarantees is  determined based on interest rates of Treasury securities prevailing  during the period when the loans are disbursed. Specifically, once a  cohort of loans is substantially disbursed (at least 90 percent), the final  discount rate for that cohort is determined, and this rate is used to  calculate reestimates of subsidy costs and for financing account interest  calculations. Using the same rate for reestimates and interest on the  financing account ensures that the financing account will break even over  time as it uses its collections to repay its Treasury borrowing. As a result,  the discount rate reflects the federal government’s actual borrowing cost  and incorporates into the subsidy cost calculation an agency’s cost of  financing its lending. For loan guarantee programs, which may or may not  borrow from Treasury, the financing account receives the subsidy cost  from the program account and holds these funds to serve as a reserve  against future loan guarantee defaults or other costs. FCRA requires that  these funds—referred to as uninvested funds—earn interest from  Treasury at the same rate as the discount rate used to calculate the  present value when estimating the subsidy cost. The Office of  Management and Budget (OMB) provides tools for agencies to use to  discount estimated cash flows and calculate interest on financing account  balances.
section_title: Fair Value Approach and the Current Basis of the Budget
paragraphs: For several years, the Congressional Budget Office (CBO) and others  have raised the concern that FCRA subsidy cost estimates recorded in  the budget underestimate the costs of federal credit programs and do not  completely reflect the costs imposed on taxpayers. Some have suggested  revising FCRA to include in the subsidy cost an additional estimated cost  related to certain market risk. This suggestion has been referred to as the  fair value approach and centers around the debate that beyond the cash  flows associated with the direct loan or loan guarantee, which are  recognized under FCRA, costs are imposed on taxpayers who would, in a  similarly risky private market transaction, require compensation for  bearing the aggregate risk associated with making the loan. However, it  is important to note that this cost to the taxpayer does not represent a  monetary cost to the government as it is not a cash outlay by Treasury.
Instead, it can be thought of as representing a noncash social cost of  federal lending.
CBO has provided information on fair value estimates to aid  congressional decision making regarding the value of resources being  devoted to federal credit programs for several years. In a 2004 report,  CBO initially laid out the conceptual foundation for the fair value approach  and subsequently issued several more reports more fully examining the  implications of using the fair value approach in the decision-making and  the budget process. In a 2014 testimony, CBO compared and  contrasted the use of the fair value approach versus FCRA in informing  decisions and in budget formulation and execution, laying out advantages  and disadvantages of each method. At present, CBO provides  congressional budget committees with cost estimates for credit programs  using both the fair value approach and the FCRA methodology.
The term fair value in the context of suggested revisions to FCRA subsidy  costs is similar in concept to its use in private-sector generally accepted  accounting principles (GAAP) for financial accounting; however, there are  differences in how the two would be applied. The fair value approach  discussed in this report relates to budgeting for federal credit programs,  while the term “fair value” under private-sector GAAP applies to the  valuation of certain assets and liabilities of private-sector entities and is  defined as the price that would be received to sell an asset or paid to  transfer a liability in an orderly transaction between market participants. In  a general sense, the “fair value” label for federal budgeting purposes  suggests a parallel between federal and private-sector notions of  appropriate compensation for making loans. The label “fair value” reflects  the perspective that this compensation—the risk premium—that  taxpayers demand can be found by observing what they would require to  make similarly risky investments in private financial markets. That view  provides the analogue to the situation contemplated in private-sector  GAAP fair value.
The federal budget has for decades represented a system of cash  accounts. FCRA, therefore, was designed to put credit programs on the  same plane as noncredit programs: FCRA reflects only the cost  associated with estimated cash flows between the government and the  borrower or lender, such as repayment of principal, payments of interest  and fees, and claim payments to lenders. All federal programs, including  those for spending programs or tax provisions whose cash costs appear  in the budget, also have associated noncash costs and benefits that  accrue to society at large. However, these noncash costs and benefits  are not included in the budget. Accordingly, budget decisions demand  trade-offs beyond just the cash cost; such decisions need to also consider  noncash costs and benefits. For example, a project supported by federal  spending could reduce unemployment—while at the same time result in  detrimental environmental effects. Because the federal budget was not  envisioned to present a complete picture of the total costs and benefits to  society of government programs and policies, it should not be used as the  sole rationale for federal activities. Specifically, OMB guidance in Circular  No. A-94, Guidelines and Discount Rates for Benefit-Cost Analysis of  Federal Programs, directs agencies to perform program evaluations,  including consideration of social costs and not just the costs to the federal  government. The compensation cost to taxpayers of making risky  investments, grants, or loans would be a noncash social cost considered  in performing benefit-cost analysis.
A fuller examination of the fair value approach, including the nature of the  social, noncash costs and the arguments for and against their inclusion in  the budget, is presented later in this report.
section_title: No Overall Consistent Trends Identified in Under- or Overestimates of Subsidy Costs, and Various Economic and Portfolio Changes Caused Certain Significant Reestimates
paragraphs: We analyzed direct loan and loan guarantee programs’ annual and  lifetime reestimates from fiscal years 2001 through 2014 by cohort,  program, agency, and purpose to identify any trends. We also  considered whether a program’s funding was discretionary or mandatory.  Our analysis considered many factors, including magnitude of  reestimates, consistency in reestimate patterns over time, as well as the  number of programs with either upward or downward reestimates. Based  on our analyses of these factors related to reestimate data for the fiscal  years 2001 through 2014 cohorts, we did not identify any overall  consistent trends in under- or overestimates of subsidy costs across  federal credit programs government-wide. However, there were some  programs with significant upward or downward reestimates, which could  generally be explained by specific events. For example, the 2008 financial  crisis likely contributed to upward annual reestimates for housing, small  business, and agriculture loan guarantee programs because borrowers’  ability to repay weakened with rising unemployment and falling market  revenue. Unless otherwise noted, the amounts discussed in this section  are based on information reported by OMB in the President’s Budgets.  See appendix II for additional detailed reestimate trend information.
subsections: section_title: No Clear Overall Trends in Subsidy Cost Reestimates across Federal Credit Programs Government- Wide
paragraphs: Based on our analysis of reestimates for fiscal years 2001 through 2014  cohorts, we found that through fiscal year 2014, both direct loan and loan  guarantee programs had net lifetime upward reestimates, meaning that  original subsidy costs were underestimated. However, in concluding  about overall trends, we considered many factors, including magnitude of  reestimates, consistency in reestimate patterns over time, as well as the  number of programs with either upward or downward reestimates. Based  on our analyses of these factors related to reestimate data for the fiscal  years 2001 through 2014 cohorts, we did not identify any overall  consistent trends in under- or overestimates of subsidy costs across  federal credit programs government-wide.
Reestimates provide information to improve the estimation process and  yield insights into program performance. For example, upward  reestimates could indicate that borrowers are delinquent in repaying  loans, and as a result, loan performance is worse than initially expected.  Reestimates take into account actual loan performance and expected  changes in future loan performance, which can both vary because of  portfolio changes (e.g., changes in the credit-worthiness of borrowers)  and changes in the economy—external events that affect borrower  behavior. Reestimates of subsidy costs are to be expected as loan  cohorts age and as the economy deviates from the paths assumed when  subsidy costs were originally estimated. When estimating or reestimating  subsidy costs, agencies must respond to changes in their credit program  portfolios and the economy. While forecasting future loan performance  can be challenging, the goal is to avoid consistent bias, reflected in either  recurring upward or downward reestimates. Consistent bias in forecasting  loan performance would result in subsidy cost estimates that provide  misleading information about program performance. At the same time, a  period of recurring overestimates or underestimates does not necessarily  mean that the original estimates were biased. A particularly challenging  period for forecasting loan performance was the onset of the 2008  financial crisis. A key question in evaluating subsidy cost estimates is  whether agencies were able to foresee deteriorating performance in credit  program portfolios.
Government-wide, a total of 101 direct loan programs reported  reestimates for the fiscal years 2001 through 2014 cohorts. As shown in  table 1, 42 programs had lifetime upward reestimates and 59 programs  had lifetime downward reestimates. Overall, the reestimates for these  programs totaled a net lifetime upward reestimate of $3.1 billion, meaning  that the original subsidy costs of the cohorts obligated during this period  were underestimated by $3.1 billion, which is less than 1 percent of the  amount of loans disbursed by the cohorts in our review. Based on data  reported in the President’s Budget, the estimated lifetime subsidy income,  meaning negative subsidy cost, of the fiscal years 2001 through 2014  cohorts of direct loan programs totaled about $91 billion, after considering  the effects of lifetime reestimates. Therefore, the net lifetime upward  reestimate of direct loan programs’ fiscal years 2001 through 2014  cohorts, represents about 3 percent of the lifetime subsidy income.
Further, as shown in figure 6, four direct loan programs accounted for 88  percent of the lifetime upward reestimate of $32.6 billion, with Education’s  Direct Student Loan Program accounting for 71 percent. Similarly, four  direct loan programs accounted for 88 percent of the lifetime downward  reestimates of $29.5 billion, with Treasury’s Government Sponsored  Enterprises (GSE) Mortgage Backed Securities (MBS) Purchase Program  accounting for 55 percent.
Government-wide, a total of 76 loan guarantee programs reported  reestimates for the fiscal years 2001 through 2014 cohorts. As shown in  table 2, 35 loan guarantee programs had lifetime upward reestimates and  41 programs had lifetime downward reestimates. Overall, the reestimates  for these programs totaled a net lifetime upward reestimate of $39 billion,  which is less than 1 percent of the amount of loans guaranteed by the  cohorts in our review. Based on data reported in the President’s Budget,  the estimated lifetime subsidy cost of the fiscal years 2001 through 2014  cohorts of loan guarantee programs totaled about $26 billion, after  considering the effects of lifetime reestimates. Therefore, for the fiscal  years 2001 through 2014 cohorts, loan guarantee programs initially  estimated subsidy income of $13 billion.
Further, as shown in figure 7, five loan guarantee programs accounted for  91 percent of the $104.5 billion lifetime upward reestimates, with HUD’s  Mutual Mortgage Insurance (MMI) Fund accounting for 65 percent.  Similarly, three loan guarantee programs accounted for 95 percent of the  $65.5 billion lifetime downward reestimates, with Education’s Federal  Family Education Loan (FFEL) program accounting for 91 percent.
In concluding about overall trends, we considered many factors, including  magnitude of reestimates, consistency in reestimate patterns over time,  and the number of programs with either upward or downward  reestimates. Based on our analyses of these factors related to reestimate  data for the fiscal years 2001 through 2014 cohorts, we did not identify  any overall consistent trends in under- or overestimates of subsidy costs  across federal credit programs government-wide. Specifically, although  both direct loan and loan guarantee programs government-wide had  overall lifetime upward reestimates for the cohorts over the 14-year period  of our analysis, the reestimates fluctuated significantly from year to year.  For example, as shown in figure 8, from fiscal years 2006 through 2014,  direct loan programs recorded overall net upward reestimates for 4 years  and overall net downward reestimates for 5 years. Also during this period,  loan guarantee programs recorded overall net upward reestimates for 5  years and overall net downward reestimates for 4 years. The large  upward reestimates in fiscal year 2012 for loan guarantees and in fiscal  year 2014 for direct loans were primarily attributed to HUD’s MMI Fund  and Education’s Direct Student Loan Program, respectively, which are  discussed later.
We also analyzed reestimates over time based on whether programs are  discretionary or mandatory. Under FCRA, as previously discussed,  appropriations for initial subsidy costs of discretionary programs are  typically limited to a definite amount. Mandatory credit programs are  funded by the operation of their authorizing statutes, typically in indefinite  amounts. However, both discretionary and mandatory programs  automatically receive permanent indefinite budget authority for the cost of  upward reestimates. Thus, agencies with discretionary credit programs  theoretically could have an incentive to initially underestimate subsidy  costs so that they could make more loans or loan guarantees within a  given appropriation level. If this incentive did not exist and absent any  overriding economic trend, one could expect reestimates to lower the  original subsidy cost estimates as often as they raise it, and the patterns  would be similar for discretionary and mandatory programs.
Overall, we did not identify any consistent trends that would indicate  whether for some discretionary programs there was an effort to benefit  from initially underestimating subsidy costs. As shown in table 3,  generally the same proportion of discretionary and mandatory credit  programs had upward and downward reestimates. The one pattern we  observed was in relation to the magnitude of loan guarantee reestimates.  Specifically, regarding the dollar amount of reestimates, about 95 percent  of the upward reestimates were from discretionary loan guarantee  programs, while about 93 percent of the downward reestimates were from  mandatory loan guarantee programs. These trends are primarily driven by  two programs—upward reestimates for HUD’s discretionary MMI Fund  and downward reestimates for Education’s mandatory FFEL program.  The reestimates for these programs, which can generally be explained by  economic events and portfolio changes, are described in more detail in  the following section.
Our analysis of reestimates trend data excluded activity from Treasury’s  Troubled Asset Relief Program (TARP). TARP is an example of a  federal program that implemented a budgeting process similar to the fair  value approach. TARP was required by law to estimate the budgetary  cost of purchases and guarantees of troubled assets in accordance with  FCRA, except that such costs were required to be calculated by adjusting  the discount rate for market risk. These cost estimates were reestimated  annually, at fiscal year-end, to reflect revised assumptions for market risk,  asset performance, and other key variables and economic factors.  Interest earned or paid on financing account transactions with Treasury  was based on FCRA discount rates (not adjusted for market risk). As a  result, as program funds were repaid, reestimates reflected reduced costs  because of improvements in the economy and also because the noncash  cost that was considered in the market-risk-adjusted discount rates was  not reflected in the actual federal cash flows. Overall, TARP has had  lifetime downward reestimates of nearly $177 billion through fiscal year  2014. If the FCRA methodology had been used to initially estimate the  subsidy cost of TARP, the lifetime downward reestimate would have been  significantly less—meaning that the overestimate of initial subsidy costs  would have been less. As of September 30, 2014, TARP has reported an  estimated lifetime subsidy cost of $54.6 million for its direct loan,  investment, and guarantee programs.
section_title: Significant Upward and Downward Reestimates Could Generally Be Explained by Specific Events Affecting a Few Large Credit Programs
paragraphs: We identified a few programs with significant upward or downward  lifetime reestimates for the fiscal years 2001 through 2014 cohorts, which  could generally be explained by portfolio or economic changes, as well as  revisions in estimation methodologies.
We analyzed estimates of fiscal years 2001 through 2014 cohorts based  on the purposes of the programs. Specifically, the types of direct loan  programs with the largest lifetime reestimates were in the education,  international, and other categories, and the types of loan guarantee  programs with the largest lifetime reestimates were in the housing,  education, and small business and agriculture categories. (See fig. 9.)  These reestimates could generally be explained by specific events  affecting a few large programs.
The education-related category had the largest lifetime upward reestimate  for direct loans and the biggest swings in annual reestimates. For  example, in fiscal year 2010, this category had a net downward  reestimate of $11.4 billion and, in fiscal year 2014, a net upward  reestimate of $18.7 billion, primarily driven by Education’s Direct Student  Loan Program. The reported estimated lifetime subsidy income for the  Direct Student Loan Program’s fiscal years 2001 through 2014 cohorts of  direct loans totaled about $73.3 billion, after considering a lifetime upward  reestimate of about $23.1 billion. The primary cost driver of the Direct  Student Loan Program is the difference between borrowers’ interest rates  on their loans and Education’s cost of borrowing to finance its lending,  represented by the discount rate in the subsidy cost calculation.  Consistent with the process to develop the President’s Budget, Education  prepares its initial subsidy cost estimates in advance of knowing the  actual borrower interest rates on its lending and interest rates to finance  its lending. Further, interest rate changes are impossible to predict with  certainty. As a result, changes in interest rates, which are outside the  control of Education, can have a significant effect on subsidy cost  reestimates for the program.
According to Education, this program experienced generally upward  reestimates over the years mainly driven by discount rate changes;  revised assumptions related to income-driven repayment plans and  public service loan forgiveness; and rising borrower default rates. After  fiscal year 2014, the Direct Student Loan Program reported an upward  reestimate of $21.0 billion, which, according to Education officials, was  primarily related to newly implemented income-driven repayment plans  for borrowers. This reestimate had a significant effect not only on the  reestimates in the education category but also on direct loan program  reestimates government-wide. The size of the Direct Student Loan  Program also contributes to the magnitude of its reestimates. For  example, for the fiscal years 2001 through 2014 cohorts, Education has  reported loan disbursements totaling about $825 billion. With this loan  volume, a 1 percentage point change in the subsidy rate for all cohorts  would result in an $8.25 billion reestimate. In comparison, a 1 percentage  point change in the subsidy rate of a loan program with less loan volume  would have a smaller reestimate amount.
subsections: section_title: International Direct Loan Programs
paragraphs: The lifetime upward reestimates for the international category were  primarily driven by the Export-Import Bank’s (Ex-Im) Direct Loan  Program. The reported estimated lifetime subsidy cost for the fiscal years  2001 through 2014 cohorts of Ex-Im’s Direct Loan Program totaled about  $1.1 billion, after considering a lifetime upward reestimate of $2.8 billion.  Ex-Im reported that upward reestimates were due to estimation modeling  changes made in fiscal year 2012. Specifically, Ex-Im uses a loss  estimation model to estimate subsidy costs. The model calculated loss  rates based on historical data, including default and loss history of prior  loan transactions, as well as variables that can be used to predict defaults  and losses, such as transaction amount and length, obligor type, product  type, and risk rating. According to Ex-Im, in 2012, it added qualitative  factors (e.g., minimum loss rate; global economic risk; and region,  industry, and aircraft portfolio obligor concentration risk) to account for  specific risks associated with the agency’s current portfolio. Ex-Im added  qualitative factors to the estimation methodology to better and more  accurately measure default risk. When Ex-Im added qualitative factors,  there was also an increase in direct loan exposure because of the  financial crisis, which magnified the impact of the qualitative factors. Ex- Im’s direct loan exposure increased from $4.5 billion in 2008 to   $32.7 billion in 2014.
section_title: Other Direct Loan Programs
paragraphs: The downward reestimates in the direct loan other category were  primarily driven by Treasury’s GSE MBS Purchase Program. The  reported lifetime subsidy income of this program totaled about   $21.8 billion, after considering a lifetime downward reestimate of   $16.1 billion. Under this program, Treasury purchased $226 billion of  GSE MBS from the secondary market from September 2008 through  December 2009. As a result of scheduled principal repayments, the  portfolio declined to $136 billion as of March 2011, when Treasury began  the orderly disposition of the remaining MBS portfolio. Treasury  completed the orderly disposition of this portfolio in March 2012.  Following the principal repayments and sales, significant downward  reestimates were recorded in fiscal years 2009 and 2011. These  downward reestimates were the result of higher-than-projected proceeds  from MBS repayments and sales because of improving market conditions  following the 2008 financial crisis.
section_title: Housing Loan Guarantee Programs
paragraphs: The housing category had the largest lifetime upward reestimates for loan  guarantee programs and experienced significant annual upward  reestimates from fiscal years 2008 through 2012, ranging from $8.5 billion  to $28.1 billion during this period. These reestimates were primarily driven  by HUD’s MMI Fund. The reported estimated lifetime subsidy cost for the  fiscal years 2001 through 2014 cohorts of MMI loan guarantees totaled  about $18.7 billion, after considering a lifetime upward reestimate of  $75.3 billion. A variety of economic, portfolio, and market changes  contributed to upward reestimates for MMI’s forward mortgages, which  accounted for $68.2 billion of the MMI Fund’s lifetime upward reestimate.  Chief among these changes affecting the cost were downward  adjustments to long-term housing price and interest rate assumptions  stemming from the mortgage and financial crises in the late 2000s.  Housing prices are an important variable in estimating the MMI Fund’s  subsidy costs because of their influence on the probability of mortgage  default and the severity of losses in the event of default. However, long- term housing price forecasts are inherently uncertain. In addition, the  budget process requires these assumptions to be made more than a year  in advance. HUD officials told us that the assumptions used to make the  original credit subsidy estimates were more optimistic than the revised  assumptions used to make the reestimates, which contributed to upward  reestimates. Another key reason for the MMI Fund’s upward reestimates  was a downward adjustment in mortgage interest rate assumptions.  Mortgage interest rates are an important variable in estimating the fund’s  subsidy costs because of their influence on both mortgage prepayments  and defaults.
A number of portfolio and mortgage market developments associated with  higher-than-expected losses also contributed to the MMI Fund’s upward  reestimates. For example, growth in the proportion of MMI-insured  mortgages with seller-funded down-payment assistance and competition  from private mortgage institutions in the low down-payment mortgage  market contributed to upward reestimates that began in the early 2000s.  MMI-insured loans with seller-funded down-payment assistance grew  from about 6 percent of the MMI Fund’s business in 2000 to about 30  percent in the mid-2000s. Unlike other key mortgage industry participants,  HUD allowed borrowers to obtain down-payment assistance from  nonprofits that operated programs supported partly by financial  contributions and service fees from participating property sellers. The  seller-funded down-payment assistance loans performed worse than  comparable loans with down-payment assistance from other sources or  with no assistance, possibly because these homebuyers had less equity  in the transactions and thus may have been more likely to default. For  example, the MMI Fund cost estimates reflected an estimated subsidy  rate of positive 6.35 percent for seller-funded down-payment assistance  loans, compared with negative 0.01 percent for non-seller-funded down- payment assistance.
Similar to Education’s Direct Student Loan Program, the size of the MMI  Fund also contributes to the magnitude of its reestimates. Because the  amount of loan guarantees provided is so large, a minor change in the  subsidy rate during the reestimate process can result in a significant  reestimate in terms of dollars. For example, for the fiscal years 2001  through 2014 cohorts, HUD has reported loan guarantees totaling about  $2.2 trillion under the forward mortgage issuance program. With this  volume of loan guarantees, a 1 percentage point change in the subsidy  rate for all cohorts would result in a $22 billion reestimate.
section_title: Education-Related Loan Guarantee Programs
paragraphs: The education-related category had the largest lifetime downward  reestimates for loan guarantee programs, driven by Education’s FFEL  program. The reported estimated lifetime subsidy income of the FFEL  program totaled about $8.4 billion for the cohorts since fiscal year 2001,  after considering the effects of lifetime downward reestimates of   $59.6 billion. The significant downward reestimates were attributable to  many factors; chief among them were interest rate changes.  Programmatic changes, such as Education’s ability to purchase  outstanding guaranteed loans from lenders, were reflected as  modifications under FCRA. In addition, the program was terminated by  statute in 2010, prohibiting new loan guarantees after June of that year.
section_title: Small Business and Agriculture Loan Guarantee Programs
paragraphs: The small business and agriculture loan guarantee category had lifetime  upward reestimates of $7.4 billion, which were primarily driven by  reestimates from the Small Business Administration’s (SBA) 7(a) Loan  Guarantee and 504 Certified Development Company Loan Guarantee  Programs. The reported estimated lifetime subsidy cost for the fiscal  years 2001 through 2014 cohorts of 7(a) Loan Guarantee and 504  Certified Development Company Loan Guarantee Programs’ loan  guarantees totaled about $5.0 billion and $3.9 billion, after the effect of  lifetime upward reestimates of $4.1 billion and $3.8 billion, respectively.  These programs experienced higher-than-normal reestimates for fiscal  years 2009 and 2010. SBA reported that the cause of these reestimates  was the downturn in the economy and an unprecedented continuing  period of high unemployment, which increased default claim payments  and the uncertain effects these events would have on future default claim  payments. In addition, SBA reported that worse-than-expected  performance in loans originated during fiscal years 2005 through 2008  also contributed to the upward reestimates.
section_title: Reestimates during the Financial Crisis
paragraphs: To further analyze reestimates, we evaluated annual reestimates for  direct loan and loan guarantee programs from fiscal years 2006 to 2014  to determine whether the 2008 financial crisis had an effect on  reestimates. We found that the negative economic outlook caused by  the economic downturn during the 2008 financial crisis likely increased  the projected cost of housing, small business, and agriculture loan  guarantee programs, as evidenced by upward reestimates during the  financial crisis. For fiscal years 2008 through 2012, the housing loan  guarantee programs’ annual net upward reestimates ranged from   $8.5 billion to $28.1 billion, while the small business and agriculture  related loan guarantee programs’ annual net upward reestimates ranged  from $1.0 billion to $4.3 billion. These reestimates for both categories of  programs were substantially larger than the reestimates before and after  this period. In addition, rising default rates associated with Education’s  Direct Student Loan Program could likely also be, in part, attributed to the  financial crisis. However, this program had upward reestimates before  and after the financial crisis. (See fig. 10.)
section_title: Fair Value Subsidy Cost Estimates May Be Useful, but They Are Not Consistent with Long-standing Federal Budgeting Practices, Involve Significant Implementation Challenges, and Should Not Be Recognized in Budget Costs
paragraphs: The fair value approach to estimate subsidy costs, supported by some  experts we interviewed, would add market risk to what is recognized  under FCRA. While credit program subsidy cost estimates under the fair  value approach may provide useful information to decision makers for  evaluating the costs against the benefits of credit programs, the additional  market risk recognized under the fair value approach does not reflect  additional cash costs beyond those recognized by FCRA. The  introduction of market risk into credit program subsidy costs under the fair  value approach would be inconsistent with long-standing federal  budgeting practices and presents several implementation issues. More  specifically, the fair value approach would (1) add noncash costs into the  budgeting process, which is based on cash costs; (2) be inconsistent with  the budget treatment of similarly risky programs; (3) lack transparency  with respect to inclusion of a noncash cost in budget totals; (4) involve  significant implementation issues; and (5) be complicated by comparisons  to GAAP fair value. Further, as discussed in the prior section, we did not  identify consistent trends in overall under- or overestimates of subsidy  costs across federal credit programs government-wide. Consequently, we  do not support the fair value approach to estimate subsidy costs for the  budget and believe the current FCRA methodology is more appropriate,  as it represents the best estimate of the direct cost to the government and  is consistent with current budgetary practices .Other experts we  interviewed, as well as OMB, opposed the fair value approach.
subsections: section_title: Fair Value Approach Cost Estimates May Be Useful to Decision Makers for Evaluating the Costs against the Benefits of Credit Programs
paragraphs: Fiscal Year 2014 Subsidy Costs  For fiscal year 2014, the estimated subsidy  cost for new loans and guarantees across all  credit programs was an estimated subsidy  income of $35.7 billion. This represented  about .01 percent of estimated federal outlays  and receipts for the year.
The fair value approach to estimate credit program costs may be useful  for evaluating the costs against the benefits of credit programs in that it  accounts for market risks beyond those already recognized under FCRA.  CBO and others have reported that subsidy cost estimates prepared  under FCRA requirements do not completely reflect the costs imposed on  taxpayers by federal credit programs, thus prompting proposals to modify  FCRA subsidy cost estimates based on the fair value approach. More  specifically, proposals calling for the adoption of the fair value approach  are motivated by the idea that the social costs to taxpayers of making  loans should be recognized. The social cost of making a loan includes not  only the estimated cash cost to the government for making the loan and  for providing for the possibility of default—both of which are currently  recognized under FCRA requirements—but also the noncash cost to  taxpayers for bearing the risk associated with the loan—which is not  currently recognized under FCRA requirements. Because such social  costs are not currently being accounted for, proponents of the fair value  approach asserted that budget decisions may be distorted by an incentive  to overly rely on risky credit programs as a policy tool because credit  programs look relatively less expensive than other forms of federal  assistance (e.g., grants).
Aggregate Risk Premium  In private financial markets, taxpayers as  investors with diversified portfolios would still  demand compensation for bearing the risk  that the macroeconomy—the national or  global economy as a whole—may falter. This  risk—referred to as aggregate risk (which  represents a portion of overall market risk)— arises from the possibility of significant  economic downturns, when even a well- diversified portfolio of financial investments  will experience a reduction in value.
Proponents of the fair value approach have generally viewed the  government as a pass-through to a collection of taxpayers who bear the  cost of risk, recognizing that the government must ultimately either reduce  spending or turn to taxation to recoup the cost of a defaulted loan. In this  sense, taxpayers could be considered as analogous to investors in a  private corporation who must contribute more resources if the corporation  experiences losses. In private financial markets, taxpayers as investors  with diversified portfolios would still demand compensation for bearing the  risk that the macroeconomy—the national or global economy as a  whole—may falter. As shown in figure 11, this risk—referred to as  aggregate risk (which represents a portion of overall market risk)—arises  from the possibility of significant economic downturns, when even a well- diversified portfolio of financial investments will experience a reduction in  value. In such bad economic times, loan payments are likely to fall just  when returns are worth most to investors. Compensation for taking on this  aggregate risk—the aggregate risk premium—is over and above that  demanded to account for the time value of money (i.e., the notion that a  dollar today is worth more than a dollar in the future because it can earn  interest). The fair value approach is based on the premise that the  subsidy cost of credit programs should include this aggregate risk  premium due to taxpayers, even if it is not a cash cost to Treasury.
While proponents of the fair value approach suggested several methods  to estimate the cost of credit programs under the fair value approach, we  are focusing on the most commonly discussed method for use in federal  budgeting, which calls for adjusting the discount rate to account for the  aggregate risk premium. Some proponents of the fair value approach  also viewed adjusting the discount rate as the most straightforward  method to derive fair value approach measurements. Under this method  to implement the fair value approach, the difference between FCRA and  fair value approach subsidy cost estimates arises from the choice of  discount rates. The estimates of expected cash flows associated with the  loan program, including repayments, interest, or the net amount lost  through defaults or other loan performance, are the same in both  approaches. However, the difference in discount rates means that those  expected cash flows will have different present values under the fair value  approach and FCRA.
To incorporate the cost of bearing this aggregate risk into budget costs for  loans, the fair value approach adds an aggregate risk premium to the  discount rate used in FCRA calculations, which is determined based on  interest rates on Treasury securities. The Treasury rate is considered to  be default-free because investors are protected against default by the  government’s ability to cover its debts by raising tax revenue or by cutting  other federal spending. Adding the aggregate risk premium to the  discount rate incorporates a noncash social cost into the subsidy cost  estimate. When the expected future cash flows (i.e., payments of interest  and repayments of principal) associated with the loan are discounted  using a discount rate above the Treasury rate, the resulting present value  of these future payments to the government is lower than it would be if  discounting were done using the Treasury rate. A lower present value for  these future payments to the government translates into a higher subsidy  cost to the government when the loan is made. As shown in figure 12,  the aggregate risk premium is one factor that may explain differences  between market interest rates and Treasury interest rates. The debate  over the fair value approach rests on whether the cost associated with  aggregate risk should be considered in the subsidy cost of credit  programs for the budget of the federal government.
The budget, as presented under FCRA, does not recognize an aggregate  risk premium, and the cost of the government making loans is lower than  it would be under the fair value approach. Some proponents of the fair  value approach have stated that the disconnect of subsidy cost estimates  under FCRA from market valuation is at odds with the presentation of  other costs in the budget that do reflect values in private market  transactions (e.g., purchase of office supplies or wages paid). Market  prices are key benchmarks in assessing the costs to society of using its  resources in one project versus another. In this context, the budget under  FCRA does not reflect the social costs of making loans, which fair value  approach proponents believed should be considered in making budget  decisions that require trade-offs in the presence of a federal budget  constraint.
The social benefits and costs of extending credit is an important  consideration in decision making about funding levels. As stated in OMB  Circular No. A-94, federal programs should be evaluated based on  comprehensive estimates of the expected benefits and costs to society  and not just the monetary benefits and costs to the government.  Therefore, for credit programs, both cash costs to the government and  social costs imposed on taxpayers could be weighed against benefits to  borrowers and to the public at large. These social costs would include the  cost of bearing risk that the government has transferred to taxpayers,  represented by the aggregate risk premium. OMB Circular No. A-129,  Policies for Federal Credit Programs and Non-Tax Receivables, requires  agencies to provide benefit-cost analyses as part of biennial program  reviews. These reviews are also intended to take account of changes in  program risks and costs. In this context, the fair value approach  aggregate risk premium could be classified as a cost imposed by a  program and included in total societal costs along with the cash costs to  the government. It is in this setting that several proponents of FCRA  believed, and we concur, that the fair value approach would be most  appropriately considered by decision makers, rather than in budget  estimates.
Reflecting a different concern, some proponents of the fair value  approach to budgeting for federal credit programs, cited as motivation the  perceived over-reliance on federal credit as a policy tool and the desire to  correct any bias toward underestimated costs under FCRA. Consistent  with this view, some proponents of the fair value approach generally  supported the approach for initial subsidy cost estimates that are used by  congressional decision makers to determine loan levels to approve. After  loan levels are approved, these proponents of the fair value approach  generally expressed no preferences for the methodology used to  determine subsidy cost estimates for existing credit program portfolios.  The effects of the 2008 financial crisis on parts of the federal credit  portfolio demonstrated the sensitivity of loan performance to conditions in  the macroeconomy. Subsidy cost estimates of loan guarantee programs  related to housing and small business and agriculture, in particular, had  not anticipated the possibility of large losses associated with the crisis in  the mortgage market and extreme weakness in market demand for goods  and services experienced during the 2008 financial crisis. Repayment of  student loans also declined significantly during this period. Some  proponents of the fair value approach told us that adopting the fair value  approach would help address concerns about the over-reliance on federal  credit programs by raising the subsidy cost of credit programs, likely  resulting in fewer loans being made. Also, according to some  proponents of the fair value approach, raising the cost of credit programs  would weigh against any bias in underestimating costs. In contrast,  proponents of the FCRA methodology stated that to the extent that  agencies were underestimating subsidy costs under FCRA, this would be  more appropriately addressed through improvements in the subsidy  estimation process rather than application of the fair value approach.
Going forward, there are some reasons to expect that agencies’  estimates of expected loan losses will better reflect the possibility of a rise  in defaults in a macroeconomic downturn. Typically, agencies project  future losses based on historical experience. Before the 2008 financial  crisis, program experience generally did not include the effect of a  significant economic downturn. Therefore, expected loss projections  made prior to 2008 would have likely underestimated the actual losses.  Now, the depressing effects of the 2008 financial crisis across the  government’s credit portfolio are included in each program’s historical  data. Although agencies can project individual loan programs’ expected  losses with the downturn included in historical data, the possibility of  extreme losses occurring simultaneously across loan programs would not  be reflected in the loss estimates of any one program. For that, the  government would have to evaluate performance across its entire credit  portfolio, trying to assess the potential size of total losses in a bad  economy. However, our analysis of credit program reestimates over the  course of the 2008 financial crisis revealed that only parts of the portfolio  experienced significant increases in reestimates, implying some degree of  diversification against the risk of aggregate losses. While performance of  parts of the federal credit portfolio does track with financial market  outcomes, performance of others, such as disaster loans, may not.
section_title: Fair Value Approach Subsidy Cost Estimates Are Not Consistent with Long-standing Federal Budgeting Practices, Involve Significant Implementation Challenges, and Should Not Be Included in the Budget
paragraphs: While fair value approach estimates may provide useful information for  evaluating the costs against the benefits of credit programs, the additional  market risk recognized under that approach do not reflect additional  estimated cash costs beyond those recognized by FCRA. The concept of  the fair value approach to recognize the aggregate risk premium due to  taxpayers beyond the FCRA-reflected risks (based on expected cash  outlays) evolved from the consideration of investor behavior in private  financial markets. Subsidy cost estimates prepared under the fair value  approach would be inconsistent with long-standing budgeting practices  and involve significant implementation challenges. More specifically, the  fair value approach would add noncash social costs into the budget process, which is primarily be complicated by comparisons between the fair value approach and  based on cash costs to Treasury;  result in inconsistency with the budgetary treatment of similarly risky  programs;  result in less transparency and cause verification issues related to  noncash costs in budget totals;  involve significant implementation issues; and  private-sector GAAP fair value.
Because of these issues, we do not support the fair value approach to  estimate credit program subsidy costs for the budget and believe that the  current FCRA methodology is more appropriate for this purpose. In  addition, OMB has reported that it opposes the fair value approach  because it would make the budgeting process less transparent and less  accurate.
subsections: section_title: Noncash Social Cost versus Cash Budget Cost to Treasury
paragraphs: Deployment of the fair value approach in the federal budget would  provide a perspective on the cost of aggregate risk that is not currently  represented in the budget for any type of federal program and would add  noncash costs to primarily cash totals found in budget accounts. As  previously discussed, the fair value approach would add the  compensation cost to taxpayers of bearing aggregate risk to the FCRA  subsidy cost estimate, thereby explicitly introducing noncash social costs  into what is fundamentally a cash budgeting system. Proponents of both  the fair value approach and FCRA recognized the aggregate risk  premium as representing a social cost reflecting the ultimate transfer of  the risk of making loans from the government to taxpayers. However,  these social costs do not represent a cash cost to the federal government  and would not be recognized under FCRA estimates because no money  is disbursed or received by Treasury as a result of the different cost  calculation and its inclusion in budget figures. As shown in figure 13, the  initial subsidy cost would be higher under the fair value approach. As the  loan is repaid in the future, the agency would reestimate the subsidy cost,  creating a difference in the timing of the subsidy cost recognition  compared to that under the FCRA methodology. If the loan performed as  expected, the resulting reestimates under the fair value approach would  be downward, in essence amortizing the aggregate risk premium initially  estimated. In contrast, under the FCRA methodology, if the loan  performed as expected, there would be no reestimate. If the loan  performed worse than expected, under both the fair value approach and  FCRA, the agency would update the estimated cash flows and record a  reestimate. However, the resulting final lifetime subsidy cost under the fair  value approach or FCRA would be the same, after completing  reestimates, because the cash flows to and from the government are the  same. The cash flows between the government and the borrower are not  affected by the different discount rates used under the fair value approach  or FCRA.
The concepts that currently underlie the federal budget date to the 1967  Report of the President’s Commission on Budget Concepts. The  commission identified the major purposes of the budget, which included  processes to propose particular programs to advance policy goals and to  propose total expenditures and revenues intended to promote stability  and growth in the macroeconomy. In practice, OMB has observed that the  budget provides “the means for the President and the Congress to decide  how much money to spend, what to spend it on, and how to raise the  money they have decided to spend.” In other words, the budget supports  decisions about which programs to fund and at what level given the  presence of an overall budget constraint (in that government spending  must be supported by tax revenues or debt). Government programs’ fiscal  effects on the macroeconomy are associated with financial inflows and  outflows of Treasury.
The inclusion of social costs in the budget would depart from the concept  of cash expenditures and revenues that currently underlies the budget.  Some proponents of the fair value approach stated that in practice, the  budget already includes noncash costs. Specifically, FCRA introduced  this apparent anomaly by presenting the current and future costs of loan  making in terms of today’s dollars, meaning their worth today, so that the  costs may be compared to the outlays made today when the loan is  disbursed. The subsidy cost of the loan is the budget authority the  Congress appropriates and is the net present value of outflows and  inflows from the government over the life of the loan. Putting credit  program costs in present value terms differs from the current cash basis  used in other programs’ budget accounts to reflect the time value of  money. FCRA could be called modified cash budgeting and serves to  represent the lifetime cost of the loan in today’s dollars. This is consistent  with the method used to compute the fiscal gap and discounts cash flows  in and out of Treasury at the default-free Treasury rate of borrowing.  FCRA does not include in subsidy costs any estimates of costs that do  not represent cash flows to or from the government and will not eventually  be paid to or from Treasury.
The adoption of the fair value approach would, all else equal, initially  increase subsidy cost estimates and the federal budget deficit by  including the cost of bearing aggregate risk. The higher initial estimated  subsidy cost under the fair value approach would increase the budget  authority required for a given volume of loans compared to that required  under FCRA, thereby raising the federal budget deficit through the effect  on outlays. The federal budget deficit has significance in policy making  and in analyzing the economy, and experts who opposed the fair value  approach cautioned against the inclusion in the budget of what they  termed phantom costs of aggregate risk under the fair value approach.  Ultimately though, as noted above, net cash outlays under both the fair  value approach and FCRA are the same, so any upward bias in initial  subsidy cost estimates introduced by the fair value approach would be  eliminated through downward reestimates as receipts from loan  repayments are recognized.
Under the fair value approach, if actual cash flows were as initially  estimated, there would be an additional amount in the financing account  that represents the compensation to taxpayers for bearing risk, which is a  social cost and not a cash cost to Treasury. Social costs do not produce  fiscal effects insofar as they are not cash receipts or disbursements from  Treasury. Consequently, to avoid misrepresenting the fiscal effect of  credit programs on the federal budget deficit, some proponents of the fair  value approach suggested recording a revenue to offset this noncash  social cost to clear the additional amount in the financing account and  correct deficit balances.
Several experts we spoke with disagreed with the fair value approach of  reflecting social costs or the compensation to taxpayers for bearing risks  associated with credit programs in subsidy cost estimates for the budget.  These experts, who favored the current FCRA approach, rejected the  characterization by some financial economists of the government’s being  a pass-through to a collection of taxpayers, no different than investors in  a private corporation. Unlike private corporations, the federal government  is enduring and can avoid insolvency through exercise of its power to levy  taxes and can more easily access credit through the Treasury securities  market. These proponents of FCRA noted that the government has a  lower cost of borrowing than a private financial institution, and as an  entity, the government has the ability to more readily collect on loans  through tax refund offsets and garnishment of wages. In addition, some  federal loans, such as student loans, may not be discharged through  bankruptcy. Therefore, these experts claimed, the cost of providing a  credit program is less expensive for the government than the private  sector. The more fundamental disagreement over the fair value approach  concerns whether the government’s true cost of capital is represented by  the “riskless” rate at which it borrows or whether that cost should also  include compensation to taxpayers for bearing aggregate risk. This  debate in the financial economics literature about the government’s cost  of capital dates back several decades and has not been settled.
section_title: Inconsistency with the Budgetary Treatment of Similarly Risky Programs
paragraphs: If the fair value approach were deployed for the government’s portfolio of  direct loans and loan guarantees, inconsistency of treatment across  budgetary accounts would have to be considered. Potential  inconsistencies arise from (1) the comparability of loan program budget  totals that include social costs with noncredit program cash costs that do  not include social costs, (2) the exclusion of social costs associated with  costs of programs that present risks similar to those of loans, and (3) the  treatment of the presence of risk and uncertainty in federal activities other  than loan making. These inconsistencies could distort the decisions the  budget is intended to support by making loans appear relatively more  expensive than other programs because of the inclusion of noncash  social costs.
The federal budget is primarily recorded on a cash and obligations  basis. The inclusion of social cost in the form of the fair value approach  risk premium raises the relative costs of loans compared to other  programs budgeted based on cash. However, many other federal  programs impose social costs in addition to incurring cash outlays. One  example would be the costs of environmental damage resulting from  federally funded construction projects. Such social costs may not be  priced in the market as an aggregate risk premium might be, but they are  real costs to society in terms of losses in environmental quality and  services. If the fair value approach were to be adopted for budgeting  credit program costs, maintaining consistency in the budget would require  recognition of the social costs of all federal programs across the board,  presenting a daunting analytical problem, at a minimum.
The introduction of aggregate risk compensation in the budget would  create another inconsistency in the budget’s portrayal of the costs of  uncertain outcomes. Under the fair value approach, an agency would—as  it does now under FCRA—make an estimate of expected loan  performance, including repayments, prepayments, defaults, and  recoveries. The expected cash flows would be associated with average  losses over the life of the loan cohort, implying equal weight on both lower  and higher levels of loss. With the fair value approach, the addition of the  aggregate risk premium implicitly weights the worse outcome more  heavily by adding a cost associated with the possibility that losses are  greater than expected. Elsewhere, the budget presents as point estimates  the expected value of uncertain spending outcomes with the prospects of  better and worse outcomes equally weighted. For example, the  President’s Budget includes funding requests for the costs of fighting  forest fires. That request represents the expected value of the funding  level required based on the probability of a good outcome (i.e., few fires)  and a bad outcome (i.e., an active fire season). To the extent that this risk  cannot be diversified—that is, offset by risk elsewhere in government  spending—then, as with the fair value approach, a risk premium would be  added. Weighting bad outcomes more heavily, as with the fair value  approach, would thus be inconsistent with the treatment of risk and  uncertainty in all other budget estimates.
section_title: Transparency and Verification Issues
paragraphs: Cost estimates prepared under the fair value approach in the budget  would introduce a number of transparency and verification issues.  Regarding transparency in the presentation of the budget, it may not be  obvious that credit program costs included an aggregate risk premium, so  the lack of comparability with other programs’ cash budgeting would not  be clear. Moreover, as previously discussed, some proponents of the fair  value approach believed that the use of fair value would address the  perceived over-reliance on federal credit and correct for any bias in  underestimates of costs. However, as also previously discussed, our  analysis of reestimates for the fiscal years 2001 through 2014 cohorts of  direct loans and loan guarantees did not identify any overall consistent  trends in under- or overestimates of subsidy costs across federal credit  programs government-wide. Further, some proponents of FCRA asserted  that any problem with subsidy cost estimates will not be solved by  revising a budget estimate via the fair value approach but by engaging  decision makers in discussions about the types and amounts of federal  credit that should be provided in the budget. For example, one expert  stated that concerns about credit program losses could be addressed by  tightening eligibility criteria or reducing appropriations. In addition,  proponents of FCRA felt that any inaccuracy in estimating subsidy costs  should more appropriately be tackled by strengthening the data and  methods agencies use in forecasting expected cash flows.
Using the fair value approach may also mask information about direct  loan and loan guarantee performance. Under FCRA, the annual  reestimates may provide useful information to analyze actual loan  performance and to evaluate the quality of the estimation process as,  year by year, actual loan performance is recorded and expectations of  future loan performance are updated. Under the fair value approach, such  information may not be transparent because the effects of the adjusted  discount rate would also be included.
Further, under the fair value approach, the accuracy of the estimate of the  aggregate risk premium is not transparent and verifiable, which is an  important consideration given its cost-increasing effect. A primary  challenge in the fair value approach to budgeting is identifying the  aggregate risk premium applicable to any particular program. If the credit  program has a close counterpart in private credit markets, referred to as a  comparable, the difficulty is reduced though not eliminated. For  example, private credit markets could likely provide a proxy for HUD’s  MMI Fund. However, there is likely not a private market comparable for  SBA’s Disaster Loan Program. In the absence of a market comparable,  the analytical task would be significant and subjective, and in any event,  resulting estimates could be subject to criticism and controversy that  would be hard to resolve. Moreover, even when a market comparable  exists, the task of extracting the aggregate risk premium from the  difference between the default-free Treasury rate and the observed  market rate would still be subjective. This complication arises because  other kinds of costs and risks that are not applicable to government  lending may be compensated in the market rate, as was illustrated in  figure 12. Arriving at a verifiable and auditable estimate of the aggregate  risk premium for each credit program is essential if there is to be  confidence in decisions that depend on comparing their relative costs.
Some proponents of the fair value approach suggested that TARP  illustrates successful implementation of the fair value approach. TARP  was required to use market-risk adjusted discount rates when determining  subsidy costs for the budget. For investment programs, TARP’s  valuations were based on market prices of securities for comparable  institutions and not solely the aggregate risk. In addition, because the  intention of TARP was to liquidate the assets when economically feasible  rather than hold them to maturity, the use of market prices was an  appropriate measure of expected cash proceeds to be received from  liquidation when the assets were sold. Therefore, TARP’s use of market- risk adjusted discount rates may not be directly comparable to other credit  programs. Under FCRA and in accordance with OMB Circular No. A-11,  Preparation, Submission, and Execution of the Budget, if an agency were  to plan to sell loan assets, the cash flows developed to estimate subsidy  costs would include assumptions related to expected sale proceeds,  which could be based on market information.
section_title: Additional Significant Implementation Issues
paragraphs: Several experts we spoke with stated that there would be significant  challenges to implementation of the fair value approach. (See app. III for  further details on these implementation challenges.) Several experts,  including proponents of both the fair value approach and FCRA, stated  that agencies and OMB do not currently have sufficient resources to  implement the fair value approach for subsidy cost estimates in the  budget. Some proponents of the fair value approach suggested that  private-sector expertise could be recruited to address the challenges of  identifying the appropriate aggregate risk premium for a program.  However, other experts stated that for programs that lack a market  comparable, private-sector expertise may or may not be more suited to  address the challenge of identifying the aggregate risk premium.
Conceptual and practical implementation difficulties would also confront  agency analysts. For example, a decision would need to be made about  whether the aggregate risk premium for an existing cohort should be  updated during the reestimate process. Updating the aggregate risk  premium could add significant volatility to subsidy cost estimates, making  it more difficult to understand reasons for reestimates (i.e., poor estimates  or worse-than-expected performance). However, not updating the  aggregate risk premium would result in cost estimates based on out-of- date or noncurrent estimates of risks. Further, to the extent that the  financial accounting for credit programs continues to be consistent with  the budgeting for credit programs, not updating the aggregate risk  premium would be difficult for an agency to support during a financial  statement audit because the auditor would expect credit program cost  estimates to be based on current risk information. In addition, because  fair value approach subsidy cost estimates would include noncash costs  that would, if actual cash flows were as initially estimated, eventually  result in downward reestimates, decisions would need to be made on  whether to recognize these downward reestimates each year or as a one- time adjustment. If the fair value approach were used, decisions would  also need to be made regarding the interest rate used to calculate interest  income and expense amounts on financing account balances so that the  financing account will break even over time as it uses its collections to  repay its Treasury borrowing.
Other implementation challenges would relate to programs that are  currently required to set borrower fees or interest rates to produce  subsidy-neutral cost estimates, such as the Department of Energy’s Loan  Guarantee Program, or even negative-subsidy cost estimates to cover  administrative costs or to generate reserves, such as HUD’s MMI Fund  loan guarantee program. Decisions would also be needed related to  whether any increases to discretionary spending caps would be made if  the fair value approach were implemented. Lastly, because the financial  accounting for credit programs currently mirrors FCRA and budgetary  accounting, the Federal Accounting Standards Advisory Board would  need to determine whether accounting standards would need to be  revised for any changes made related to the use of the fair value  approach for the budget.
section_title: Comparisons between the Fair Value Approach and Private- Sector GAAP Fair Value
paragraphs: Consideration of the fair value approach has been complicated by the  introduction of financial economics concepts and by the use of the term  “fair value” in both FCRA and private-sector GAAP contexts. Financial  economics aims to explain the behavior of private market participants  when confronted with risk and uncertainty in making investment  decisions. This requires an understanding of the alternatives available for  managing risks and of their respective costs. Application of these private- sector concepts to a government setting is an unfamiliar exercise to many  in the public sector. Further, awareness of the private-sector GAAP  guidance on the use of fair value for measuring private financial  institutions’ assets may mistakenly suggest relevance to federal  budgeting. The label “fair value” as it relates to federal credit program  subsidy cost proposals reflects the perspective that the risk premium  taxpayers demand can be found by observing what they would require to  make similarly risky investments in private financial markets. That view  provides the analogue to the situation contemplated in private-sector  GAAP uses of fair value, wherein the valuation of certain assets and  liabilities of private-sector entities is based on the price that would be  received to sell an asset or paid to transfer a liability in an orderly  transaction between market participants. For those who advocate the  application of private-sector accounting principles to the public sector,  employing private-sector GAAP in estimating the costs of federal credit  programs is attractive. However, any parallels between the public and  private-sector settings are not straightforward. Consequently, the  suggestion to apply private-sector GAAP to federal budgeting for credit  programs creates the potential for misrepresentation of the costs of  government programs.
Federal Generally Accepted Accounting  Principles (U.S. GAAP)  U.S. GAAP is established by the Federal  Accounting Standards Advisory Board  (FASAB).   The primary accounting standard for federal  credit programs is Statement of Federal  Financial Accounting Standards No. 2,  Accounting for Direct Loans and Loan  Guarantees, which became effective in fiscal  year 1994.  When FASAB established this accounting  standard, it stated that it recognized the value  of having financial accounting support the  budget. It also endorsed the logic underlying  the Federal Credit Reform Act of 1990  (FCRA) and recommended that accounting  standards for credit programs be consistent  with budgeting under FCRA.
While the concepts behind the fair value approach and private-sector  GAAP fair value are similar, there are differences in how the two would be  applied. First, under private-sector GAAP, fair value is defined as the  price that would be received to sell an asset or paid to transfer a liability in  an orderly transaction between market participants. In contrast, because  private-sector GAAP fair value—which is based on market prices— includes costs that may not be relevant to the federal government, such  as liquidity costs, the fair value approach extracts aggregate risk from  overall market risk to recognize the risk applicable to federal credit  programs in the view of a taxpayer. Consequently, the fair value approach  does not reflect the price that would be received to sell an asset or paid to  transfer a liability in an orderly transaction between market participants  because the aggregate risk premium recognized under the fair value  approach represents only a portion of the risks and other factors that are  reflected in market prices.
Private-Sector Generally Accepted  Accounting Principles (GAAP) Fair Value  To increase consistency and comparability in  GAAP fair value measurements and related  disclosures, GAAP requires entities to  disclose fair value information based on a  hierarchy of inputs used to determine fair  values. The fair value hierarchy includes three  levels of inputs:
The highest priority—or level 1—refers to  fair values derived from direct market  prices for the specific asset (e.g., quoted  prices of common stock).
Level 2 refers to fair values derived from
Level 3—the lowest priority—refers to fair  values derived from unobservable inputs,  which are primarily derived from  management’s best estimate of how a  market participant would assess the risk  inherent in the asset. These unobservable  inputs are used because there is little to  no direct market activity.
Second, under private-sector GAAP, generally loans that a bank holds for  investment are recorded at amortized cost, net of an impairment  allowance for estimated credit losses. Such loans typically comprise the  bulk of assets held by banks insured by the Federal Deposit Insurance  Corporation. However, loans originated with the intent to sell in the  secondary market to government-sponsored entities and other investors  are measured at the lower of cost or fair value, unless the institution has  elected to account for the loans at fair value under the fair value option.  The private-sector GAAP fair value measurement provides information on  the current value of the asset that is available for sale. In contrast, the fair  value approach would be applied to all credit programs, regardless of  whether the government plans to sell assets or hold them to maturity.  Currently, Treasury is the only federal agency routinely selling some of its  credit programs’ assets. However, under FCRA and in accordance with  OMB Circular No. A-11, Preparation, Submission, and Execution of the  Budget, if an agency were to plan to sell loan assets, the cash flows  developed to estimate subsidy costs would include assumptions related  to expected sale proceeds, which could be based on market information.
Financial institution  Percentage of loan  portfolio measured  at GAAP fair value  2%  2%  2%  1%  1%  As of the end of 2013, the five largest (based  on total assets) domestic private-sector  financial institutions used GAAP fair value for  approximately 2 percent or less of their loan  portfolios and these fair values were classified  as level 2 or level 3.
GAO believes the current FCRA methodology is more appropriate to  estimate credit program subsidy costs for the budget. The construction,  use, and interpretation of the federal budget as a system of primarily cash  accounts have been the norm for decades. Subsidy cost estimates  prepared under the fair value approach would not be consistent with  federal budgeting practices of recognizing expected cash outlays.  Further, the application of the fair value approach to only credit programs,  the loss in transparency and in the ability to verify the noncash cost, and  significant implementation issues argue against change from the FCRA  approach. In addition, to the extent that agencies were consistently  underestimating subsidy costs under FCRA, this kind of bias would be  more appropriately addressed through improvements in the subsidy  estimation process, rather than application of the fair value approach.  However, based on our analyses of reestimate data for the fiscal years  2001 through 2014 cohorts, we did not identify any consistent trends in  overall under- or overestimates of subsidy costs across federal credit  programs government-wide. Although the fair value approach may be  useful to decision makers for evaluating the costs against the benefits of  federal credit programs in that it accounts for market risks beyond those  risks already recognized under FCRA, and the provision of this type of  information is consistent with OMB’s guidance in OMB Circular No. A-129  requiring biennial reviews of credit programs, it is not appropriate for use  in estimating credit subsidy costs for the budget.
section_title: Agency Comments
paragraphs: We provided a draft of this report to CBO and OMB for their review and  comment. Both CBO and OMB provided technical comments, which we  have incorporated as appropriate.
As agreed with your office, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to other interested parties. In  addition, the report will be available at no charge on the GAO website at  http://www.gao.gov.
If you or your staff have any questions about this report, please contact  Cheryl E. Clark at (202) 512-9377 or clarkce@gao.gov, Susan J. Irving at  (202) 512-6806 or irvings@gao.gov, or Susan Offutt at (202) 512-3763 or  offutts@gao.gov. Contact points for our Offices of Congressional  Relations and Public Affairs may be found on the last page of this report.  GAO staff members who made key contributions to this report are listed  in appendix IV.
section_title: Appendix I: Objectives, Scope, and Methodology
paragraphs: To determine whether there were similarities in the size and direction of  reestimates across, or within, federal credit programs and, based on this  analysis of reestimates, to identify factors, if any, that help explain any  significant trends in reestimates, we examined reestimate data reported  for all direct loan and loan guarantees by cohort for fiscal years 2001  through 2014. We chose loan cohorts beginning in fiscal year 2001 to  ensure that our analysis covered a full business cycle. Reestimate data  were obtained from the President’s Budgets for fiscal years 2003 through  2016. Specifically, we used tables 7 and 8 reestimate data from the  Federal Credit Supplement (FCS) to the Budget of the U.S. Government  for fiscal years 2003 through 2016. The FCS for fiscal year 2003 is the  first year in which data for the fiscal year 2001 cohorts were reported.  Because of the 2-year lag between the timing of the loan cohort  disbursement and the reporting in the FCS, the fiscal year 2014 cohort of  direct loans and loan guarantees (from the fiscal year 2016 FCS) is the  most recent cohort in our data.
The reestimate data were in spreadsheets that reproduce the data as  they appear in the FCS. In spreadsheets, the first column contains five  different fields: (1) the agency name, (2) the bureau name, (3) the  program name, (4) the risk category name, and (5) the cohort year. We  developed a computer algorithm to distinguish among these fields and  identified the unique agency, bureau, and risk category combination as a  “program.” We retained this information for each cohort of direct loans  and loan guarantees.
We reviewed the agency, bureau, and risk category data manually to look  for inconsistencies such as spelling and formatting differences that could  affect the number of distinct direct loan and loan guarantee programs  identified by our computer algorithm. We found that some names were  reported differently over time. For example, the risk category Farm  Storage Facility Loan Program reported in the fiscal year 2003 to 2008  FCSs is the same as the risk category Farm Storage Facility Loans  reported in the fiscal year 2009 to 2016 FCSs. In another example, the  Indian Land Acquisition risk category, reported in fiscal year 2003 to 2008  FCSs, was called Indian Tribe Land Acquisition in subsequent years’  FCSs. In cases such as these, we standardized the program names to  facilitate our analysis of credit programs over time. We cleaned the data  to remove footnotes, standardized the coding of missing values, and  reformatted numeric values to permit mathematical calculations, as  appropriate. For example, numbers saved as text characters were  multiplied by 1 to obtain values that could be added, subtracted,  multiplied, or divided.
We supplemented data from the FCS with information on whether  programs were mandatory or discretionary, which we obtained from  tables 1 and 2 of the FCS or based on research of the program’s  budgetary funding type. We also used professional judgment to classify  the primary purpose of each program as one of seven possible  categories: (1) education-related; (2) energy, transportation, and  infrastructure; (3) housing; (4) international; (5) small business and  agriculture; (6) other; and (7) the Troubled Asset Relief Program (TARP).  Because TARP was a unique, one-time program implemented in  extraordinary circumstances, and because the amount of its lifetime  downward reestimate was so large in comparison to all other credit  programs, we excluded TARP from our analysis.
From the spreadsheets, we created a single file of cohort-level direct loan  data and a single file of cohort-level loan guarantee data. These data  were the basis for our examination of trends in reestimates across  programs and over time. We examined patterns in direct loan and loan  guarantee programs by agency, by program, by purpose, by fiscal year  the direct loan or loan guarantee was approved, and by program funding  type (mandatory and discretionary). Our analysis focused on lifetime  reestimate amounts, annual reestimate amounts, and a comparison of  most recently reported reestimated and original subsidy rates for each  program. For each year of the FCS, we calculated program-level lifetime  reestimate amounts as the sum of the lifetime reestimate amounts  reported for each cohort in the program. We examined the direction of the  most recent lifetime reestimate amounts by purpose and by agency. We  identified programs with relatively large lifetime reestimate amounts and  examined their influence on upward and downward reestimates  government-wide. For each program, we calculated the annual reestimate  amount as the annual change in the program-level lifetime reestimate  amounts. Our conclusions about possible trends were based on our  professional judgment in assessing the data, and not based on a  statistical analysis.
We also examined reestimated subsidy rates for each program relative to  the most recently reported original subsidy rate. For each FCS, we  calculated these program-level relative reestimated rates as a weighted  average of the cohort-level data. In these calculations, differences  between the reestimated rate and the most recently reported original  subsidy rate were weighted by the size of each cohort, as measured by  the cohort’s reported total disbursements to date.
In assessing data reliability, we encountered some data limitations, which  we individually evaluated based on professional judgment. For each data  limitation, we adjusted the data, identified alternative data calculation  methods when available, or determined that the data were reliable for our  purposes. For example, not all programs reported data in the FCS each  year. In addition, one program did not report reestimate information by  cohort. Instead, all reestimates were combined and reported with the  most recent cohort. We also noted some discrepancies between the  lifetime reestimate amount reported for each cohort and the running total  of the annual reestimate amounts that had been reported since the cohort  of direct loans or loan guarantees was first disbursed. These  discrepancies tended to be less prevalent for later cohort years because  of quality controls implemented by the Office of Management and Budget  (OMB) in fiscal year 2008.
To evaluate implications of using subsidy cost estimates developed under  the fair value approach for the budget and to determine whether we  believe such concepts should be incorporated into subsidy cost estimates  for the budget, we reviewed literature related to the Federal Credit  Reform Act of 1990 (FCRA), the budget, and the fair value approach. This  literature included GAO reports, Congressional Budget Office reports,  Congressional Research Service reports, OMB guidance and budget  information, the 1967 Report of the President’s Commission on Budget  Concepts, legislation, position papers, and academic reports. We  identified a diverse group of individuals or organizations with expertise in  FCRA, the fair value approach, financial economics, and federal  budgeting through our review of relevant reports in these issue areas,  based on internal discussions with GAO staff familiar with experts in this  area, and based on recommendations from experts interviewed. We  considered expert experience, work history, and published work relevant  to our engagement to help ensure expertise qualifications and to achieve  a balanced review. We conducted semistructured interviews with 30  experts to achieve a variety of expertise and viewpoints. The views  expressed by the experts should be interpreted in the context of the  following qualification. Although we were able to secure the participation  of a balanced, highly qualified group of individuals, we could not interview  all of the individuals with expertise in relevant fields because of the need  to limit the number of interviews conducted.
We conducted this performance audit from June 2014 to January 2016 in  accordance with generally accepted government auditing standards.  Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives.
section_title: Appendix II: Analysis of Reestimates
paragraphs: We analyzed direct loan and loan guarantee programs’ annual and  lifetime reestimates by cohort, program, and agency purpose from fiscal  years 2001 through 2014 to identify any trends. We also considered the  purpose of the credit programs based on the following categories:   (1) education-related; (2) energy, transportation, and infrastructure;   (3) housing; (4) international; (5) small business and agriculture; and   (6) other. We excluded the Department of the Treasury’s (Treasury)  Troubled Asset Relief Program (TARP) from our analysis because TARP  was a unique, one-time program implemented in extraordinary  circumstances. Further, the size of TARP downward reestimates dwarfs  the reestimates of all other credit programs, and its inclusion would make  any trend analysis less meaningful. The amounts discussed in this  appendix are based on information reported in the President’s Budgets.
subsections: section_title: Reestimates by Agency
paragraphs: We analyzed the reestimates for fiscal years 2001 through 2014 by  agency. Table 4 illustrates the agencies with direct loan programs, the  total loan disbursements from these programs during the period, the  number of direct loan programs at each agency, the number of programs  that had either upward or downward lifetime reestimates, and the amount  of the upward or downward reestimates. For example, the Department of  Education (Education) had seven direct loan programs, with one program  comprising lifetime upward reestimates of $23.1 billion and six programs  comprising lifetime downward reestimates of $7.7 billion. Overall,  Education’s direct loan programs represented a net lifetime upward  reestimate of $15.4 billion. In contrast, Treasury had five direct loan  programs, with two programs comprising lifetime upward reestimates of  $2.4 billion and three programs comprising lifetime downward reestimates  of $16.4 billion. Overall, Treasury’s direct loan programs represented a  net lifetime downward reestimate of $14.0 billion.
Table 5 summarizes the lifetime reestimates for agencies with loan  guarantee programs for fiscal years 2001 through 2014. As shown, the  Department of Housing and Urban Development and Education  accounted for the largest net lifetime upward and downward reestimates,  respectively.
section_title: Reestimates by Program Purpose
paragraphs: We also analyzed the reestimates for fiscal years 2001 through 2014  based on the program purpose. Table 6 summarizes direct loan program  reestimates by purpose. Direct loan programs related to education and  international lending experienced net lifetime upward reestimates. The  other category, which represents programs that do not fit in the other  categories, including Treasury’s Government Sponsored Enterprises  Mortgage Backed Securities Purchase Program and the Small Business  Administration’s (SBA) Disaster Loan Program experienced net lifetime  downward reestimates.
As shown in table 7, loan guarantee programs related to housing and  small business and agriculture experienced net lifetime upward  reestimates, while loan guarantee programs related to education  experienced net lifetime downward reestimates.
section_title: Differences between Original and Reestimated Subsidy Rates
paragraphs: We also compared the most recently reported original and reestimated  subsidy rates for direct loan and loan guarantee programs. To calculate  the difference between the original and reestimated subsidy rates for  each program, the difference for each cohort of direct loans or loan  guarantees was weighted based on reported disbursements for direct  loans or guaranteed loan amounts disbursed for loan guarantees. As  shown in figure 14, we found that for most of the programs, reestimated  subsidy rates were within 10 percentage points of the original subsidy  rates. For example, if the calculated original subsidy rate for a program  was 12 percent, with a 10 percentage point difference, the calculated  reestimated subsidy rate would fall between 2 percent and 22 percent.  However, as indicated in figure 14, there were a few programs that had  larger differences between the most recently reported original and  reestimated subsidy rates. For example, the Department of Energy’s  Advanced Technology Vehicles Manufacturing direct loan program  reported an overall lifetime downward reestimate of $2.7 billion mostly  attributable to a significant drop in the credit subsidy cost estimate for one  loan, as a result of a significantly improved credit rating, reducing the  original subsidy rate by 41.2 percentage points, from 45.3 percent to a  reestimated rate of 4.1 percent. As another example, SBA’s Small  Business Investment Company (SBIC) participating securities loan  guarantee program reported an overall lifetime upward reestimate of   $1.7 billion, primarily because of reestimates for fiscal years 2009 and  2010. SBA reported that these reestimates were due to the downturn in  the economy during the financial crisis that resulted in lower-than- projected recoveries. For SBIC, the calculated original subsidy rate of  0.3 percent increased to a calculated reestimated rate of 24.7 percent.
section_title: Appendix III: Fair Value Approach Implementation Considerations
paragraphs: Based on our review of literature and interviews with individuals  knowledgeable about the Federal Credit Reform Act (FCRA), the federal  budget, and the fair value approach, we identified a number of issues that  would need to be considered if the fair value approach were implemented  for credit program subsidy cost estimates in the federal budget.
subsections: section_title: Determining the Aggregate Risk Premium
paragraphs: The primary task in the fair value approach to budgeting for credit  programs is identifying the risk premium applicable to any particular  program. Generally, most proponents of the fair value approach whom we  interviewed suggested that private market information could be used to  determine the risk premium. If the type of federal lending has a close  counterpart in private credit markets, the difficulty of this task is reduced,  but not eliminated. However, most proponents of the FCRA methodology  suggested that it would be difficult to find a private market comparable for  federal credit programs because the federal government tends to  intervene in either inefficient or nonexistent markets. In the absence of a  private market comparable, the analytical task of arriving at an  appropriate aggregate risk premium would be significant and subjective.  Moreover, even when a market comparable exists, the task of extracting  the aggregate risk premium from the difference between the default-free  Treasury interest rate and the observed market rate would be subjective.  This complication arises because some of the costs and risks that may be  compensated in the market rate might be significant to an individual  investor but not relevant to the federal government, such as a more or  less favorable tax treatment or liquidity. Overall, the experts we  interviewed could not provide clear insight into how aggregate risk  premium applicable to the federal government could be extracted from  the market rate. Arriving at a verifiable and auditable estimate of the  aggregate risk premium for each credit program is essential if there is to  be confidence in decisions that depend on comparing their relative costs.
section_title: Subjectivity
paragraphs: Under FCRA, when calculating subsidy cost estimates, all agencies use  the same methodology to determine discount rates, which are based on  interest rates of Treasury securities. Under the fair value approach,  discount rates would be derived from a market comparable, if available,  and each agency could use different methodologies to determine the  aggregate risk premium. Of the experts we interviewed, proponents of the  FCRA methodology generally believed that because of the addition of the  risk premium in the fair value approach discount rate, fair value approach  estimates would be more subjective than FCRA estimates, in part  because more assumptions would be involved. Some proponents of the  fair value approach, on the other hand, believed that fair value approach  cost estimates would be as, or less, subjective than FCRA estimates  because market information would inform the cost estimates. If the fair  value approach resulted in more subjective estimates, this could create a  wider variety of estimates, reducing transparency and consistency across  programs. This inconsistency would be even greater if each agency  estimating subsidy costs used a different methodology to determine the  aggregate risk premium applicable to a program. Some experts we  interviewed suggested, however, that the Office of Management and  Budget (OMB) or the Department of the Treasury (Treasury) should be  responsible for developing the fair value approach aggregate risk  premium to add on to the discount rate for each credit program, which  could reduce inconsistencies. Other experts suggested that OMB could  develop guidance for agencies on appropriate methods for determining  the aggregate risk premium to help ensure consistent and appropriate  application of the fair value approach across programs.
section_title: Resources
paragraphs: Most experts we interviewed believed that implementing the fair value  approach would require additional resources for agencies directly  involved in making the subsidy cost estimates and for entities overseeing  the fair value approach estimation process, such as OMB. The types of  additional resources that would be needed include additional technical  training for current employees, hiring of new staff, use of private-sector  experts, and funds to cover additional administrative costs associated  with development of fair value approach methodologies and estimates.  Some experts stated that the resources used to implement the fair value  approach would be better used by agencies to either (1) improve their  estimates of expected cash flows used in both the FCRA or fair value  approach subsidy cost estimates or (2) gain a more thorough  understanding of, and reporting on, the benefits of credit programs.
section_title: Locking the Discount Rate
paragraphs: Under FCRA, the discount rate is locked—meaning that the discount rate  is determined and cannot be changed—after a cohort of loans is  substantially disbursed. This helps ensure that the reasons for  reestimates are limited to changes in estimation methodologies or actual  loan performance, rather than fluctuations in interest rates, which are  outside the control of agencies. Based on our interviews, there were  differing views as to whether the discount rate should be locked or should  fluctuate under the fair value approach. Under the fair value approach, if  the discount rate was allowed to fluctuate, reestimates could fluctuate  significantly year to year based on the market. This volatility in the  reestimates would be caused by market conditions, which are outside the  control of agencies. In addition, it would be more difficult to determine  whether reestimates were due to estimates of expected cash flows that  differed from actual loan performance or changes in the aggregate risk  premium. Under the fair value approach, the accuracy of the estimate of  the aggregate risk premium cannot be objectively assessed. For example,  under FCRA agencies perform comparisons of estimated and actual loan  performance to assess the estimation process. Because the aggregate  risk premium reflects a noncash cost, there is no method that can be  used to verify the reasonableness of the aggregate risk premium  estimate. In addition, updating the risk premium increases the  administrative activities and would require additional resources.  Conversely, under the fair value approach if the discount rate were locked  in order to avoid this volatility in the reestimates and to reduce workload  burdens, then the resulting reestimates would be based on out-of-date  risk information. The financial accounting for credit programs currently  mirrors FCRA and budgetary accounting. If the financial accounting were  to be revised to incorporate any changes to implement fair value  approach subsidy cost estimates for the budget, then not updating the  aggregate risk premium would result in cost estimates based on  noncurrent risks. This would be difficult for an agency to support during a  financial statement audit because auditors would expect estimates to be  based on currently available risk information.
section_title: Auditability
paragraphs: As previously discussed, the financial accounting for credit programs is  consistent with the budgeting for credit programs. Auditing credit program  balances as part of an agency’s financial statement audit includes  determining whether direct loans and loan guarantees outstanding are  properly reported in the agency’s financial statements and footnotes. This  auditing goal would not change if the fair value approach were adopted  for financial reporting purposes. One expert noted that with the fair value  approach, external auditors would need to focus on assessing whether  agencies have identified an appropriate private market comparable to  identify the aggregate risk premium, or if the agency claims there was no  market comparable, the auditor will need to verify the reasonableness of  that claim. Under the fair value approach, each agency could identify its  own methodologies to identify a private market comparable and to derive  the aggregate risk premium to add to the discount rate for a particular  program. However, the current cash budgeting process allows federal  credit program officials and auditors to see the outflows and inflows of  accounts and permits the comparison of actual cash flows to estimated  cash flows with the goal of verifying the reasonableness of subsidy cost  estimates and improving estimates going forward. With the fair value  approach, there would be no mechanism to verify the reasonableness of  the aggregate risk premium because it does not correlate to any cash  flow of the program. Depending on how well agencies were able to   (1) find a private-sector comparable, (2) establish methodologies to derive  the aggregate risk premium, and (3) adequately document their decision- making process and resulting aggregate risk premiums, this could create  financial statement auditability issues for agencies.
section_title: Volatility
paragraphs: Under the fair value approach, the aggregate risk premium included in  discount rates would be derived from a market comparable, if available. If  no market comparable is available, this task would be more complicated  and assumptions would need to be made. Some experts we spoke with  believed that market information could vary more widely than interest  rates on Treasury securities, resulting in greater volatility in original  subsidy estimates year to year. In addition, depending on how the fair  value approach is implemented during the reestimate process, if the  aggregate risk premium is updated for annual reestimates, many experts  we interviewed believed that reestimates would be more volatile from  year to year. If the fair value approach resulted in more volatile subsidy  estimates and reestimates, this could lead to greater swings in the deficit  than are currently experienced under FCRA.
section_title: Timing of Recognition of the Fair Value Approach Downward Reestimate
paragraphs: Under the fair value approach, the financing account would include the  subsidy cost associated with the noncash cost reflected in the aggregate  risk premium. Therefore, when a loan is fully repaid, and if actual cash  flows were as initially estimated, there would be an additional amount in  the financing account that represents a social cost and not a cash cost to  Treasury. Social costs do not produce fiscal effects insofar as they are  not cash receipts or disbursements from Treasury. Some proponents of  the FCRA methodology referred to this as a phantom cost, which could  cause swings in the federal deficit depending on how the social cost is  cleared from the financing account. This could (1) occur immediately after  the loans are disbursed, (2) be amortized over the life of the loan cohort  through the reestimate process, or (3) be cleared by a closing reestimate  after the entire loan cohort was repaid. To avoid misrepresenting the  fiscal effect on the federal deficit, the social cost in the financing account  would have to be liquidated by means of an offsetting “phantom” receipt  immediately after the loans are disbursed. If the social cost is amortized  over the life of a cohort or cleared at the end of the cohort, this would be  reflected in downward reestimates for programs. Several of the  proponents of the fair value approach whom we interviewed were  indifferent as to when this downward reestimate took place as it would be  outside the congressional decision-making process.
section_title: Financing Account Interest Rate
paragraphs: Under FCRA, the discount rate is also used as the interest rate to  calculate interest income and expense on financing account balances so  that the financing account will break even over time as it uses its  collections to repay its Treasury borrowing. Under the fair value  approach, the financing account interest rate could continue to be based  on the FCRA-defined discount rate based on interest rates on Treasury  securities, as was done with Troubled Asset Relief Program, or it could be  based on discount rates including the aggregate risk premium. If the  financing account interest rate is based on the FCRA discount rate, then  recording the annual interest income and expense on the financing  account helps to amortize the additional amount in the financing account  that represents the noncash social cost. If the interest rate includes the  aggregate risk premium, this would in essence monetize the social cost  but would result in interest payments between agencies and Treasury to  be based on rates not tied to Treasury borrowing costs. Based on our  interviews, most experts did not have a conclusive answer or did not  provide an answer as to what the financing account interest rate should  be under the fair value approach. Many proponents of the fair value  approach did not have an opinion on which rate should be used because  the financing account transactions are outside the congressional  decision-making process.
section_title: Programs with Specific Subsidy Rate Requirements
paragraphs: Some federal credit programs, such as the Department of Energy’s Loan  Guarantee Program, have statutory mandates to charge borrowers fees  at a level that will result in an initial subsidy cost of zero. Other programs,  such as the Department of Housing and Urban Development’s Mutual  Mortgage Insurance Fund loan guarantee program, have statutory  mandates to charge fees at a level to help establish reserves for  unexpected future losses. For programs with these types of requirements,  agencies estimate expected loan performance cash flows and then  determine fees that are necessary to generate the required subsidy rate.  Under the fair value approach, while the expected loan performance cash  flows would be the same, because the discount rate includes the  aggregate risk premium, the cost appears higher. As a result, agencies  would need to charge borrowers higher fees to cover the initially  estimated noncash social costs of a program. However, these noncash  social costs would then be offset, or cleared, during the reestimate  process, meaning that borrowers would be charged more than is needed  to cover the initially estimated cash costs of the program. These higher  fees could affect borrower demand for the credit program. The experts we  interviewed stated that this was a congressional decision on how fees  should be charged. The experts also believed that borrower fees should  not be returned if the estimated cost of a program turned out to be lower  than originally estimated in part because of the administrative burden and  the fact that if costs were underestimated, the government would not  request more fees from borrowers.
section_title: Spending Caps
paragraphs: Recent concurrent budget resolutions have included spending cap limits  on discretionary spending, which are enforceable during the  congressional budget process. One expert pointed out that when FCRA  was implemented, there was an adjustment to the spending caps then in  place to reflect this “change in concept.” If the fair value approach were  implemented and were considered a “change in concept,” the Budget  Control Act of 2011 provided that the President’s budget could include  adjustments to discretionary spending limits, subject to consultation with  the Senate and House, to reflect this conceptual change. Because of the  expected higher costs under the fair value approach, some experts  speculated that these caps would likely be raised.
section_title: Consistency between Federal Budget and Financial Accounting Standards
paragraphs: The Federal Accounting Standards Advisory Board (FASAB) established  the primary accounting standard for federal credit programs, Statement of  Federal Financial Accounting Standards No. 2, Accounting for Direct  Loans and Loan Guarantees, which became effective in fiscal year 1994.  When this standard was issued, FASAB stated that it recognized the  value of having financial accounting support the budget. It also endorsed  the logic underlying FCRA and recommended that accounting standards  for credit be consistent with budgeting under FCRA. FASAB also stated  that as more experience is gained, some modifications in budgetary  requirements may be needed and that so long as the modifications are  made on a credit reform basis and do not materially affect the basic  recognition and measurement principles embodied in the accounting  standards, it intended that accounting practices for direct loans and loan  guarantees should change as needed to remain consistent with the  budget. If the fair value approach were implemented for the budget,  FASAB would need to determine if that approach is consistent with the  basic recognition and measurement principles embodied in the  accounting standards. Having the accounting standards for credit  programs mirror the budgeting for credit programs means that the  financial statement audit can help provide assurance that the agencies’  budgeted amounts are reasonable.
section_title: Appendix IV: GAO Contacts and Staff Acknowledgments
subsections: section_title: GAO Contacts
section_title: Staff Acknowledgments
paragraphs: In addition to the contacts named above, Marcia Carlsen (Assistant  Director), Carol Henn (Assistant Director), Ardith Spence (Assistant  Director), Maria Belaval, Mark Cheung, David Chrisinger, Oliver Culley,  Robert Dacey, Francine DelVecchio, Melissa Emrey-Arras, Natasha  Guerra, Cole Haase, Debra Hoffman, Wilfred Holloway, Karen Jarzynka- Hernandez, Jason Kelly, Jason Kirwan, Dragan Matic, Rebecca Perkins,  Michael Reed, Oliver Richard, Mathew Scirè, Monasha Thompson, Frank  Todisco, Matthew Ward, and Steven Westley made key contributions to  this report.
section_title: Related GAO Products
paragraphs: Rural Housing Service: Progress on GAO Recommendations and  Preliminary Observations on Loan Guarantee Risk Management.   GAO-15-625T. Washington, D.C.: May 19, 2015.
DOE Loan Programs: Current Estimated Net Costs Include $2.2 Billion in  Credit Subsidy, Plus Administrative Expenses. GAO-15-438. Washington,  D.C.: April 27, 2015.
Telecommunications: USDA Should Evaluate the Performance of the  Rural Broadband Loan Program. GAO-14-471. Washington, D.C.:   May 22, 2014.
DOE Loan Programs: DOE Should Fully Develop Its Loan Monitoring  Function and Evaluate Its Effectiveness. GAO-14-367. Washington, D.C.:  May 1, 2014.
Federal Student Loans: Better Oversight Could Improve Defaulted Loan  Rehabilitation. GAO-14-256. Washington, D.C.: March 6, 2014.
Small Business Administration: Actions Needed to Ensure Planned  Improvements Address Key Requirements of the Development Company  (504) Loan Program. GAO-14-233. Washington, D.C.: March 6, 2014.
Federal Student Loans: Borrower Interest Rates Cannot Be Set in  Advance to Precisely and Consistently Balance Federal Revenues and  Costs. GAO-14-234. Washington, D.C.: January 31, 2014.
FHA Mortgage Insurance: Applicability of Industry Requirements Is  Limited, but Certain Features Could Enhance Oversight. GAO-13-722.  Washington, D.C.: September 9, 2013.
COMPETES Reauthorization Act: Federal Loan Guarantees for  Innovative Technologies in Manufacturing. GAO-13-717R. Washington,  D.C.: July 24, 2013.
Department of Energy: Status of Loan Programs. GAO-13-331R.  Washington, D.C.: March 15, 2013.
Department of Energy: Advanced Technology Vehicle Loan Program  Implementation Is Under Way, but Enhanced Technical Oversight and  Performance Measures Are Needed. GAO-11-145. Washington, D.C.:  February 28, 2011.
Department of Energy: Further Actions Are Needed to Improve DOE’s  Ability to Evaluate and Implement the Loan Guarantee Program.   GAO-10-627. Washington, D.C.: July 12, 2010.
Small Business Administration: Additional Measures Needed to Assess  7(a) Loan Program’s Performance. GAO-07-769. Washington, D.C.:   July 13, 2007.
Mortgage Financing: FHA’s $7 Billion Reestimate Reflects Higher Claims  and Changing Loan and Performance Estimates. GAO-05-875.  Washington, D.C.: September 2, 2005.
SBA Disaster Loan Program: Accounting Anomalies Resolved but  Additional Steps Would Improve Long-Term Reliability of Cost Estimates.  GAO-05-409. Washington, D.C.: April 14, 2005.
Mortgage Financing: Actions Needed to Help FHA Manage Risks from  New Mortgage Loan Products. GAO-05-194. Washington, D.C.:   February 11, 2005.
Export-Import Bank: OMB’s Method for Estimating Bank’s Loss Rates  Involves Challenges and Lacks Transparency. GAO-04-531. Washington,  D.C.: September 30, 2004.
Small Business Administration: Model for 7(a) Program Subsidy Had  Reasonable Equations, but Inadequate Documentation Hampered  External Reviews. GAO-04-9. Washington, D.C.: March 31, 2004.
Department of Education’s Federal Direct Loan Program: Status of  Recommendations to Improve Cost Estimates and Presentation of  Updated Cash Flow Information. GAO-04-567R. Washington, D.C.:  March 29, 2004.
Student Loan Programs: As Federal Costs of Loan Consolidation Rise,  Other Options Should Be Examined. GAO-04-101. Washington, D.C.:  October 31, 2003.
Maritime Administration: Weaknesses Identified in Management of the  Title XI Loan Guarantee Program. GAO-03-657. Washington, D.C.:   June 30, 2003.
Small Business Administration: Accounting Anomalies and Limited  Operational Data Make Results of Loan Sales Uncertain. GAO-03-87.  Washington, D.C.: January 3, 2003.
Small Business Administration: Section 7(a) General Business Loans  Credit Subsidy Estimates. GAO-01-1095R. Washington, D.C.: August 21,  2001.
Department of Education: Key Aspects of the Federal Direct Loan  Program’s Cost Estimates. GAO-01-197. Washington, D.C.: January 12,  2001.
Department of Veterans Affairs: Credit Costs and Risks of Proposed VA  Small Business Loan Guarantee Program. GAO/GGD-00-158.  Washington, D.C.: June 30, 2000.
Credit Reform: Key Credit Agencies Had Difficulty Making Reasonable  Loan Program Cost Estimates. GAO/AIMD-99-31. Washington, D.C.:  January 29, 1999.
Credit Reform: Greater Effort Needed to Overcome Persistent Cost  Estimation Problems. GAO/AIMD-98-14. Washington, D.C.: March 30,  1998.
Budget Issues: Budgetary Treatment of Federal Credit Programs.  GAO/AFMD-89-42. Washington, D.C.: April 10, 1989.