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Federal loan and loan guarantee programs have grown to immense proportions, amounting to $ 3.6 trillion in FY2016. That’s well over $10,000 for every man, woman, and child in the United States. Federal loans and loan guarantees outstanding have doubled in size since the Financial Crisis. There are signs that some programs, and especially some of the largest programs such as student loans or FHA home mortgage loans, may be extending too much credit to vulnerable borrowers who can be hurt by defaults and the associated stresses. The stresses are compounded by bankruptcy laws that preclude a debtor from writing off a student loan in bankruptcy or from writing down the size of a mortgage even when a home has lost substantial value. While federal budget rules create incentives to lend to less risky borrowers, those same rules may also be incentivizing agencies to use large volumes of credit while not paying sufficient attention to the outcomes these resources are producing for program beneficiaries. As with other federal programs, it is outcomes and not just program expansion that should be a central focus of policymakers and agency leadership.
The issues raised apply across federal programs: how can program evaluation help government agencies to understand the outcomes of their programs? How can evaluation of outcomes be made cost-effective? How can agencies conduct program evaluation without inviting adverse reactions in today’s unusual policy environment? How can Treasury and OMB support agencies to improve their program outcomes?
The size of federal credit programs has doubled since the 2008 financial crisis, creating a growing risk to the federal government and potential long-term harm to borrowers who may have over-extended themselves with loans they are unlikely to be able to repay. The challenge for the federal government is being able to best determine how it balances serving credit-worthy borrowers vs. borrowers who are more likely to default. One hypothesis for the rapid growth in federal credit programs (mainly student loans and home mortgage insurance) is that the government has not been willing to address income redistribution directly, so in recent years it has been doing it indirectly, via extensions of credit. But, should it be giving loans to constituents who can’t ultimately afford to pay off the loans?
Federal credit programs are an attractive way to provide assistance, but currently, this tool may be over-used compared to other policy tools. To appropriators, grant dollars appear to be more costly than loans or loan guarantees. Credit is seen as a “miracle drug” when it comes to budget scoring; in fact some loan programs like those supported by the Federal Housing Administration (FHA) are seen as revenue-producing, so they score in the budget as a negative subsidy! The 1967 budget concepts commission excluded from the unified budget those credit programs that are 100 percent privately funded (but yet federally-backed), like Fannie Mae, Freddie Mac, and the Federal Home Loan Bank System. As a result, they evade budget discipline.
The student loan default rate is expected to be 25 percent for loans that borrowers take out this year, while the default rate for the riskiest FHA mortgages is projected to be around 20 percent. These defaults will have serious effects for the borrowers for years to come, and could increase the federal deficit. Thus, lending to financially disadvantaged individuals and households can hurt them, rather than help. For example, student loans are exempt from the bankruptcy process, and homeowners can be saddled with underwater loans.
Federal lending agencies should not just look at their total portfolios, but rather focus on their riskiest loans and do a benefit-cost analysis on whether they are hurting or helping this class of borrowers. Otherwise, problems for selected classes of borrowers could be hidden by cross-subsidization in the overall loan portfolio. For each credit program, get granular. Identify the riskiest loans and adjust eligibility based on FICO scores; this will need to vary over time, based on business cycles, etc.
Conducting portfolio analyses of credit programs that examine program outcomes (not just the volume of loans) is sometimes restricted by law. For example, Federal Student Aid (FSA) is legislatively prohibited from tracking the outcomes of the students to whom they lend. As a result, that program cannot conduct student-level evaluations on the effectiveness of its lending. FSA needs to be given the authority to collect outcome data (e.g., did the students graduate, did they get jobs that can cover their loans, how long does it take them to repay, etc.). Since the authorizing committees in Congress put these restrictions in place, it may require some other broad-based congressional committee (e.g., Government Reform, or Appropriations) to authorize such analyses.
The administrative expenses that support many federal loan programs are budgeted separately. There is no link to the volume of loans being financed. The two should be linked, and included in the calculation of the subsidy. When there is insufficient administrative staff, there is no ability to support default aversion techniques (such as debt counseling), which increases the risk of default, and the costs to the government.
There may need to be better accuracy in the re-estimation process for loan defaults, as the economy goes through different business cycles. Right now, there is a permanent, indefinite appropriation that covers any shortfalls, and this end-runs the budget process and could incentivize program managers to under-estimate the true costs of their programs (however, to date, the track record has been good and, at least on average, there hasn’t been gaming of the system).
The choice of interest rate used in subsidy calculations for federal credit programs has important implications for subsidy cost calculations. Consideration should be given to requiring that calculations based upon market or risk-adjusted interest rates be published in the budget even if budget subsidy calculations continue to be based upon Treasury equivalent rates.