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This study utilizes Farm Service Agency lending data to verify if previous racial and gender bias allegations still persist in more recent lending decisions. Beyond loan approval decisions, this study focuses on trends in direct loan packaging terms for approved single proprietorship farm borrowers. Results indicate that although no significant disparities were noted in loan amounts and maturities prescribed for various racial and gender minority groups, nonwhite male and female borrowers were usually charged higher interest rates than the others. Loan pricing differentials could have been the lenders' strategy for price management of borrowers' credit risks.

Federal farm credit programs currently administered by the USDA were initiated in the early 1900s to help the farm sector cope with natural disasters, and these programs have continued to evolve. There has been a rich history of research analyzing USDA farm credit programs and the effects they have had on farmers, ranchers, and credit markets. This paper highlights past research and offers a view of the future direction of research on federal farm credit programs.

We estimate the elasticity of U.S. farm exports to U.S. farm subsidies using a gravity model of statelevel farm exports to 100 major trading destinations for the period 1999 to 2011. Our identification strategy exploits the within-state variation that is free of endogeneity bias in the levels and trends of farm subsidies and farm exports. We find that a 1% decrease in farm subsidies would reduce U.S. farm exports by 0.40% per annum. This equivalently means that the complete abolishment of the farm subsidy program would reduce U.S. farm exports by approximately $15.3 billion per year. Importantly, we document robust evidence that amber box subsidy programs such as countercyclical payments and marketing loan gains have the strongest effect on farm exports, while green box subsidy payments, such as direct payments have negligible effects. Finally, subsidy payments affect exports only in agricultural commodities, not in livestock. Our subsidy elasticity estimates are statistically significant, stable, and economically meaningful, and are vitally needed by U.S. and global policymakers in the face of critical domestic and international developments.

PurposeCredit may help farmers survive and grow by helping farm households cope with farm or off-farm income variation and by allowing farmers to adopt more efficient production technologies and take advantage of scale economies. This study estimates how credit constraints affect the survival and growth of beginning farms and explores how this effect varies depending on the age of the farm operator.Design/methodology/approachFarms businesses are classified as credit constrained using a measure of repayment capacity: the interest expense ratio (interest expenses relative to gross income). Linked data from consecutive Agricultural Censuses are used to track individual farms over time.FindingsResults show that beginning farms with a high interest expense ratio take on less new debt over the subsequent five years. These credit-constrained farms were found to have lower five-year survival and growth rates than similar unconstrained farms. The negative effect of being constrained on growth is greater for farms with operators younger than 40 years old.Practical implicationsThe finding that credit constraints impede the growth and survival of beginning farms supports a rationale for targeted loan programs designed to help beginning farmers. Results suggest that some of the benefits from these programs will be greater for farms with younger operators.Originality/valueThis study is the first to estimate the effect of credit constraints on the survival and growth of farm businesses. The expansive farm-level panel dataset, which includes almost all beginning farmers in the US, allows for precise coefficient estimates while controlling for numerous farm and operator characteristics.

This analysis utilizes farm-level data to evaluate the extent to which U.S. farm program benefits, particularly direct payments, bring about distortions in production. The issue is important in WTO negotiations and in the debate over the distortionary effects of decoupled (\"green-box\") payments. Our results suggest that the distortions brought about by AMTA payments, though statistically significant in some cases, are very modest. Larger effects are implied for market loss assistance payments. Probit models suggest that AMTA payments do not influence the likelihood that agents will acquire more land. Our results are reinforced using an aggregate county-level acreage model.

We design an experiment to simulate how people make agricultural production decisions under three policy scenarios, each incorporating direct payments (DPs): (a) price uncertainty without countercyclical payments (CCPs); (b) price uncertainty with CCPs; and (c) price uncertainty, CCPs, and uncertainty regarding base acreage updating. Results are the CCP program and perceived possibility of future base updating created incentives for subjects to invest more in program (base) crops, despite payments being decoupled from current production decisions. Those choosing to reduce revenue risk by increasing plantings of base crops may face reduced incomes, suggesting the efficiency of crop markets may be diminished.

The US government channels financial support to farmers using a diverse mix of policy measures: top-ups to market revenues when markets or the weather turn bad: direct income supplements based on the area of land farmed: monetary rewards for undertaking good environmental practices: public investments in agricultural research, etc. The objective of this article is to assess differences in the income transfer efficiency of US government spending on different farm programs, including: counter-cyclical, direct, disaster, and marketing loan. The benefits and costs of farm programs, and thus transfer efficiency, vary also according to the policy mechanism used and whether there are secondary knock-on effects in other markets that lead to lower output prices and higher purchased input prices or to a reallocation of farm resources. The hierarchy of payment transfer efficiency implied by the regression results for the entire sample is marketing loan benefits followed by direct payments and then disaster payments in order of declining efficiency.

Farm operations received $29.5 billion (84 percent) of that total, while farm households received $5.6 billion (16 percent). The two rounds of Coronavirus Food Assistance Programs (CFAP 1 and CFAP 2) in 2020 provided $23.5 billion in direct payments to farmers and ranchers, who faced additional market disruptions, production costs, and reduced farm-level prices.The Coronavirus (COVID-19) pandemic caused disruptions to the U.S. agriculture sector, including a decline in commodity prices in the first half of 2020. To mitigate the effects of the pandemic, Congress passed six economic relief and stimulus bills in 2020. One bill authorized USDA to create the Coronavirus Food Assistance Programs (CFAP 1 and CFAP 2), which provided direct payments to farm operations. Other Federal departments and agencies created broader programs from which both farm operations and family farm households were eligible to receive assistance. For example, the U.S. Small Business Administration's Paycheck Protection Program (PPP) offered forgivable loans, and the Economic Injury Disaster Loan Program (EIDL) provided forgivable advances. Most family farm households were also eligible for Economic Impact Payments (EIP), administered by the Internal Revenue Service (IRS). And family farm households that lost off-farm wages were eligible for the Federal Pandemic Unemployment Compensation (FPUC) administered by the U.S. Department of Labor.Total COVID-19-related relief to the U.S. agriculture sector was an estimated $35.1 billion in 2020. Farm operations received $29.5 billion (84 percent) of that total, according to the 2021 Farm Income Forecast: September Update (https://www.ers.usda.gov/topics/farm-economy/farm-sector-income-finances/farm-sector-income-forecast/), while farm households received $5.6 billion (16 percent). CFAP alone provided $23.5 billion in financial assistance.

This analysis evaluates the implied production neutrality of fixed, direct payments. These decoupled payments have played an important role in recent US farm policy. This analysis offers additional evidence regarding the potential for direct payments to have production and acreage effects. However, many questions remain open to inquiry. Farmers' indications that they direct much of their payments to on-farm operating costs while, at the same time, not expanding acreage, is somewhat puzzling. Additional research is needed to evaluate these relationships in greater detail. Likewise, we present a broad evaluation of the factors that farmers reveal to underlie their acreage decisions. These factors need to be examined more fully to determine what underlies the differences across producers.

The Farm Service Agency (FSA) direct farm loan program provides credit to family-sized farms including those operated by beginning farmers and socially disadvantaged applicants. Approximately 37% of all U.S. farms are estimated to be eligible for FSA direct loans when farm size, credit needs, farming experience, and occupation are taken into account. However, market penetration rates for various borrower cohorts range from 0.8% to 4.6% for FY 2000S2003. In general, beginning farmers have weaker financial characteristics than non-beginning farmers. Yet, the same result is not found when comparing socially disadvantaged farmers with non-socially disadvantaged farmers, such that there are few significant differences or the differences in financial characteristics are mixed. Overall, results indicate FSA direct farm loan borrowers have weaker financial characteristics than eligible, non-FSA direct farm loan borrowers, implying FSA is serving farmers likely to be denied credit by commercial lenders.