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USDA direct and guaranteed farm loan programs exhibit significant geographical variation in lending activity. County‐level estimations made using Tobit procedures indicate that use of Farm Service Agency (FSA) farm loan programs is greater in counties with lower per capita income and regions experiencing greater farm financial stress. Use of direct FSA loan programs was lower in counties with fewer private‐sector lenders. Guarantee loan program usage was found to decline when commercial agricultural lenders are absent from the county. FSA loan programs were more highly utilized in counties with an FSA loan service center and in states receiving greater FSA farm loan funding in past years.

The purpose of this paper is to investigate changes proposed in 2012 to commodity programs for the new Farm Bill. Both the Senate and House Agriculture Committee versions of the new Farm Bill eliminate current commodity programs including direct payments, create new revenue‐based commodity program options designed to cover “shallow” revenue losses, and also introduce supplemental crop insurance coverage for shallow revenue losses.

This paper documents the payment functions for the new revenue programs proposed in both the Senate and House Ag Committee Farm Bills, and also estimates expected payments for each using a model based on historical county yield data, farmer‐level risk rates from RMA, and commodity price levels from the March 2012 CBO baseline projections.

The authors find significant variation in expected per acre payment across programs, crops, and regions. In general, the Senate's bill would be expected to be preferred over the House's bill for corn and soybean producers, particularly those in the Midwest. Also, the RLC program in the House's Bill typically would be projected to pay much less than the Senate's SCO or ARC programs for most producers in the Midwest.

This study develops an extensive nationwide model of county and farm yield and price risks for the five major US crops and employs the model to evaluate expected payment rates and the distribution of payments under the House and Senate Farm Bill proposals. These analyses are important for program evaluation and should be of great interest to producers and policymakers.

The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.

The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.

Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.

The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.

The aim of this paper is to show how provisions of the Supplemental Revenue Assistance Payments (SURE) program impacts production practices, and empirically examine changes in crop insurance participation rates as a means of measuring producer responses to the program.

The structure of the SURE program is described and a stylized theoretical model is used to show the SURE program's effects on farm‐level crop insurance and production decisions. A county‐level cross‐sectional empirical specification with regional fixed effects is used to test the hypothesis that producers who are most likely to benefit from production practice re‐optimization are more likely to participate in crop insurance.

Results from empirical analyses of corn, soybean, and wheat production areas show that the SURE program has had substantial impacts on crop insurance participation by producers who are more likely to receive SURE indemnities and exploit moral hazard opportunities.

Because the program has only recently been introduced, empirical estimates of the program's long‐run impacts are not estimable.

Results indicate that the program can have unexpected market consequences, with increased frequency and size of SURE indemnity claims than the Congressional Budget Office anticipated and increases in aggregate tax payer subsidies for both the crop insurance and SURE program. These outcomes can have important implications on motivating a restructuring of the program in the next farm bill.

Increased tax payer expenditures on the SURE and crop insurance programs in the form of subsidies can lead to non‐trivial reductions in social welfare.

This research is the first to develop a rigorous model of the SURE program's impacts on producer responses and associated effects on crop insurance participation. The study also provides empirical evidence of these effects.

The purpose of this paper is to analyze determinants of farmers’ participation and credit rationing in microcredit programs using survey data from Ghana.

The authors use the Garrett Ranking Technique to analyze farmers’ reasons for participation or non-participation in credit programs, a probit regression model to estimate factors influencing farm households’ participation, and the Heckman’s sample selection model to identify factors influencing farm households’ probability of being credit rationed by microcredit programs.

The results reveal that farm households participate in credit programs because of improved access to savings services and agricultural loans. Fear of loan default and lack of savings are reasons for non-participation in credit programs. Furthermore, membership in farmer-based organizations (FBOs) and the household head’s formal education are positively associated with farmers’ participation in credit programs. The likelihood of farmers being credit rationed (i.e. their loan applications were either rejected or the amount of credit they applied for was reduced) is less likely among higher income farmers and members of FBOs such as farmer cooperatives and savings clubs.

The findings suggest that policy strategies aiming to improve access to savings and credit services should educate farmers and strengthen FBOs that could serve as entry points for financial service providers. Such market smart strategies have the potential to improve farmers’ access to financial services and reduce rural poverty.

Although existing studies have examined farmers’ participation in credit markets and credit rationing separately, the unique contribution of this paper is the analysis of participation in microcredit programs as well as the likelihood of farmers being credit rationed in Ghana.

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A two‐stage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior.

It is found that there are liquidity effects of credit constraints for a significant share of the beginning and low‐resource farmers who participated in the state‐funded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent.

This paper is the first to apply the switching regression model to a state‐funded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

The Farm Service Agency (FSA) conservation loan program was introduced in the 2008 Farm Bill to provide additional credit to assist producers implementing approved Natural Resources Conservation Service (NRCS) conservation projects. This paper explores why this program has been widely underutilized despite an overall increase in United States Department of Agriculture (USDA) Conservation Program participation.

The FSA administrative loan data are merged with NRCS program participation and payments data for 2010–2021. The share of project costs paid by producers and resulting savings achieved by farmers participating in both programs if their cost-share portion was paid by FSA loans are estimated, as well as the impact on farmer conservation spending under different estimates of increased participation.

A significant share of FSA farmers are likely to take advantage of NRCS programs, with the majority of participants paying under $25,000 in cost-share portions. These loans are less suited to guaranteed conservation loans and more appropriate for the discontinued direct conservation loan program. Few FSA borrowers participating in NRCS cost-share programs pay more than $50,000 in cost-share portions. These loans would receive the majority of benefits from interest reduction schemes under the current guaranteed loan program.

Our results and suggestions provide valuable information when discussing the Guaranteed Conservation Loan Program in the 2023 Farm Bill legislation.

No prior research has attempted to merge FSA guaranteed or direct loan data with conservation program participation and payment data, focused on producer cost-share levels or the FSA Guaranteed Conservation Loan Program in the last decade, making this study a valuable contribution to the literature.

Rural development programs are widely used policy instruments mitigating rural-urban economic disparities. Yet, little research has examined their effect on rural labor. This study fills this knowledge gap by quantifying the causal impact of such programs on the labor allocation of farm households in Taiwan.

A theoretical framework based on the agricultural household model is constructed to guide the empirical specification. A unique dataset compiles administrative data on the program’s subsidies with farm household surveys across seven years. To cope with endogeneity bias, an instrumental variables model is applied. The eligibility rule for a township to participate in the program is used as the instrument.

We find that the program increases the labor supply of farm household members. These effects are more pronounced for off-farm work, particularly non-heads of farm households. The program’s subsidies supporting culture and promotion-related activities have larger effects. Finally, females benefited more from the program.

We focus on farm households since this group is the target of place-based rural development programs. In addition, we identify the causal impact of place-based development programs on rural labor. Finally, this study is relevant to the literature on intra-household models by demonstrating that place-based rural development programs can affect the labor supply of farm household members.

The purpose of this paper is to evaluate the risk management benefits provided by the supplemental coverage option (SCO) insurance plan which was created in the 2014 Farm Bill. Specifically, the marginal expected utility benefits are compared with the potential additional subsidy cost introduced by the new program for a stylized example of a corn producer.

The paper uses a stylized simulation model examines the preferred insurance program choice for a typical Midwestern corn farmer. The expected utility of the farmer is calculated under their preferred insurance program choice both with and without the availability of the SCO program, and compared to the case where crop insurance is not available. Scenarios are examined for a range of farmer risk aversion levels, different levels of correlation between farm-level and county-level corn yields, and case with and without insurance premium subsidies.

The SCO program is found to enter into the preferred insurance program choice for risk averse farmers. As risk aversion increases, farmers are estimated to prefer higher coverage levels for individual products along with SCO coverage. While the availability of existing crop insurance programs are shown to substantially increase the expected utility of farmers, the marginal impact of adding SCO to the crop insurance program is relatively small. Furthermore, the additional expected benefits generated by SCO are shown to include both risk management and expected return components. With subsidies removed, the estimated marginal benefits provided by SCO are reduced significantly.

The findings of this paper can help inform the policy debate for future farm bills as agricultural support programs continue to evolve. The results in this paper can also be used to help explain farm-level decision making related to crop insurance program choices.

This paper contributes to the literature by documenting a new, federally supported risk management programs made available to farmers in the 2014 Farm Bill and evaluates the marginal benefits the SCO program offers US crop producers.

Several farm safety net strategies are available to farmers as a source of financial protection against losses due to price instability, government policies, weather fluctuations and global market changes. Producers can employ these strategies combining crop insurance policies with countercyclical policies for several crops and production areas; however, less is known about the efficiency of these strategies in enhancing profit and reducing its variability. In this study, we examine the efficiency of these strategies at minimizing inter crop year farm profit variability.

We utilized relative mean of profit and coefficient of variation, to compare counterfactually calculated farm safety net strategies for a sample of 28,615 observations across 2,486 farms and four dryland crops (corn, soybean, sorghum and wheat) in Kansas spanning nine crop years (2014–2022). A no farm safety net strategy is used as the benchmark for every alternative strategy to ascertain whether a policy customization is statistically different from a no farm safety case.

The general pattern of the results suggests that program combination strategies that have a high-profit enhancement potential necessarily have low profit risk for dryland wheat and sorghum production. On the contrary, such a connection is absent for dryland corn and soybeans production. Low-cost farm safety net strategies that enhance corn and soybeans profits do not necessarily lower profit risks.

This paper is one of the first to use a large sample of actual farm-level observations to evaluate how combinations of safety net programs offered under the Title I (PLC, ARCCO and ARCIC) and XI (FCIP) of the U.S. Farm Bill rank in terms of profit level enhancement and profit risk reduction.