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The purpose of this paper is to analyze the effect of the 2008 Farm Bill's average crop revenue election (ACRE) program on the risk‐reducing effectiveness of crop insurance products.

Three crop/region combinations are examined, representing regions with both high and low price‐yield correlation regions. Actual production history (APH) and crop revenue coverage (CRC) insurance instruments are considered separately under the 2002 Farm Bill and under ACRE. Monte Carlo simulations, combined with the copula approach, are used to simulate net wealth distributions and to calculate the corresponding expected utilities. The outcomes are evaluated using certainty‐equivalent wealth based on different risk premium assumptions.

Crop insurance contracts appear to be more effective under the 2002 Farm Bill than under ACRE, especially for crops characterized by low yield‐price correlation. CRC insurance is found to be more effective than APH insurance for all crop/region combinations considered.

The paper only considers a static framework and farm‐level insurance contracts. Further research could investigate how ACRE affects decoupled income support, whether the results change if Supplemental Revenue Assistance is included, or how different the outcomes might be for multiple‐crop farms.

The results suggest that risk‐reducing effectiveness decreases under ACRE and that no reasonable adjustment to APH base price can make APH competitive with CRC for any crop/regions considered.

The risk‐reducing effectiveness of the 2008 Farm Bill's ACRE program is analyzed, and as a methodological contribution the copula approach is used to model the multivariate distribution of yields and prices.

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.

In recent years, prices for prime farmland have increased substantially, begging the question is the dramatic increase the result of a speculative bubble or consistent with market fundamentals with increases driven by increased global demand, low interest rates, and recent changes to US agricultural and energy policies. The purpose of this paper is to investigate the impacts of recent agricultural support policies and ethanol policies on farmland values and rental rates.

Farm-level Agricultural Resource Management Survey data collected by the United States Department of Agriculture (USDA) between 1998 and 2008 as well as county-level data collected by the USDA, US Census Bureau, and Bureau of Economic Analysis are used to determine the impacts of recent agricultural support policies and ethanol policies on farmland values and rental rates, while controlling for parcel characteristics and urban pressure. Specifically, weighted ordinary least squares and two-stage least squares are used to investigate the impact of various governmental agricultural support policies, corn ethanol facilities location, and local corn ethanol production capacity on farmland values and rental rates.

The results indicate that government payments, urban pressure, and the proximity of the parcel to an ethanol facility have a positive impact on both farmland values and rental rates. More specifically, parcels located in the same county as at least one corn ethanol facility are more valuable and command higher rental rates. In addition, county-level ethanol production capacity is positively associated with farmland values and rental rates. An inverse relationship between distance of the parcels from an ethanol facility and farmland values is also found; a similar result is found for rental rates.

The findings suggest that agricultural support payments and ethanol policies are capitalized into farmland values. These findings have important implications for the formulation of future farm policy. A limitation of the analyses is that farmland values are estimated by landowners; future research could utilize farmland transaction data to overcome potential biases generated by using landowner estimates. In addition, while our study period covers 11 years, future research could expand the time period further to analyze the effect of more recent agricultural and ethanol policies.

This paper extends prior research pertaining to factors influencing farmland values and rental rates by also examining the proximity of the parcel to an operating ethanol facility using a unique data set.

For over 20 years, decoupled agricultural support programs have played a large role in farm policy. The purpose of this paper is to investigate the effects of decoupled agricultural support payments on farm-level debt.

A two-stage least squares model is used to estimate the impact of decoupled payments, farm production characteristics, demographics, regional risk factors, as well as cross-sectional and temporal fixed effects on farm debt, along with weather-related instrumental variables.

Results indicate that a negative and statistically significant relationship exists between decoupled payments and farm debt. This study also provides evidence that research results not accounting for the endogenous relationship between acres operated and farm-level debt should be interpreted with caution.

The constantly changing sets of policy options provide a challenge in identifying the impact of a single policy, ceteris paribus. Therefore, one notable limitation is in extrapolating the results in this study to make implications on the elimination of the direct payments program, as part of the 2014 Farm Bill.

This implies that farmers likely use annual decoupled payments to reduce their debt, potentially influencing their exposure to financial risks, capacity to withstand financial instability, and access to credit. The methodology used may establish a foundation for continued research that seeks to empirically identify and measure the complex interrelationships among agricultural public policies and farm-level financial measures.

Decoupled payment programs may indirectly influence debt decisions, which can influence production decisions in the long run.

In order to accurately identify the impact of direct payment programs on farm debt levels, this study is the first of its kind to account for the endogenous relationship between production decisions and debt and use a large unbalanced panel of data available from the Agricultural Resource Management Survey.

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.

US decoupled direct payments, paid to farm operators based on historic yields and base acreage under the 2002 Farm Bill, may alter a farmer's access to credit or his ability to meet debt servicing obligations. More specifically, direct payments might improve the farmer's liquidity position or repayment capacity enabling the farmer to obtain more favorable credit terms. In turn, more favorable credit terms might allow a farm to remain in business or expand production, leading to current production distortions. Since direct payments are based on historic production, beginning farmers tend to receive lower levels of direct payments and hence these payments might impact beginning farmers differently than more experienced farmers. The purpose of this paper is to investigate the effects of direct payments on liquidity and repayment capacity for experienced and beginning farmers.

Given the manner in which direct payments are calculated and administered, it is likely that direct payments affect beginning farmers and more experienced farmers differently; hence the authors analyze the impacts of direct payments on the current and term debt coverage ratios for these two groups separately. In the analysis, the authors control for farm financial characteristics, farm operator characteristics, and other factors. Data from the US Department of Agriculture (USDA) Agricultural Resource Management Survey (ARMS) for the years 2005, 2006, and 2007 were used in the weighted regression analysis and jackknifed standard errors computed.

A positive significant relationship was found between the level of direct payments (in dollars) and the term debt coverage ratio for experienced farmers, suggesting that direct payments improve repayment capacity. However, this relationship is not significant for beginning farmers. Also, a negative significant relationship was found between the number of base acres and the current ratio for experienced farmers, while this relationship lacks significance for beginning farmers.

The paper provides evidence that decoupled direct payments impact a farmer's liquidity and repayment capacity. Furthermore, direct payments impact beginning and experienced farmers differently. This paper also contributes to the growing body of research investigating the mechanisms by which decoupled payments have the potential to distort current production.

In the United States, successive farm bills and the 2007 Renewable Fuels Standard (RFS) have largely defined domestic subsidy and conservation programs and U.S. food-aid initiatives over the past decade. This chapter examines the effects of the current mixture of U.S. agricultural policies and international food-aid programs on domestic and global food-insecure populations. A detailed research-based examination is carried out with respect to the impacts of U.S. subsidy programs on agricultural production, domestic and global agricultural commodity prices, and their implications for food-insecure populations. The impacts of the RFS are assessed along with the effects of current and potentially reformed U.S. international food-aid programs.

This study concludes that current U.S. agricultural subsidy programs have small or negligible impacts on the aggregate level and mixture of U.S. agricultural output, U.S. domestic prices and global prices, and domestic and global food insecurity among poor households. The RFS has increased prices for food and feed grain and oilseeds with adverse implications for the urban poor in developing countries and some poor U.S. households. The portfolios of U.S. food-aid programs are managed inefficiently because of congressional mandates designed to aid special interest groups that waste 30% of the current budget. While U.S. subsidy programs likely should be moderated for other reasons, they have few impacts on domestic and globally food-insecure households. However, in relation to global and domestic food insecurity, the RFS should be discontinued and major reforms to U.S. international food aid implemented.

Regional differences in crop insurance uptake have persisted over time. To partly explain this phenomenon, the purpose of this paper is to propose and evaluate a budget constraint (heuristic) effect within the standard expected utility theory (EUT) framework through simulation methods.

Within the EUT framework, a standard simulation model is used to gain insights into farm insurance decisions when a budget constraint is in effect. The budget constraint is modeled as it has been revealed through the data on farmers’ insurance expenditures. In the simulation analysis, certainty equivalent values are used to rank farm options subject to the revealed budget constraint.

A budget constraint effect within the EUT framework stands out in explaining the observed regional differences. The proposed explanation is consistent with the historical trends on the ratio of crop insurance expenditure to expected crop value, higher premium rates in regions with lower crop insurance uptake, and the limited turnout for the 2014 Farm Bill’s supplemental area-based crop insurance products. Farmers’ crop insurance choices are found to be mostly constrained-optimal.

This appears to be the first study taking the revealed preferences approach to farmers’ crop insurance choices in a simulation analysis. Some policy implications are drawn and future research avenues are suggested. The findings should be of considerable value to policymakers, academics, bankers, and producers in regard to the design and use of risk management tools.

The purpose of this paper is to use a linked-farm approach and a cohort approach to estimate farm entry and exit rates using the US Census of Agriculture. The number of new farms entering agriculture was re-estimated and adjusted upward since not all new and beginning farmers are known to US Department of Agriculture.

In addition to a linked-farm approach (linking farms over time), a cohort approach (farms that started operating in the same year) is used to determine exit rates conditional on the number of years a farm has been operating. Linear forecasting, moving-average forecasting, and using data from a later Census are used to re-estimate the number of new farms in their first year of operating.

Using the linked-farm approach, an average annual entry rate of 7.5 percent and exit rate of 8.5 percent is estimated for 2007 to 2012, which vary based on the farmer’s lifecycle. The cohort approach shows that exit rates are lower than 4 percent for the first 40 years of operating a farm business and then exit rates gradually increase. Revised estimates of approximately 70-80,000 new farms entering each year are calculated, which are considerably higher numbers than the 30-40,000 new farm entrants participating in the Census of Agriculture.

The linked-farm and cohort approaches are used to provide updated estimates for farm entry and exit using new Census data and to make comparisons with previous years. To the authors’ knowledge, this is the first study to provide revised estimates for new farm entrants into US agriculture.