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"The U.S. has a long history of providing generous support for the agricultural sector. A recent omnibus package of farm legislation, the 2008 Farm Bill (P.L. 110-246) will provide in excess of $284 billion in financial support to U.S. agriculture over the 2008-2012 period. Commodity program payments account for $43.3 billion of this total. Our paper is concerned with the distribution of these benefits. Farm subsidies make agricultural production more profitable by increasing and stabilizing farm prices and incomes. If these benefits are expected to persist, farm land values should capture the subsidy benefits. We use a large sample of individual farm land values to investigate the extent of this capitalization of benefits. Our results confirm that subsidies have a very significant impact on farm land values and thus suggest that landowners are the real benefactors of farm programs. As land is exchanged, new owners will pay prices that reflect these benefits, leaving the benefits of farm programs in the hands of former owners that may be exiting production. Approximately 45% of U.S. farmland is operated by someone other than the owner. We report evidence that owners benefit not only from capital gains but also from lease rates which incorporate a significant portion of agricultural payments even if the farm legislation mandates that benefits must be allocated to producers. Finally, we examine rental agreements for farmers that rent land on both a cash and share basis. We find evidence that farm programs that are meant to stabilize farm prices provide a valuable insurance benefit"--National Bureau of Economic Research web site

The federal crop insurance program covered more than 110 billion dollars in total liability in 2018. The program consists of policies across a wide range of crops, plans, and locations. Weather and other latent variables induce dependence among components of the portfolio. Computing value-at-risk (VaR) is important because the Standard Reinsurance Agreement (SRA) allows for a portion of the risk to be transferred to the federal government. Further, the international reinsurance industry is extensively involved in risk sharing arrangements with U.S. crop insurers. VaR is an important measure of the risk of an insurance portfolio. In this context, VaR is typically expressed in terms of probable maximum loss (PML) or as a return period, whereby a loss of certain magnitude is expected to return within a given period of time. Determining bounds on VaR is complicated by the non-homogeneous nature of crop insurance portfolios. We consider several different scenarios for the marginal distributions of losses and provide sharp bounds on VaR using a rearrangement algorithm. Our results are related to alternative measures of portfolio risks based on multivariate distribution functions and alternative copula specifications. ; Published version

The federal crop insurance program covered more than 110 billion dollars in total liability in 2018. The program consists of policies across a wide range of crops, plans, and locations. Weather and other latent variables induce dependence among components of the portfolio. Computing value-at-risk (VaR) is important because the Standard Reinsurance Agreement (SRA) allows for a portion of the risk to be transferred to the federal government. Further, the international reinsurance industry is extensively involved in risk sharing arrangements with U.S. crop insurers. VaR is an important measure of the risk of an insurance portfolio. In this context, VaR is typically expressed in terms of probable maximum loss (PML) or as a return period, whereby a loss of certain magnitude is expected to return within a given period of time. Determining bounds on VaR is complicated by the non-homogeneous nature of crop insurance portfolios. We consider several different scenarios for the marginal distributions of losses and provide sharp bounds on VaR using a rearrangement algorithm. Our results are related to alternative measures of portfolio risks based on multivariate distribution functions and alternative copula specifications.