Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments.

The Agricultural Act of 2014 solidified insurance as the cornerstone of U.S. agricultural policy. The Congressional Budget Office (2014) estimates that this act will increase spending on agricultural insurance programs by $5.7 billion to a total of $89.8 billion over the next decade. In light of the sizable resources directed toward these programs, accurate rating of insurance contracts is of the utmost importance to producers, private insurance companies, and the federal government. Unlike most forms of insurance, agricultural insurance is plagued by a paucity of spatially correlated data. A novel interpretation of Bayesian Model Averaging is used to estimate a set of possibly similar densities that offers greater efficiency if the set of densities are similar while seemingly not losing any if the set of densities are dissimilar. Simulations indicate that finite sample performance—in particular small sample performance—is quite promising. The proposed approach does not require knowledge of the form or extent of any possible similarities, is relatively easy to implement, admits correlated data, and can be used with either parametric or nonparametric estimators. We use the proposed approach to estimate U.S. crop insurance premium rates for area‐type programs and develop a test to evaluate its efficacy. An out‐of‐sample game between private insurance companies and the federal government highlights the policy implications for a variety of crop‐state combinations. Consistent with the simulation results, the performance of the proposed approach with respect to rating area‐type insurance—in particular small sample performance—remains quite promising.

Technological change in plant research rarely shifts the entire yield distribution upwards as assumed in the agricultural economics literature. Rather, technologies have been targeted at a specific subpopulation of the yield distribution-for example, drought resistant seeds or so-called racehorse seeds-therefore, it is unlikely technological advancements are equal across subpopulations. In this manuscript we introduce a mixture model of crop yields with an embedded trend function in the component means, which allows different rates of technological change in each mixture or subpopulation. By doing so, we can test some interesting hypotheses that have been previously untestable. While previous literature assumes an equivalent rate of technological change across subpopulations we reject the null in 84.0%, 82.3%, and 64.0% of the counties for corn, soybean, and wheat respectively. Conversely, with respect to stable subpopulations through time (i.e. climate change) we reject in only 12.0%, 5.4%, and 4.6% of the counties for corn, soybean, and wheat respectively. These results have implications for modelling yields, directing funds regarding plant science research, and explaining the prevalence of heteroscedasticity in yield data.

This paper considers the current and possible institutions (programs, policies, participants, etc.) that govern public Business Risk Management (BRM) in Canada. This is an important policy topic for two reasons: BRM spending accounts for the vast majority of public monies funneled to Canadian agricultural producers and the upcoming Canadian Agricultural Partnership includes a mandated BRM review and thus presents an opportunity to change these institutions in meaningful ways. We pay particular attention to the rhetoric surrounding greater involvement of private insurance, the lack of rhetoric regarding the use of crown corporations, and issues of subsidization. We conclude with policy recommendations favoring commodity‐specific revenue versus whole‐farm net margin insurance, a possible reduction in subsidy levels, and a call to reconsider the role of crown corporations. We also make programming recommendations regarding the discontinued use of private reinsurance, a reduction in the level of program reserves, and greater transparency. Ce document examine les institutions actuelles et potentielles (programmes, politiques, participants, etc.) qui gouvernent la gestion des risques d'entreprises (GRE) au Canada. Deux raisons rendent important ce sujet politique : les dépenses liées á la GRE totalisent la grande majorité des fonds publics accordés aux producteurs agricoles, et le futur cadre politique agricole offre l'occasion de modifier ces institutions de manière significative. Nous portons une attention particulière á la rhétorique entourant l'implication plus soutenue des assurances privées, á l'absence de rhétorique au sujet de l'utilisation de sociétés d'État, et aux enjeux de subvention. Nous concluons avec des recommandations politiques favorisant les assurances de revenus provenant spécifiquement de produits agricoles versus celles de la marge nette de l'exploitation globale, une potentielle réduction des niveaux de subvention, et un appel á tenir compte du rôle des sociétés d'État. Nous proposons aussi des recommandations de programmation concernant l'arrêt de l'utilisation des réassurances privées, une réduction du niveau des programmes de réserve, et une transparence accrue.

In empirical applications with crop yield data, conditioning for heteroscedasticity is both important and challenging. It is important because the scale of the distribution can markedly influence the results, and challenging because statistical tests for the common heteroscedasticity assumptions (constant or proportional variance) often lead to ambiguous conclusions. Alternatively, Harri et al. (2011) proposed a methodology that estimates the degree of heteroscedasticity, removing the need to make a specific assumption. Such approaches assume that volatility changes are symmetric (identical) across tails of the yield distribution. We propose a generalization to the Harri et al. (2011) methodology, which allows asymmetry between the tails, akin to the generalization of GARCH to AGARCH. Using U.S. county level yield data from 1951–2017, we find evidence of asymmetry in corn and soybean, but not wheat. Moreover, the asymmetry takes a particular form—increasing volatility in the lower tail. To investigate economic significance, we consider the effect of imposing symmetric heteroscedasticity in rating crop insurance contracts, as currently done by the USDA's Risk Management Agency in rating their Area Risk Protection products. We find that relaxing the symmetry assumption leads to economically and statistically significant rents. Our results suggest that the Risk Management Agency and others should consider the possibly asymmetric nature of heteroscedasticity in crop yield data.