C  The Journal of Risk and Insurance, 2012, Vol. 79, No. 1, 261-285 DOI: 10.1111/j.1539-6975.2010.01397.x ASPATIAL ECONOMETRIC ANALYSIS OF LOSS EXPERIENCE IN THE U.S. CROP INSURANCE PROGRAM Joshua D. Woodard Gary D. Schnitkey Bruce J. Sherrick Nancy Lozano-Gracia Luc Anselin ABSTRACT Patterns in loss-ratio experience in the U.S. corn insurance market are investi- gated with a spatial econometric model. The results demonstrate systematic geographically related misratings and provide estimates of the impacts of several observable factors on the magnitude of misrating in the program. The model is used to estimate actuarial cross-subsidizations across the primary corn-producing states and counties. The impacts of the primary factors are substantial, resulting in net premium transfers of approximately 26 percent of total premiums annually. The misratings likely have important insurance demand, welfare, and land-use implications. Insurance markets are typically best suited for risks that are uncorrelated, occur with high frequency, and have a large number of like participants—among a handful of other standard conditions. Systemic risks (such as in crop production) induce correlation in losses, violating the standard insurability conditions and potentially leading to market failures (Glauber, 2004). Complementary causes of market failures in such systemic risk markets may include capital market imperfections, inadequate reinsurance capacities, capital and information shocks due to unexpected events, fat- tailed distributions that prevent diversification, and agency problems (see, e.g., Froot, Joshua D. Woodard is Assistant Professor in the Department of Agricultural Economics at Texas A&M University. Gary D. Schnitkey and Bruce J. Sherrick are Professors, both in the Department of Agricultural & Consumer Economics at the University of Illinois at Urbana-Champaign. Nancy Lozano-Gracia is an Economist at the World Bank. Luc Anselin is Walter Isard Chair and Director, School of Geographical Sciences and Urban Planning, and Director GeoDa Center for Geospatial Analysis and Computation, Arizona State University. Joshua D. Woodard can be contacted via e-mail: woodardjoshua@gmail.com. This manuscript is adapted from a chapter of Woodard’s PhD dissertation. The authors would like to thank the editor, Georges Dionne, and two anonymous reviewers, as well as Jeffrey R. Brown, Philip Garcia, Nicholas D. Paulson, and seminar participants at Georgia State University, Iowa State University, University of Georgia, New Mexico State University, Purdue University, University of Illinois, and Texas A&M University for helpful comments and suggestions. 261