Heterogeneity and Distributional Form of Farm-Level Yields

TLDR: In this article, the authors used the extensive potential of government farm-level crop insurance data and evaluated a broader set of parametric distributional possibilities than previously, finding that the systematic intra-county variation is surprisingly strong.

Abstract: Representing farm-level crop yield heterogeneity and distributional form is critical for risk and crop insuranceresearch.Moststudieshaveusedcountydata,understatingbothsystematicandrandomvariation. Comparison of systematic versus random intra-county variation is lacking. Few studies compare the various distributional forms that have been proposed. This study utilizes the extensive potential of government farm-level crop insurance data. Results show that systematic intra-county variation is surprisingly strong. A newly applied reverse lognormal distribution is preferred when county-wide variation is removed, but the normal distribution fits surprisingly well in the crop insurance relevant percentiles when county-wide variation is not removed. Representing and accounting for both spatial and temporal heterogeneity is a major problem in agricultural economics and policy analysis due to the fact that most data are aggregated to at least the county level (e.g., Gardner and Kramer 1986; Just and Pope 1999). Both systematic and random components of crop yields are major factors in intra-county farm-level heterogeneity that are critical for modeling risk, producer behavior, and crop insurance participation. Most studies have either used aggregate (at least county-level) data or relied on relatively few farm-level observations. The former makes results primarily illustrative, while the latter limits statistical significance. This article characterizes intra-county crop yield heterogeneity both spatially and temporally with the most extensive dataset utilized to date and evaluates a broader set of parametric distributional possibilities than previously.