Directional aspects of crop yield correlation: Implications for insurance rating and contract design

Author:

Goodwin Barry K.1,Rejesus Roderick2ORCID,Harri Ardian3,Coble Keith4

Affiliation:

1. Departments of Economics and Agricultural and Resource Economics North Carolina State University Raleigh North Carolina USA

2. Department of Agricultural and Resource Economics North Carolina State University Raleigh North Carolina USA

3. Department of Agriculture and Life Sciences Mississippi State University Mississippi State Mississippi USA

4. College of Agriculture and Life Sciences Mississippi State University Mississippi State Mississippi USA

Abstract

AbstractWe estimate directional anisotropic models of linear correlation for crop yields. We find that directional distances (i.e., the degree to which yield correlation decays depending on direction) tend to differ from one another, with east to west distances being “longer” than north to south distances (i.e., correlation tends to decline slower in the east to west direction), at least for the major crops of corn and soybeans. Results for wheat are somewhat ambiguous. However, in all cases, average yield aggregates made up of east to west linked counties tend to be more accurate than is the case for north to south linkages. Implications for rating and contract design in the US area yield federal crop insurance program are offered.

Funder

Risk Management Agency

Publisher

Wiley

Reference23 articles.

1. Access to markets, weather risk, and livestock production decisions: Evidence from Ethiopia

2. Structural Adjustment and Economic Efficiency of Rice Farmers in Northern Ghana

3. A Spatial Econometric Approach to the Economics of Site‐Specific Nitrogen Management in Corn Production

4. Coble Keith BarryGoodwin Mary FrancesMiller RodRejesus ArdianHarri andDanielLinton.2020. “Review of the Pasture Rangeland Forage Rainfall Index Crop Insurance Program Indexing and Rating Methodology Final Report.” Technical Report. Submitted to the RMA.

5. Land Resilience and Tail Dependence among Crop Yield Distributions

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