An Analysis of Cover Crops and Yield Risk: A Parametric Moment Based Approach

The potential benefits of cover crops have been highlighted in the literature, yet there is a limited understanding of their impact on crop yield risk. This study investigates the impact of cover crop adoption on crop yield risk. Specifically, a parametric moment-based approach is utilized to evaluate how cover crops affect the moments of crop yield distribution (i.e., mean yield, yield variance, skewness, and kurtosis). For this study, we utilize a unique county-level panel dataset containing information on cover crop adoption rates, corn and soybean yields, and weather variables. The dataset spans the period from 2005 to 2018 and covers three main corn and soybean production regions in the United States (US) Central Corn Belt (CCB)(i.e., Illinois, Indiana, and Iowa). Along with the parametric moment-based estimation method, several robustness checks in the empirical analysis (e.g., recently developed instrumental variable procedures, long-difference approach, and alternative empirical specifications) are employed. Our estimation results indicate that the counties with higher cover crop adoption tend to lower the production risk.

Bhusal, Keshav thesis final.pdf (1.2 MB)

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