Le Chen, NC State University

“Dynamically optimal cover crop adoption”

Abstract: This paper develops a stochastic dynamic programming (SDP) model to investigate optimal cover crop adoption policies taking into account cumulative effects on soil fertility, uncertain future cash crop prices, partial irreversibility of sunk machinery costs, and flexibility in the timing of adoption over time. Based on a dataset from a 35-year cotton field experiment in West Tennessee (1984-2018), we first estimate the static and dynamic yield effects of cover crop adoption and then use these estimates to evaluate the decision to adopt three cover cropping practices — hairy vetch, winter wheat and crimson clover — under conventional till and no-till production systems. Econometric estimates imply significant cumulative effects of cover crops on yields, as well as static and dynamic substitution effects between cover crops and nitrogen fertilizer inputs. Results of our dynamic programming analysis suggest that at historically prevailing prices for nitrogen fertilizer, it’s only optimal for farmers to adopt cover crops with high preexisting levels of soil fertility when no fixed costs are required under conventional tillage, while it’s preferable to adopt earlier if no-till practice has been implemented. However, when new machinery costs need to be incurred, the optimal strategy is for cotton farmers to wait and postpone cover crop adoption until new information that reduces uncertainty is available or the sunk cost of adoption decreases.