Estimating Field-Level Rotations as Dynamic Cycles

Duncan MacEwan () and Richard E. Howitt ()
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Duncan MacEwan: ERA Economics
Richard E. Howitt: ERA Economics

Chapter Chapter 9 in Applied Methods for Agriculture and Natural Resource Management, 2019, pp 145-169 from Springer

Abstract: Abstract Crop rotation systems are an important part of agricultural production for managing pests, diseases, and soil fertility. Recent interest in sustainable agriculture focuses on low input-use practices which require knowledge of the underlying dynamics of production and rotation systems. Policies to limit chemical application depending on proximity to waterways and flood management require field-level data and analysis. Additionally, many supply estimates of crop production omit the dynamic effects of crop rotations. We estimate a dynamic programming model of crop rotation which incorporates yield and cost intertemporal effects in addition to field-specific factors including salinity and soil quality. Using an Optimal Matching algorithm from the Bioinformatics literature, we determine empirically observed rotations using a geo-referenced panel dataset of 14,000 fields over 13 years. We estimate the production parameters which satisfy the Euler equations of the field-level rotation problem and solve an empirically observed four-crop rotation.

Date: 2019
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DOI: 10.1007/978-3-030-13487-7_9

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