The relation between wheat, soybean, and hemp acreage: a Bayesian time series analysis

Joohun Han () and John N. Ng’ombe
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Joohun Han: University of Arkansas
John N. Ng’ombe: North Carolina A&T State University

Agricultural and Food Economics, 2023, vol. 11, issue 1, 1-12

Abstract: Abstract The 2018 United States Farm Bill has opened the possibility for farmers to increase their profits through hemp cultivation. The literature suggests hemp has the potential to replace soybeans in soybean–wheat double-cropping because hemp shares key attributes of soybeans as a rotation crop (profitability, potential as an energy crop, and maintenance of soil fertility). Nonetheless, due to a short history of hemp cultivation in the USA, it is difficult to predict a time series relationship between hemp, soybean, and wheat through conventional approaches. In this article, we use Bayesian time series models and data from Statistics Canada and the Alberta Agricultural and Rural Development Department to examine a time series relationship between hemp, wheat, and soybean acreage and therefore predict farmers’ decision when hemp is a legal alternative agricultural commodity. Our results show evidence of complementary and substitution relationships for hemp–wheat and hemp–soybean, respectively. In addition, the results indicate a potential of hemp monoculture as a positive response to self-positive shock on hemp acreage that lasts for years.

Keywords: Industrial hemp; Wheat; Double-cropping; Bayesian vector autoregressive model; Impulse response analysis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1186/s40100-023-00242-1

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