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Global growing‐area elasticities of key agricultural crops estimated using dynamic heterogeneous panel methods

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  • Md Zabid Iqbal
  • Bruce A. Babcock

Abstract

We estimate the short‐ and long‐run global response of corn, soybeans, wheat, and rice growing areas to output price changes allowing responses to vary across countries using methods from the panel time‐series literature. Our estimates of growing‐area response are considerably lower than estimates obtained using more traditional models. Previous findings appear biased due to the assumption of homogeneous response across countries. Our aggregate estimates of short‐ and long‐run elasticities of four crop growing areas with respect to average price are 0.024 and 0.143, respectively. Crop‐specific results indicate that both corn and soybean growing areas are generally more responsive than wheat and rice. For corn and soybeans, the long‐run own‐price growing‐area elasticities are 0.274 and 0.793, respectively. The long‐run own‐price elasticities for wheat and rice are 0.279 and 0.045, respectively. The short‐run own‐price elasticities for corn and soybeans are 0.133 and 0.199, respectively, which are higher than wheat (0.037) and rice (0.00001).

Suggested Citation

  • Md Zabid Iqbal & Bruce A. Babcock, 2018. "Global growing‐area elasticities of key agricultural crops estimated using dynamic heterogeneous panel methods," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 681-690, November.
  • Handle: RePEc:bla:agecon:v:49:y:2018:i:6:p:681-690
    DOI: 10.1111/agec.12452
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    2. Zhao, Xin & Calvin, Katherine & Wise, Marshall, 2020. "The critical role of conversion cost and comparative advantage in modeling agricultural land use change," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304204, Agricultural and Applied Economics Association.
    3. Valenti, Daniele & Bertoni, Danilo & Cavicchioli, Davide & Olper, Alessandro, 2023. "Understanding the role of supply and demand factors in the global wheat market: a Structural Vector Autoregressive approach," FEEM Working Papers 338780, Fondazione Eni Enrico Mattei (FEEM).
    4. Xin Zhao & Katherine V. Calvin & Marshall A. Wise, 2020. "The Critical Role Of Conversion Cost And Comparative Advantage In Modeling Agricultural Land Use Change," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-44, February.

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