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Global Drivers of Agricultural Demand and Supply

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  • Sands, Ronald
  • Jones, Carol
  • Marshall, Elizabeth P.

Abstract

Recent volatility in agricultural commodity prices and projections of world population growth raise concerns about the ability of global agricultural production to meet future demand. This report explores the potential for future agricultural production to 2050, using a model-based analysis that incorporates the key drivers of agricultural production, along with the responses of producers and consumers to changes to those drivers. Model results show that for a percentage change in population, global production and consumption of major field crops respond at nearly the same rate. In response to a change in per capita income, the percentage change in crop consumption is much lower, about one-third the percentage change in income. The model also suggests that the global economy absorbs changes in agricultural productivity growth through compensating responses in yield, cropland area, crop prices, and international trade.

Suggested Citation

  • Sands, Ronald & Jones, Carol & Marshall, Elizabeth P., 2014. "Global Drivers of Agricultural Demand and Supply," Economic Research Report 186137, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uersrr:186137
    DOI: 10.22004/ag.econ.186137
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    Cited by:

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    2. Stephan J. Goetz & Meri Davlasheridze, 2017. "State-Level Cooperative Extension Spending and Farmer Exits," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 39(1), pages 65-86.
    3. Junpyo Park, 2022. "Distance to Biorefinery Plants and Its Influence on Agricultural Land Value: Evidence from the United States Midwest Region," Land, MDPI, vol. 11(9), pages 1-14, September.
    4. Thomas W. Hertel & Uris Lantz C. Baldos & Dominique van der Mensbrugghe, 2016. "Predicting Long-Term Food Demand, Cropland Use, and Prices," Annual Review of Resource Economics, Annual Reviews, vol. 8(1), pages 417-441, October.
    5. Cai, Yongxia & Woollacott, Jared & Beach, Robert H. & Rafelski, Lauren E. & Ramig, Christopher & Shelby, Michael, 2023. "Insights from adding transportation sector detail into an economy-wide model: The case of the ADAGE CGE model," Energy Economics, Elsevier, vol. 123(C).
    6. Ronald D. Sands, 2018. "U.S. Carbon Tax Scenarios And Bioenergy," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-12, February.
    7. Chatterjee, Diti & Dinar, Ariel & González-Rivera, Gloria, 2018. "An empirical knowledge production function of agricultural research and extension: The case of the University of California Cooperative Extension," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 290-297.
    8. Capellán-Pérez, Iñigo & de Castro, Carlos & Arto, Iñaki, 2017. "Assessing vulnerabilities and limits in the transition to renewable energies: Land requirements under 100% solar energy scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 760-782.
    9. Talukdar, Swapan & Naikoo, Mohd Waseem & Mallick, Javed & Praveen, Bushra & Shahfahad, & Sharma, Pritee & Islam, Abu Reza Md. Towfiqul & Pal, Swades & Rahman, Atiqur, 2022. "Coupling geographic information system integrated fuzzy logic-analytical hierarchy process with global and machine learning based sensitivity analysis for agricultural suitability mapping," Agricultural Systems, Elsevier, vol. 196(C).

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    Keywords

    Crop Production/Industries; Demand and Price Analysis; Environmental Economics and Policy; Land Economics/Use;
    All these keywords.

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