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Leading Indicators Of Regional Cotton Acreage Response: Structural And Time Series Modeling Results

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  • Houston, Jack E.
  • McIntosh, Christopher S.
  • Stavriotis, Paul A.
  • Turner, Steven C.

Abstract

Resurgent cotton production compels better acreage forecasts for planning seed, chemical, and other input requirements. Structural models describe leading acreage response indicators, and forecasts are compared to time-series models. Cotton price, loan rate, deficiency payments, lagged corn acreage, the PIK program, and previous cotton yield significantly influence cotton acreage response.

Suggested Citation

  • Houston, Jack E. & McIntosh, Christopher S. & Stavriotis, Paul A. & Turner, Steven C., 1999. "Leading Indicators Of Regional Cotton Acreage Response: Structural And Time Series Modeling Results," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 31(3), pages 1-11, December.
    • Handle: RePEc:ags:joaaec:15147
    DOI: 10.22004/ag.econ.15147
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    References listed on IDEAS

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    1. David A. Bessler & Ted Covey, 1993. "On the Search for Econometric Structure in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(Special_I), pages 41-47.
    2. Parrott, Scott D. & McIntosh, Christopher S., 1996. "Nonconstant Price Expectations and Acreage Response: The Case of Cotton Production in Georgia," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 28(1), pages 203-210, July.
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    7. Shideed, Kamil H. & White, Fred C., 1989. "Alternative Forms Of Price Expectations In Supply Analysis For U.S. Corn And Soybean Acreages," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(2), pages 1-12, December.
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    Cited by:

    1. Liang, Yan & Miller, J. Corey & Harri, Ardian & Coble, Keith H., 2011. "Crop Supply Response under Risk: Impacts of Emerging Issues on Southeastern U.S. Agriculture," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(2), pages 181-194, May.
    2. Sanders, Dwight & Altman, Ira J. & Manfredo, Mark R. & Anderson, Rachel, 2009. "Using USDA Production Forecasts: Adjusting for Smoothing," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2009, pages 1-9.
    3. Flanders, Archie, 2014. "Stocks-to-Use Response for Acreage Allocation of Arkansas Field Crops," Journal of the ASFMRA, American Society of Farm Managers and Rural Appraisers, vol. 2014, pages 1-15.
    4. Adhikari, Murali & Houston, Jack E. & Paudel, Laxmi & Bandyopadhyay, Dipankar & Paudel, Biswo Nath & Devkota, Nirmala, 2003. "Forecasting Irrigation Water Demand: A Structural And Time Series Analysis," 2003 Annual meeting, July 27-30, Montreal, Canada 22109, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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    Crop Production/Industries;

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