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A Markov Chain Analysis Of Structural Changes In The Texas High Plains Cotton Ginning Industry

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  • Ethridge, Don E.
  • Roy, Sujit K.
  • Myers, David W.

Abstract

Markov chain analysis of changes in the number and size of cotton gin firms in West Texas was conducted assuming stationary and non-stationary transition probabilities. Projections of industry structure were made to 1999 with stationary probability assumptions and six sets of assumed conditions for labor and energy costs and technological change in the non-stationary transition model. Results indicate a continued decline in number of firms, but labor, energy, and technology conditions alter the configuration of the structural changes.

Suggested Citation

  • Ethridge, Don E. & Roy, Sujit K. & Myers, David W., 1985. "A Markov Chain Analysis Of Structural Changes In The Texas High Plains Cotton Ginning Industry," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 17(2), pages 1-10, December.
  • Handle: RePEc:ags:sojoae:29968
    DOI: 10.22004/ag.econ.29968
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    References listed on IDEAS

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    1. Campbell, John D., 1969. "Central Cotton Ginning: Comparative Costs, Use in Other Countries, and Potential Use in the United States," Farmer Cooperative Research Report (FCRR) 314175, United States Department of Agriculture, Economic Research Service.
    2. Shaw, Dale L. & Cleveland Jr, O. A. & Ghetii, Joseph L., 1977. "Economic Models for Cotton Ginning," Archive 259784, Texas Tech University, Department of Agricultural and Applied Economics.
    3. Bernard F. Stanton & Lauri Kettunen, 1967. "Potential Entrants and Projections in Markov Process Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 49(3), pages 633-642.
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    Cited by:

    1. Disney, W. Terry & Duffy, Patricia A. & Hardy, William E., Jr., 1988. "A Markov Chain Analysis Of Pork Farm Size Distributions In The South," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 20(2), pages 1-8, December.
    2. Zimmermann, Andrea & Heckelei, Thomas, 2012. "Differences of farm structural change across European regions," Discussion Papers 162879, University of Bonn, Institute for Food and Resource Economics.
    3. Stokes, Jeffrey R., 2006. "Entry, Exit, and Structural Change in Pennsylvania's Dairy Sector," Agricultural and Resource Economics Review, Cambridge University Press, vol. 35(2), pages 357-373, October.
    4. Hua, Wei & Sohngen, Brent & Hite, Diane, 2005. "Assessing the Relationship Between Crop Choice and Land Use Change Using A Markov Model," 2005 Annual meeting, July 24-27, Providence, RI 19257, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Legrand D. F. Saint‐Cyr, 2022. "Heterogeneous farm‐size dynamics and impacts of subsidies from agricultural policy: Evidence from France," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 893-923, September.
    6. Alexander Gocht & Norbert Röder & Sebastian Neuenfeldt & Hugo Storm & Thomas Heckelei, 2012. "Modelling farm structural change: A feasibility study for ex-post modelling utilizing FADN and FSS data in Germany and developing an ex-ante forecast module for the CAPRI farm type layer baseline," JRC Research Reports JRC75524, Joint Research Centre (Seville site).
    7. Legrand D. F, Saint-Cyr, 2017. "Farm heterogeneity and agricultural policy impacts on size dynamics: evidence from France," Working Papers SMART 17-04, INRAE UMR SMART.

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    Keywords

    Crop Production/Industries;

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