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Mitigating The Effects Of Multicollinearity Using Exact And Stochastic Restrictions: The Case Of An Aggregate Agricultural Production Function For Thailand

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  • Mittelhammer, Ron C.
  • Young, Douglas L.
  • Tasanasanta, Damrongsak
  • Donnelly, JohnT.

Abstract

Mixed estimation and OLS were each used to estimate an aggregate agricultural production function for Thailand for which data were highly multicollinear. The final mixed model obtained using minimax regret in the pretest appeared to significantly outperform OLS in terms of precision and overall reasonableness, mitigating a serious multicollinearity problem.

Suggested Citation

  • Mittelhammer, Ron C. & Young, Douglas L. & Tasanasanta, Damrongsak & Donnelly, JohnT., 1979. "Mitigating The Effects Of Multicollinearity Using Exact And Stochastic Restrictions: The Case Of An Aggregate Agricultural Production Function For Thailand," 1979 Annual Meeting, July 29-August 1, Pullman, Washington 278283, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea79:278283
    DOI: 10.22004/ag.econ.278283
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    References listed on IDEAS

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    1. Masakatsu Akino & Yujiro Hayami, 1974. "Sources of Agricultural Growth in Japan, 1880–1965," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 88(3), pages 454-479.
    2. Judge, G. G. & Yancey, T. A. & Bock, M. E., 1973. "Properties of estimators after preliminary tests of significance when stochastic restrictions are used in regression," Journal of Econometrics, Elsevier, vol. 1(1), pages 29-47, March.
    3. Johnston, Bruce F, 1970. "Agriculture and Structural Transformation in Developing Countries: A Survey of Research," Journal of Economic Literature, American Economic Association, vol. 8(2), pages 369-404, June.
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