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A Cox Parametric Bootstrap Test of the von Liebig Hypotheses

Author

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  • Simeon Kaitibie
  • William E. Nganje
  • B. Wade Brorsen
  • Francis M. Epplin

Abstract

This study uses a Cox parametric bootstrap test to select between two specifications of the von Liebig hypothesis, a switching regression (SR) model, and a linear response function with a stochastic plateau. Specifying the production function as a linear response function with a stochastic plateau yields a superior approximation of the data for livestock gain as a function of forage allowance than the SR approach. Dans la présente étude, nous avons utilisé la technique du bootstrap paramétrique de Cox pour choisir entre deux caractéristiques de l'hypothèse de von Liebig: un modèle de régression avec changement de régime et une fonction de réponse linéaire avec plateau stochastique. établir la fonction de production comme une fonction de réponse linéaire avec plateau stochastique offre une meilleure approximation des données sur le gain de poids du bétail comme fonction de l'apport de fourrages comparativement au modèle de régression avec changement de régime.

Suggested Citation

  • Simeon Kaitibie & William E. Nganje & B. Wade Brorsen & Francis M. Epplin, 2007. "A Cox Parametric Bootstrap Test of the von Liebig Hypotheses," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 55(1), pages 15-25, March.
    • Handle: RePEc:bla:canjag:v:55:y:2007:i:1:p:15-25
    DOI: 10.1111/j.1744-7976.2007.00077.x
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    References listed on IDEAS

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    1. Tembo, Gelson & Brorsen, B. Wade & Epplin, Francis M., 2003. "Linear Response Stochastic Plateau Functions," 2003 Annual Meeting, February 1-5, 2003, Mobile, Alabama 35217, Southern Agricultural Economics Association.
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    Cited by:

    1. Klaus Moeltner & A. Ford Ramsey & Clinton L. Neill, 2021. "Bayesian Kinked Regression with Unobserved Thresholds: An Application to the von Liebig Hypothesis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1832-1856, October.
    2. Jon T. Biermacher & B. Wade Brorsen & Francis M. Epplin & John B. Solie & William R. Raun, 2009. "The economic potential of precision nitrogen application with wheat based on plant sensing," Agricultural Economics, International Association of Agricultural Economists, vol. 40(4), pages 397-407, July.
    3. Kwabena Nyarko Addai & John N. Ng’ombe & Simeon Kaitibie, 2022. "A Dose–Response Analysis of Rice Yield to Agrochemical Use in Ghana," Agriculture, MDPI, vol. 12(10), pages 1-15, September.

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