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An application of maximum entropy estimation: the demand for meat in the United Kingdom

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  • Iain Fraser

Abstract

In many econometric studies of demand relationships the design matrix is frequently subject to severe collinearity. In this paper the Generalized Maximum Entropy methodology is introduced and used to estimate a set of demand relationships. The ability of Generalized Maximum Entropy to estimate economic relationships that are typically subject to a high degree of collinearity among the explanatory variables, thus potentially causing traditional methods of estimation to be unreliable, is explained. The results derived by this alternative method of estimation, for a UK meat demand data set, are analysed and examined. The potential for this emerging estimation methodology is discussed.

Suggested Citation

  • Iain Fraser, 2000. "An application of maximum entropy estimation: the demand for meat in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 32(1), pages 45-59.
    • Handle: RePEc:taf:applec:v:32:y:2000:i:1:p:45-59
    DOI: 10.1080/000368400322976
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    References listed on IDEAS

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    1. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    2. Kaplan, Jonathan D. & Howitt, Richard E., 1997. "Nonpoint Source Pollution, Incomplete Information and Learning : An Entropy Approach," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35777, Western Agricultural Economics Association.
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    Cited by:

    1. Rui Fragoso & Maria Leonor da Silva Carvalho, 2013. "Estimation of cost allocation coefficients at the farm level using an entropy approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1893-1906, September.
    2. Esteban Fernández-Vázquez & Matías Mayor-Fernández & Jorge Rodríguez-Vález, 2009. "Estimating Spatial Autoregressive Models by GME-GCE Techniques," International Regional Science Review, , vol. 32(2), pages 148-172, April.
    3. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    4. Qiuqiong Huang & Richard Howitt & Scott Rozelle, 2012. "Estimating production technology for policy analysis: trading off precision and heterogeneity," Journal of Productivity Analysis, Springer, vol. 38(2), pages 219-233, October.
    5. Fernández Vázquez, Esteban & Los, Bart, 2007. "A Maximum Entropy Approach to the Indenitication of Productive Technology Spillovers," Discussion Papers 1106, The Research Institute of the Finnish Economy.
    6. Marsh, Thomas L. & Mittelhammer, Ronald C., 2001. "Adaptive Truncated Estimaton Applied To Maximum Entropy," 2001 Annual Meeting, July 8-11, 2001, Logan, Utah 36169, Western Agricultural Economics Association.
    7. Fernández Vázquez, Esteban, 2011. "Updating weighting matrices by Cross-Entropy," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 53-69.
    8. Nicola Branson, 2009. "Re-weighting the OHS and LFS National household Survey Data to create a consistent series over time: A Cross Entropy Estimation Approach," SALDRU Working Papers 38, Southern Africa Labour and Development Research Unit, University of Cape Town.
    9. Nganou, Jean-Pascal, 2005. "Estimates of Armington parameters for a landlocked economy," MPRA Paper 31459, University Library of Munich, Germany, revised 10 Aug 2008.
    10. Esteban Fernandez-Vazquez, 2011. "Estimating spatial weighting matrices in cross-regressive models by entropy techniques," ERSA conference papers ersa10p503, European Regional Science Association.
    11. Rodriguez-Vález, Jorge & Álvarez, Antonio & Arias, Carlos & Fernández, Esteban, 2005. "Estimating the Productivity of Public Infrastructure using Maximum Entropy Econometrics," Efficiency Series Papers 2005/04, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Matias Mayor Fernandez & Esteban Fernandez Vazquez & Jorge Rodriguez Valez, 2006. "Spatial Structures and Spatial Spillovers: A GME Approach," ERSA conference papers ersa06p777, European Regional Science Association.
    13. Fernández, Esteban & Fernández, Paula, 2008. "An extension to Sun's decomposition methodology: The Path Based approach," Energy Economics, Elsevier, vol. 30(3), pages 1020-1036, May.
    14. Ricardo Troncoso Sepúlveda & Claudio Parés Bengoechea, 2018. "Estimación de la migración de votantes y ubicación de coaliciones políticas usando máxima entropía generalziada. Evidencia en Chile (2001-2013)," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(74), pages 495-522, July.
    15. Rezek, Jon P. & Campbell, Randall C., 2007. "Cost estimates for multiple pollutants: A maximum entropy approach," Energy Economics, Elsevier, vol. 29(3), pages 503-519, May.
    16. R. Carter Hill & Randall C. Campbell, 2001. "Maximum Entropy Estimation in Economic Models with Linear Inequality Restrictions," Departmental Working Papers 2001-11, Department of Economics, Louisiana State University.
    17. Campbell, Randall C. & Hill, R. Carter, 2005. "A Monte Carlo study of the effect of design characteristics on the inequality restricted maximum entropy estimator," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(01), pages 1-30, June.
    18. Ricardo Troncoso Sepúlveda & Claudio Parés Bengoechea, 2018. "Estimación de la migración de votantes y ubicación de coaliciones políticas usando máxima entropía generalizada. Evidencia en Chile (2001-2013)," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 37(74), pages 495-522, July.

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