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Likelihood Diagnostics And Bayesian Analysis Of A Micro-Economic Disequilibrium Model For Retail Services

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  • Kooiman, Peter
  • van Dijk, Herman K.
  • Thurik, A. Roy

Abstract

In this paper we apply Maximum Likelihood and Bayesian methods to explain differences in floorspace productivity among retail establishments in the grocery trade. The model we develop is a switching model where sales are either supply determined or demand determined. Under excess supply the model allows for so-called 'trading-down', i.e., an increase in the share of selling area, and, thereby, a decrease in service level. To estimate our model we employ a cross-section of observations on individual shops. We present maximum likelihood results, and also study the shape of the likelihood surface by means of Monte Carlo numerical integration methods. With a uniform prior we obtain marginal posterior density functions both of the parameters of interest and of the average probability of the excess supply regime in the sample. The average probability of excess supply is .23, with a standard deviation of .06. This shows that, according to our estimates, excess demand is the rule and excess supply the exception in the sample that we analyse.

Suggested Citation

  • Kooiman, Peter & van Dijk, Herman K. & Thurik, A. Roy, 1985. "Likelihood Diagnostics And Bayesian Analysis Of A Micro-Economic Disequilibrium Model For Retail Services," Econometric Institute Archives 272289, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272289
    DOI: 10.22004/ag.econ.272289
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    1. Van Dijk, Herman K. & Kloek, Teun & Boender, C. Guus E., 1985. "Posterior moments computed by mixed integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 3-18.
    2. Maddala, G S & Nelson, Forrest D, 1974. "Maximum Likelihood Methods for Models of Markets in Disequilibrium," Econometrica, Econometric Society, vol. 42(6), pages 1013-1030, November.
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    4. Nicholas M. Kiefer, 1980. "A Note on Regime Classification in Disequilibrium Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(3), pages 637-639.
    5. Goldfelfd, Stephen M. & Quandt, Richard E., 1975. "Estimation in a disequilibrium model and the value of information," Journal of Econometrics, Elsevier, vol. 3(4), pages 325-348, November.
    6. Kooiman, P, 1984. "Smoothing the Aggregate Fix-Price Model and the Use of Business Survey Data," Economic Journal, Royal Economic Society, vol. 94(376), pages 899-913, December.
    7. Ginsburgh, Victor & Tishler, Asher & Zang, Israel, 1980. "Alternative estimation methods for two-regime models : A mathematical programming approach," European Economic Review, Elsevier, vol. 13(2), pages 207-228, March.
    8. Kooiman, P. & Kloek, T., 1985. "An empirical two market disequilibrium model for Dutch manufacturing," European Economic Review, Elsevier, vol. 29(3), pages 323-354.
    9. Laffont, Jean-Jacques & Garcia, Rene, 1977. "Disequilibrium Econometrics for Business Loans," Econometrica, Econometric Society, vol. 45(5), pages 1187-1204, July.
    10. GINSBURGH, Victor & TISHLER, Asher & ZANG, Israel, 1980. "Alternative estimation methods for two-regime models," LIDAM Reprints CORE 393, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. A. Roy Thurik, 1986. "Productivity in Small Business: An Analysis Using African Data," Entrepreneurship Theory and Practice, , vol. 11(1), pages 27-42, July.
    2. van Dijk, H. K., 1987. "Some Advances In Bayesian Estimation Methods Using Monte Carlo Integration," Econometric Institute Archives 272361, Erasmus University Rotterdam.
    3. van Dalen, J. & Koerts, J. & Thurik, A. R., 1987. "The analysis of demand and supply factors in retailing using a disequilibrium model," Econometric Institute Archives 272364, Erasmus University Rotterdam.
    4. H. Vinod, 1989. "Kernel estimation for disequilibrium models for floorspace efficiency in retailing," Journal of Productivity Analysis, Springer, vol. 1(1), pages 79-94, March.

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