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Empirical factor demands and flexible functional forms: a bayesian approach

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  • Matteo Manera
  • Bruno Sitzia

Abstract

In this paper we compare classical econometrics, calibration and Bayesian inference in the context of the empirical analysis of factor demands. Our application is based on a popular flexible functional form for the firm's cost function, namely Diewert's Generalized Leontief function, and uses the well-known Berndt and Wood 1947-1971 KLEM data on the US manufacturing sector. We illustrate how the Gibbs sampling methodology can be easily used to calibrate parameter values and elasticities on the basis of previous knowledge from alternative studies on the same data, but with different functional forms. We rely on a system of mixed non-informative diffuse priors for some key parameters and informative tight priors for others. Within the Gibbs sampler, we employ rejection sampling to incorporate parameter restrictions, which are suggested by economic theory but in general rejected by economic data. Our results show that values of those parameters that relate to non-informative priors are almost equal to the standard SUR estimates, whereas differences come out for those parameters to which we have assigned informative priors. Moreover, discrepancies can be appreciated in some crucial parameter estimates obtained with or without rejection sampling.

Suggested Citation

  • Matteo Manera & Bruno Sitzia, 2005. "Empirical factor demands and flexible functional forms: a bayesian approach," Economic Systems Research, Taylor & Francis Journals, vol. 17(1), pages 57-75.
  • Handle: RePEc:taf:ecsysr:v:17:y:2005:i:1:p:57-75
    DOI: 10.1080/09535310500034333
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    1. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
    2. MacKinnon, James G. & White, Halbert & Davidson, Russell, 1983. "Tests for model specification in the presence of alternative hypotheses : Some further results," Journal of Econometrics, Elsevier, vol. 21(1), pages 53-70, January.
    3. Chib, Siddhartha, 1993. "Bayes regression with autoregressive errors : A Gibbs sampling approach," Journal of Econometrics, Elsevier, vol. 58(3), pages 275-294, August.
    4. Lars Peter Hansen & James J. Heckman, 1996. "The Empirical Foundations of Calibration," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 87-104, Winter.
    5. Fabio Canova & Eva Ortega, 1996. "Testing calibrated general equilibrium models," Economics Working Papers 166, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Matteo Manera & Michael McAleer, 2001. "Testing Multiple Non-nested Factor Demand Systems," ISER Discussion Paper 0543, Institute of Social and Economic Research, Osaka University.
    7. Berndt, Ernst R & Darrough, Masako N & Diewert, W E, 1977. "Flexible Functional Forms and Expenditure Distributions: An Application to Canadian Consumer Demand Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(3), pages 651-675, October.
    8. Barten, A.P. & Mcaleer, M., 1991. "Comparing The Empirical Perfomance Of Alternative Demand Systems," Papers 9002a, Tilburg - Center for Economic Research.
    9. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    10. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    11. Terrell, Dek, 1996. "Incorporating Monotonicity and Concavity Conditions in Flexible Functional Forms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 179-194, March-Apr.
    12. Edward R. Morey, 1986. "An Introduction to Checking, Testing, and Imposing Curvature Properties: The True Function and the Estimated Function," Canadian Journal of Economics, Canadian Economics Association, vol. 19(2), pages 207-235, May.
    13. Galeotti, Marzio, 1996. " The Intertemporal Dimension of Neoclassical Production Theory," Journal of Economic Surveys, Wiley Blackwell, vol. 10(4), pages 421-460, December.
    14. Guilkey, David K & Lovell, C A Knox, 1980. "On the Flexibility of the Translog Approximation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 137-147, February.
    15. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-346, July.
    16. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139.
    17. Matteo Manera, 2002. "Testing misspecified non-nested factor demand systems: Some Monte Carlo results," Empirical Economics, Springer, vol. 27(4), pages 657-686.
    18. Wales, Terence J., 1977. "On the flexibility of flexible functional forms : An empirical approach," Journal of Econometrics, Elsevier, vol. 5(2), pages 183-193, March.
    19. Thomsen, Thomas, 2000. "Short cuts to dynamic factor demand modelling," Journal of Econometrics, Elsevier, vol. 97(1), pages 1-23, July.
    20. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    21. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
    22. Despotakis, Kostas A., 1986. "Economic performance of flexible functional forms: Implications for equilibrium modeling," European Economic Review, Elsevier, vol. 30(6), pages 1107-1143, December.
    23. Appelbaum, Elie, 1979. "On the Choice of Functional Forms," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(2), pages 449-458, June.
    24. Guilkey, David K & Lovell, C A Knox & Sickles, Robin C, 1983. "A Comparison of the Performance of Three Flexible Functional Forms," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 591-616, October.
    25. Fleissig, Adrian R. & Kastens, Terry & Terrell, Dek, 2000. "Evaluating the semi-nonparametric fourier, aim, and neural networks cost functions," Economics Letters, Elsevier, vol. 68(3), pages 235-244, September.
    26. Berndt, Ernst R & Khaled, Mohammed S, 1979. "Parametric Productivity Measurement and Choice among Flexible Functional Forms," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1220-1245, December.
    27. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, January.
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