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Semiparametric estimation of consumer demand systems in real expenditure

Author

Listed:
  • Krishna Pendakur

    (Department of Economics, Simon Fraser University, Burnaby, BC, Canada)

  • Stefan Sperlich

    (Georg-August Universitat Gottingen, Institut fur Statistik und ÷konometrie, Gˆttingen, Germany)

Abstract

Microdata concerning consumer demand typically show considerable variation in real expenditures, but very little variation in prices. We propose a semiparametric strategy for the consumer demand problem in which expenditure share equations are estimated nonparametrically in the real expenditure direction and estimated parametrically (with fixed or varying coefficients) in price directions. In our model, Engel curves are unrestricted: demands may have any rank. Because the demand model is derived from a cost function, it may be restricted to satisfy integrability and used for consumer surplus calculations. Since real expenditure is unobserved, but rather estimated under the model, we face a semiparametric model with a nonparametrically generated regressor. We show efficient convergence rates for parametric and nonparametric components. We illustrate the feasibility of our proposed strategy using Canadian expenditure and price data: Engel curves display curvature which cannot be encompassed by standard parametric models. We also find that the rationality restriction of Slutsky symmetry is rejected in the fixed-coefficients model, but not in the varying-coefficients model. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Krishna Pendakur & Stefan Sperlich, 2010. "Semiparametric estimation of consumer demand systems in real expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 420-457.
  • Handle: RePEc:jae:japmet:v:25:y:2010:i:3:p:420-457
    DOI: 10.1002/jae.1085
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    References listed on IDEAS

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    Cited by:

    1. Stefan Sperlich & Raoul Theler, 2015. "Modeling heterogeneity: a praise for varying-coefficient models in causal analysis," Computational Statistics, Springer, vol. 30(3), pages 693-718, September.
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    3. Simona Bigerna & Carlo Andrea Bollino & Maria Chiara D’Errico, 2020. "A general expenditure system for estimation of consumer demand functions," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 1071-1088, October.
    4. Christian Dudel & Jan Marvin Garbuszus & Julian Schmied, 2021. "Assessing differences in household needs: a comparison of approaches for the estimation of equivalence scales using German expenditure data," Empirical Economics, Springer, vol. 60(4), pages 1629-1659, April.

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