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Collective Decision-Making and Heterogeneity in Tastes

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  • Luo, Guo Ying

Abstract

This article begins by proposing a random taste parameterization of a quadratic extension of the PIGLOG demand system at the household level, which is consistent with exact aggregation. This variation in tastes is a random function of household characteristics. The econometric implication is that a well-defined heteroscedastic error enters the demand system. This heteroscedasticity can be handled by a GMM technique. Using a large Canadian cross-sectional household data set and the Quadratic Almost Ideal Demand System, homoscedasticity is rejected; however, when heteroscedasticity is allowed for, there are no longer inconsistencies between the theoretical and empirical evidence, particularly with respect to the collective decision-making properties of homogeneity, SR1 symmetry, and distribution factor proportionality and linearity.

Suggested Citation

  • Luo, Guo Ying, 2002. "Collective Decision-Making and Heterogeneity in Tastes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 213-226, April.
  • Handle: RePEc:bes:jnlbes:v:20:y:2002:i:2:p:213-26
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    1. Ryu, Hang K. & Slottje, Daniel J., 1996. "Two flexible functional form approaches for approximating the Lorenz curve," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 251-274.
    2. Sarabia, J. -M. & Castillo, Enrique & Slottje, Daniel J., 1999. "An ordered family of Lorenz curves," Journal of Econometrics, Elsevier, vol. 91(1), pages 43-60, July.
    3. McDonald, James B, 1984. "Some Generalized Functions for the Size Distribution of Income," Econometrica, Econometric Society, vol. 52(3), pages 647-663, May.
    4. Shorrocks, Anthony F, 1983. "Ranking Income Distributions," Economica, London School of Economics and Political Science, vol. 50(197), pages 3-17, February.
    5. Kakwani, N C & Podder, N, 1973. "On the Estimation of Lorenz Curves from Grouped Observations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 278-292, June.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", pages 125-132.
    7. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 133-152.
    8. Rasche, R H, et al, 1980. "Functional Forms for Estimating the Lorenz Curve: Comment," Econometrica, Econometric Society, vol. 48(4), pages 1061-1062, May.
    9. Datt, Gaurav, 1998. "Computational tools for poverty measurement and analysis," FCND discussion papers 50, International Food Policy Research Institute (IFPRI).
    10. Basmann, R. L. & Hayes, K. J. & Slottje, D. J. & Johnson, J. D., 1990. "A general functional form for approximating the Lorenz curve," Journal of Econometrics, Elsevier, vol. 43(1-2), pages 77-90.
    11. Kakwani, Nanak C & Podder, N, 1976. "Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations," Econometrica, Econometric Society, vol. 44(1), pages 137-148, January.
    12. Chotikapanich, Duangkamon, 1993. "A comparison of alternative functional forms for the Lorenz curve," Economics Letters, Elsevier, vol. 41(2), pages 129-138.
    13. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
    14. Woodland, A. D., 1979. "Stochastic specification and the estimation of share equations," Journal of Econometrics, Elsevier, vol. 10(3), pages 361-383, August.
    15. Bishop, John A & Chakraborti, S & Thistle, Paul D, 1989. "Asymptotically Distribution-Free Statistical Inference for Generalized Lorenz Curves," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 725-727, November.
    16. Charles M. Beach & Russell Davidson, 1983. "Distribution-Free Statistical Inference with Lorenz Curves and Income Shares," Review of Economic Studies, Oxford University Press, vol. 50(4), pages 723-735.
    17. Kakwani, Nanak, 1980. "On a Class of Poverty Measures," Econometrica, Econometric Society, vol. 48(2), pages 437-446, March.
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    Cited by:

    1. Waddell, Glen R. & Lee, Logan M., 2014. "The Timing of Preference and Prejudice in Sequential Hiring Games," IZA Discussion Papers 8445, Institute for the Study of Labor (IZA).
    2. Denton, Frank T. & Mountain, Dean C., 2011. "Exploring the effects of aggregation error in the estimation of consumer demand elasticities," Economic Modelling, Elsevier, vol. 28(4), pages 1747-1755, July.
    3. Frank T. Denton & Dean C. Mountain, 2007. "Exploring the Effects of Aggregation Error in the Estimation of Consumer Demand Elasticities," Social and Economic Dimensions of an Aging Population Research Papers 226, McMaster University.
    4. Chiappori, Pierre-André & Donni, Olivier, 2009. "Non-unitary Models of Household Behavior: A Survey of the Literature," IZA Discussion Papers 4603, Institute for the Study of Labor (IZA).

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