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GMM Estimation of Lattice Models Using Panel Data: Application

  • Théophile Azomahou
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    We propose an empirical application of lattice models to actual household-level data based on the generalized method of moments. We take advantage of the two dimensional structure of panel data to construct a lattice specification. Then, a class of nonparametric, positive semidefinite covariance matrix estimators that allow for a general form of spatial dependence characterized by a metric of economic distance is introduced. This framework is applied to estimating spatial patterns in the residential demand for drinking water. Estimation results indicate that accounting for spatial dependence yields efficient estimate of the asymptotic variance matrix. Compared to non-spatial strategies, spatial dependence implies higher standard errors for all parameter estimates so as to strongly modify patterns of significance.

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    File URL: http://www.beta-umr7522.fr/productions/publications/2001/2001-09.pdf
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    Paper provided by Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg in its series Working Papers of BETA with number 2001-09.

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    Date of creation: 2001
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    Handle: RePEc:ulp:sbbeta:2001-09
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    1. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
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    5. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-65, July.
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    8. Hautsch, Nikolaus & Klotz, Stefan, 2003. "Estimating the neighborhood influence on decision makers: theory and an application on the analysis of innovation decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 52(1), pages 97-113, September.
    9. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
    10. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    11. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    12. White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-61, January.
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    15. DeSarbo, Wayne S. & Kim, Youngchan & Fong, Duncan, 1998. "A Bayesian multidimensional scaling procedure for the spatial analysis of revealed choice data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 79-108, November.
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