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Estimation and Inference in Panel Structure Models

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  • Sun, Yixiao X

Abstract

This paper proposes and implements a tractable approach to detect group structure in panel data. The mechanism works by means of a panel structure model, which assumes that individuals form a number of homogeneous groups in a heterogeneous population. Within each group, the (linear) regression coe¢ cients are the same, while they may be different across different groups. The econometrician is not presumed to know the group structure. Instead, a multinomial logistic regression is used to infer which individuals belong to which groups. The model is estimated via maximum likelihood. We prove the consistency and asymptotic normality of a global MLE under the mild assumption that the time dimension is larger than the number of regressors in the linear regression. We propose a likelihood ratio test to test the null of one group against the alternative of multiple groups. Simulation studies show that the MLE performs quite well and the likelihood ratio test has good size and power properties in finite samples.

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Bibliographic Info

Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number qt5tf1231k.

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Date of creation: 01 Oct 2005
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Handle: RePEc:cdl:ucsdec:qt5tf1231k

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Related research

Keywords: dynamic panel data model; group structure; logistic regression; nonregular test; parameter heterogeneity;

References

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  1. Hsiao,Cheng, 2003. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9780521522717, Fall.
  2. Stephen Zeldes, . "Consumption and Liquidity Constraints: An Empirical Investigation," Rodney L. White Center for Financial Research Working Papers 24-85, Wharton School Rodney L. White Center for Financial Research.
  3. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291, Octomber.
  4. Kevin Lee & M. Hashem Pesaran & Ron Smith, 1996. "Growth and Convergence in a Multi-Country Empirical Stochastic Solow Model," Working Papers 9637, Economic Research Forum, revised Dec 1996.
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  6. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
  7. Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
  8. Christophe Deissenberg, Gustav Feichtinger, Willi Semmler and Franz Wirl, 2001. "History Dependence and Global Dynamics in Models with Multiple Equilibria," Computing in Economics and Finance 2001 257, Society for Computational Economics.
  9. Donald W.K. Andrews, 2004. "Cross-section Regression with Common Shocks," Yale School of Management Working Papers ysm401, Yale School of Management.
  10. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
  11. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  12. Nazrul Islam, 1998. "Growth Empirics: A Panel Data Approach- A Reply," The Quarterly Journal of Economics, MIT Press, vol. 113(1), pages 325-329, February.
  13. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
  14. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
  15. Kevin Lee & M. Hashem Pesaran & Ron Smith, 1998. "Growth Empirics: A Panel Data Approach- A Comment," The Quarterly Journal of Economics, MIT Press, vol. 113(1), pages 319-323, February.
  16. Timothy G. Conley & Bill Dupor, 2003. "A Spatial Analysis of Sectoral Complementarity," Journal of Political Economy, University of Chicago Press, vol. 111(2), pages 311-352, April.
  17. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
  18. George A. Akerlof, 1997. "Social Distance and Social Decisions," Econometrica, Econometric Society, vol. 65(5), pages 1005-1028, September.
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Citations

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Cited by:
  1. Grodner, Andrew & Kniesner, Thomas J., 2007. "Labor Supply with Social Interactions: Econometric Estimates and Their Tax Policy Implications," IZA Discussion Papers 3034, Institute for the Study of Labor (IZA).
  2. Bai, Jushan & Ando, Tomohiro, 2013. "Panel data models with grouped factor structure under unknown group membership," MPRA Paper 52782, University Library of Munich, Germany.

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