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Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors under Cross-sectional Dependence

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  • Sarafidis, Vasilis
  • Yamagata, Takashi

Abstract

This paper develops an instrumental variable (IV) estimator for consistent estimation of dynamic panel data models with error cross-sectional dependence when both N and T, the cross-section and time series dimensions respectively, are large. Our approach asymptotically projects out the common factors from regressors using principal components analysis and then uses the defactored regressors as instruments to estimate the model in a standard way. Therefore, the proposed estimator is computationally very attractive. Furthermore, our procedure requires estimating only the common factors included in the regressors, leaving those that influence the dependent variable solely into the errors. Hence aside from computational simplicity the resulting approach allows parsimonious estimation of the model. The finite-sample performance of the IV estimator and the associated t-test is investigated using simulated data. The results show that the bias of the estimator is very small and the size of the t-test is correct even when (T,N) is as small as (10,50). The performance of an overidentifying restrictions test is also explored and the evidence suggests that it has good power when the key assumption is violated.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 25182.

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Date of creation: Feb 2010
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Handle: RePEc:pra:mprapa:25182

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Keywords: Method of moments; dynamic panel data; cross-sectional dependence;

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  1. Bover, Olympia, 1991. "Relaxing Intertemporal Separability: A Rational Habits Model of Labor Supply Estimated from Panel Data," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 85-100, January.
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  10. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
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  12. Robertson, Donald & Sarafidis, Vasilis & Symons, James, 2010. "IV Estimation of Panels with Factor Residuals," MPRA Paper 26166, University Library of Munich, Germany.
  13. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute for the Study of Labor (IZA).
  14. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  15. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
  16. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.
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  18. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
  19. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
  20. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
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Cited by:
  1. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
  2. Robertson, Donald & Sarafidis, Vasilis & Symons, James, 2010. "IV Estimation of Panels with Factor Residuals," MPRA Paper 26166, University Library of Munich, Germany.

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