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Indirect Inference for Dynamic Panel Models

  • Christian Gouriéroux

    (SMU)

  • Peter C. B. Phillips
  • Jun Yu

It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with .xed eects is inconsistent under .xed time series sample size (T) and large cross section sample size (N) asymptotics. The estimation bias is particularly relevant in practical applications when T is small and the autoregressive parameter is close to unity. The present paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference (Gouriroux et al., 1993), shows unbiasedness and analyzes efficiency. The method is implemented in a simple linear dynamic panel model, but has wider applicability and can, for instance, be easily ex-tended to more complicated frameworks such as nonlinear models. Monte Carlo studies show that the proposed procedure achieves substantial bias reductions with only mild increases in variance, thereby substantially reducing root mean square errors. The method is compared with certain consistent estimators and bias-corrected ML estimators previously proposed in the literature and is shown to have superior .nite sample properties to GMM and the bias-corrected ML of Hahn and Kuersteiner (2002). Finite sample performance is compared with that of a recent estimator proposed by Han and Phillips (2005).

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File URL: http://www.eaber.org/node/22421
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Paper provided by East Asian Bureau of Economic Research in its series Development Economics Working Papers with number 22421.

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Date of creation: Jan 2006
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Handle: RePEc:eab:develo:22421
Contact details of provider: Postal: JG Crawford Building #13, Asia Pacific School of Economics and Government, Australian National University, ACT 0200
Web page: http://www.eaber.org

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  1. Monfort, Alain, 1996. "A Reappraisal of Misspecified Econometric Models," Econometric Theory, Cambridge University Press, vol. 12(04), pages 597-619, October.
  2. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, 07.
  3. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S63-84, Suppl. De.
  4. Peter C.B. Phillips & Donggyu Sul, 2003. "Bias in Dynamic Panel Estimation with Fixed Effects, Incidental Trends and Cross Section Dependence," Cowles Foundation Discussion Papers 1438, Cowles Foundation for Research in Economics, Yale University, revised Jun 2004.
  5. Tauchen, George E. & Gallant, A. Ronald, 1995. "Which Moments to Match," Working Papers 95-20, Duke University, Department of Economics.
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  8. Bun M.J.G. & Carree M.A., 2002. "Bias-corrected estimation in dynamic panel data models," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  9. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.
  10. GARCIA, René & RENAULT, Eric & VEREDAS, David, 2006. "Estimation of stable distributions by indirect inference," CORE Discussion Papers 2006112, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  11. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
  12. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
  13. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
  14. Jinyong Hahn & Whitney Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers CWP17/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  16. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  17. Chirok Han & Peter C.B. Phillips, 2007. "GMM Estimation for Dynamic Panels with Fixed Effects and Strong Instruments at Unity," Cowles Foundation Discussion Papers 1599, Cowles Foundation for Research in Economics, Yale University.
  18. Peter C.B.Phillips & Jun Yu, . "Simulation-based Estimation of Contingent Claims Prices," Working Papers CoFie-05-2008, Sim Kee Boon Institute for Financial Economics.
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  27. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  28. Ziliak, James P, 1997. "Efficient Estimation with Panel Data When Instruments Are Predetermined: An Empirical Comparison of Moment-Condition Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 419-31, October.
  29. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
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