Indirect Inference for Dynamic Panel Models
Christian Gouriérouxy Peter C. B. Phillipsz Jun Yux , , First version: June 2005 This version: December 2005
Abstract It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with …xed e¤ects 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 (Gouriéroux et al., 1993), shows unbiasedness and analyzes e ciency. The method is implemented in a simple linear dynamic panel model, but has wider applicability and can, for instance, be easily extended 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).
Phillips gratefully acknowledges support from a Kelly Fellowship at the University of Auckland Business School and from the NSF under Grant No. SES 04-142254. Yu gratefully acknowledge …nancial support from the Wharton-SMU Research Center at Singapore Management University. y CREST-INSEE, 92245 Malako¤, France and Department of Economics, University of Toronto; email: gouriero@ensae.fr. z Cowles Foundation for Research in Economics, Yale University, University of Auckland and University of York; email: peter.phillips@yale.edu. x School of Economics and Social Science, Singapore Management University, 90 Stamford Road Singapore 178903; email: yujun@smu.edu.sg.

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