Indirect Inference for Dynamic Panel Models ∗

It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed 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 efficiency. The method is implemented in linear dynamic panel models with and without an incidental trend, 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 finite 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 (2007). ∗We thank two anonymous referees for their constructive comments. We also thank seminar participants at Chinese University of Hong Kong, Singapore Management University, National University of Singapore, and the SETA meeting in Xiamen for helpful discussions. 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 acknowledges financial support from the Office of Research at Singapore Management University. Gouriéroux and Phillips gratefully acknowledge visiting support from the School of Economics and Social Sciences at Singapore Management University. †CREST-INSEE, 92245 Malakoff, France and Department of Economics, University of Toronto; email: [email protected]. ‡Cowles Foundation for Research in Economics, Yale University, University of Auckland and University of York; email: [email protected]. §School of Economics and Social Sciences, Singapore Management University, 90 Stamford Road Singapore 178903; email: [email protected].