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NONPARAMETRIC ESTIMATION OF DYNAMIC PANEL MODELS WITH FIXED EFFECTS

Published online by Cambridge University Press:  27 May 2014

Yoonseok Lee
Yoonseok Lee*
Affiliation:
Syracuse University
*
*Address correspondence to Yoonseok Lee, Center for Policy Research, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244-1020, USA; e-mail: ylee41@maxwell.syr.edu.
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Abstract

This paper considers nonparametric estimation of autoregressive panel data models with fixed effects. A within-group type series estimator is developed and its convergence rate and asymptotic normality are derived. It is found that the series estimator is asymptotically biased and the bias could reduce the mean-square convergence rate compared with the cross-section cases. A bias corrected nonparametric estimator is developed.

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ARTICLES
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Econometric Theory , Volume 30 , Issue 6 , December 2014 , pp. 1315 - 1347
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Copyright © Cambridge University Press 2014 

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References

REFERENCES

Ai, C. & Chen, X. (2003) Efficient estimation of models with conditional moment restrictions containing unknown functions. Econometrica 71, 1795–1843.CrossRefGoogle Scholar
Alvarez, J. & Arellano, M. (2003) The time series and cross-section asymptotics of dynamic panel data estimators. Econometrica 71, 1121–1159.CrossRefGoogle Scholar
Andrews, D.W.K. (1991a) Asymptotic normality of series estimators for nonparametric and semiparametric regression models. Econometrica 59, 307–345.CrossRefGoogle Scholar
Andrews, D.W.K. (1991b) Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 59, 817–858.CrossRefGoogle Scholar
Baltagi, B.H. & Li, D. (2002) Series estimation of partially linear panel data models with fixed effects. Annals of Economics and Finance 3, 103–116.Google Scholar
Bhattacharya, R. & Lee, C. (1995) On geometric ergodicity of nonlinear autoregressive models. Statistics & Probability Letters 22, 311–315.CrossRefGoogle Scholar
Chan, K.S. & Tong, H. (1986) On estimating thresholds in autoregressive models. Journal of Time Series Analysis 7, 179–190.CrossRefGoogle Scholar
Chen, X. (2007) Large sample sieve estimation of semi-nonparametric models. In Heckman, J.J. & Leamer, E.E. (eds.), Handbook of Econometrics, vol. 6B, pp. 2549–2632. Elsevier.Google Scholar
Chen, X., Hong, H., & Tamer, E. (2005) Measurement error models with auxiliary data. Review of Economic Studies 72, 343–366.CrossRefGoogle Scholar
Chen, X. & Shen, X. (1998) Sieve extremum estimators for weakly dependent data. Econometrica 66, 289–314.CrossRefGoogle Scholar
Chen, R. & Tsay, R.S. (1993) Nonlinear additive ARX models. Journal of American Statistical Association 88, 955–967.CrossRefGoogle Scholar
Davidson, J. (1994) Stochastic Limit Theory. Oxford University Press.CrossRefGoogle Scholar
Davydov, Y. (1973) Mixing conditions for Markov chains. Theory of Probability and Its Applications 18, 312–328.CrossRefGoogle Scholar
Doukhan, P. (1994) Mixing: Properties and Examples. Springer-Verlag.CrossRefGoogle Scholar
Fan, J. & Yao, Q. (2003) Nonlinear Time Series: Nonparametric and Parametric Methods. Springer-Verlag.CrossRefGoogle Scholar
Gallant, A.R. & Nychka, D.W. (1987) Semi-nonparametric maximum likelihood estimation. Econometrica 55, 363–390.CrossRefGoogle Scholar
Hahn, J. & Kuersteiner, G. (2002) Asymptotically unbiased inference for a dynamic panel model with fixed effects. Econometrica 70, 1639–1657.CrossRefGoogle Scholar
Hahn, J. & Kuersteiner, G. (2011) Bias reduction for dynamic nonlinear panel models with fixed effects. Econometric Theory 27, 1152–1191.CrossRefGoogle Scholar
Hahn, J. & Newey, W. (2004) Jackknife and analytical bias reduction for nonlinear panel models. Econometrica 72, 1295–1319.CrossRefGoogle Scholar
Hall, P. & Heyde, C.C. (1980) Martingale Limit Theory and Its Application. Academic Press.Google Scholar
Henderson, D.J., Carroll, R.J., & Li, Q. (2008) Nonparametric estimation and testing of fixed effects panel data models. Journal of Econometrics 144, 257–275.CrossRefGoogle ScholarPubMed
Henderson, D.J. & Ullah, A. (2005) A nonparametric random effects estimator. Economics Letters 88, 403–407.CrossRefGoogle Scholar
Lee, Y. (2006) General approaches to dynamic panel modelling and bias correction. Ph.D. dissertation, Yale University.Google Scholar
Lee, Y. (2012) Bias in dynamic panel models under time series misspecification. Journal of Econometrics 169, 54–60.CrossRefGoogle Scholar
Lee, Y. & Mukherjee, D. (2012) New Nonparametric Estimation of the Marginal Effects in Fixed-Effects Panel Models: An Application on the Environmental Kuznets Curve. Working paper.Google Scholar
Lee, Y. & Phillips, P.C.B. (2014) Model Selection in the Presence of Incidental Parameters. Journal of Econometrics, forthcoming.Google Scholar
Lewis, R. & Reinsel, G.C. (1985) Prediction of multivariate time-series by autoregressive model-fitting. Journal of Multivariate Analysis 16, 393–411.CrossRefGoogle Scholar
Li, Q. & Kniesner, T.J. (2002) Nonlinearity in dynamic adjustment: Semiparametric estimation of panel labor supply. Empirical Economics 27, 131–148.Google Scholar
Li, Q. & Stengos, T. (1996) Semiparametric estimation of partially linear panel data models. Journal of Econometrics 71, 389–397.CrossRefGoogle Scholar
Liebscher, E. (2005) Towards a unified approach for proving geometric ergodicity and mixing properties of nonlinear autoregressive processes. Journal of Time Series Analysis 26, 669–689.CrossRefGoogle Scholar
Meyn, S.P. & Tweedie, R.L. (1993) Markov Chains and Stochastic Stability. Springer-Verlag.CrossRefGoogle Scholar
Newey, W.K. (1997) Convergence rates and asymptotic normality for series estimators. Journal of Econometrics 79, 147–168.CrossRefGoogle Scholar
Newey, W.K. & Powell, J.L. (2003) Instrumental variable estimation of nonparametric models. Econometrica 71, 1565–1578.CrossRefGoogle Scholar
Newey, W.K. & West, K.D. (1987) A simple positive semi-definite heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55, 703–708.CrossRefGoogle Scholar
Nickell, S. (1981) Biases in dynamic models with fixed effects. Econometrica 49, 1417–1425.CrossRefGoogle Scholar
Nummelin, E. (1984) General Irreducible Markov Chains and Nonnegative Operators. Cambridge University Press.CrossRefGoogle Scholar
Park, B., Sickles, R.C., & Simar, L. (2007) Semiparametric efficient estimation of dynamic panel data models. Journal of Econometrics 136, 281–301.CrossRefGoogle Scholar
Phillips, P.C.B. & Moon, H.R. (1999) Linear regression limit theory for nonstationary panel data. Econometrica 67, 1057–1111.CrossRefGoogle Scholar
Phillips, P.C.B. & Sul, D. (2003) Dynamic panel estimation and homogeneity testing under cross section dependence. Econometrics Journal 6, 217–259.CrossRefGoogle Scholar
Porter, J.R. (1996) Essays in econometrics. Ph.D. dissertation, MIT.Google Scholar
Prakasa Rao, B.L.S. (2009) Conditional independence, conditional mixing and conditional association. Annals of the Institute of Statistical Mathematics 61, 441–460.CrossRefGoogle Scholar
Stone, C.J. (1982) Optimal global rates of convergence for nonparametric regression. Annals of Statistics 10, 1040–1053.CrossRefGoogle Scholar
Su, L & Jin, S. (2012) Sieve estimation of panel data models with cross section dependence. Journal of Econometrics 169, 34–47.CrossRefGoogle Scholar
Su, L. & Ullah, A. (2006) Profile likelihood estimation of partially linear panel data models with fixed effects. Economics Letters 92, 75–81.CrossRefGoogle Scholar
Tjøstheim, D. (1990) Non-linear time series and Markov chains. Advances in Applied Probability 22, 587–611.CrossRefGoogle Scholar
Tong, H. (1990) Non-linear Time Series: A Dynamic System Approach. Oxford University Press.CrossRefGoogle Scholar
Tweedie, R.L. (1983) Criteria for rates of convergence of Markov chains, with application to queueing theory. In Kingman, J.F.C. & Reuter, G.E.H. (eds.), Papers in Probability, Statistics and Analysis, pp. 260–276. Cambridge University Press.CrossRefGoogle Scholar
White, H. & Domowitz, I. (1984) Nonlinear regression with dependent observations. Econometrica 52, 143–161.CrossRefGoogle Scholar