Penalized empirical likelihood estimation of semiparametric models
We propose an empirical likelihood-based estimation method for conditional estimating equations containing unknown functions, which can be applied for various semiparametric models. The proposed method is based on the methods of conditional empirical likelihood and penalization. Thus, our estimator is called the penalized empirical likelihood (PEL) estimator. For the whole parameter including infinite-dimensional unknown functions, we derive the consistency and a convergence rate of the PEL estimator. Furthermore, for the finite-dimensional parametric component, we show the asymptotic normality and efficiency of the PEL estimator. We illustrate the theory by three examples. Simulation results show reasonable finite sample properties of our estimator.
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Volume (Year): 98 (2007)
Issue (Month): 10 (November)
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- Jian Zhang, 2003. "Sieve Empirical Likelihood and Extensions of the Generalized Least Squares," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 1-24.
- repec:cup:cbooks:9780521785167 is not listed on IDEAS
- Shi, Jian & Lau, Tai-Shing, 2000. "Empirical Likelihood for Partially Linear Models," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 132-148, January.
- Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November.
- Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2004.
"Empirical Likelihood-Based Inference in Conditional Moment Restriction Models,"
Econometric Society, vol. 72(6), pages 1667-1714, November.
- Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2001. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," CIRJE F-Series CIRJE-F-124, CIRJE, Faculty of Economics, University of Tokyo.
- repec:cup:cbooks:9780521780506 is not listed on IDEAS
- Newey, Whitney K, 1990.
"Efficient Instrumental Variables Estimation of Nonlinear Models,"
Econometric Society, vol. 58(4), pages 809-37, July.
- Newey, W.K., 1989. "Efficient Instrumental Variables Estimation Of Nonlinear Models," Papers 341, Princeton, Department of Economics - Econometric Research Program.
- Whitney K. Newey & Richard J. Smith, 2004.
"Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators,"
Econometric Society, vol. 72(1), pages 219-255, 01.
- Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yanyuan Ma & Jeng-Min Chiou & Naisyin Wang, 2006. "Efficient semiparametric estimator for heteroscedastic partially linear models," Biometrika, Biometrika Trust, vol. 93(1), pages 75-84, March.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Xihong Lin, 2004. "Equivalent kernels of smoothing splines in nonparametric regression for clustered/longitudinal data," Biometrika, Biometrika Trust, vol. 91(1), pages 177-193, March.
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