Youssef, Ahmed H. and El-Sheikh, Ahmed A. and Abonazel, Mohamed R. (2014): Improving the Efficiency of GMM Estimators for Dynamic Panel Models. Published in: Far East Journal of Theoretical Statistics , Vol. 47, No. 2 (May 2014)
Preview |
PDF
MPRA_paper_68675.pdf Download (754kB) | Preview |
Abstract
In dynamic panel models, the generalized method of moments (GMM) has been used in many applications since it gives efficient estimators. This efficiency is affected by the choice of the initial weighted matrix. It is common practice to use the inverse of the moment matrix of the instruments as an initial weighted matrix. However, an initial optimal weighted matrix is not known, especially in the system GMM estimation procedure. Therefore, we present the optimal weighted matrix for level GMM estimator, and suboptimal weighted matrices for system GMM estimator, and use these matrices to increase the efficiency of GMM estimator. By using the Kantorovich inequality (KI), we find that the potential efficiency gain becomes large when the variance of individual effects increases compared with the variance of the errors.
Item Type: | MPRA Paper |
---|---|
Original Title: | Improving the Efficiency of GMM Estimators for Dynamic Panel Models |
English Title: | Improving the Efficiency of GMM Estimators for Dynamic Panel Models |
Language: | English |
Keywords: | dynamic panel data, generalized method of moments, KI upper bound, optimal and suboptimal weighted matrices. |
Subjects: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis |
Item ID: | 68675 |
Depositing User: | Dr. Mohamed R. Abonazel |
Date Deposited: | 08 Jan 2016 14:23 |
Last Modified: | 26 Sep 2019 10:58 |
References: | Ahn, S.C., and Schmidt, P. (1995). Efficient Estimation of Models for Dynamic Panel Data, Journal of Econometrics, 68, 5-28. Alvarez, J., and Arellano, M. (2003). The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators, Econometrica, 71, 1121-1159. Arellano, M., and O. Bover, (1995). Another Look at the Instrumental Variable Estimation of Error-Components Models, Journal of Econometrics,68, 29-51. Arellano, M., and S. Bond, (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations, Review of Economic Studies,58, 277-98. Blundell, R., and S. Bond, (1998). Initial Conditions and Moment Restrictions in Dynamic Panel Data Models, Journal of Econometrics, 87,115-143. Hayakawa, K. (2007). Small Sample Bias Properties of the System GMM Estimator in Dynamic Panel Data Models, Economics Letters, 95,32-38. Jung, H., and H. Kwon, (2007).An Alternative System GMM Estimation in Dynamic Panel Models,Hi-Stat Discussion Paper No. 217, Hitotsubashi University. Kiviet, J.F. (2007). Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models. In The Refinement of Econometric Estimation and Test Procedures, ed. by G.D.A. Phillips and E. Tzavalis, Cambridge University Press, Cambridge, UK. S. Liu and H. Neudecker, Kantorovich inequalities and efficiency comparisons for several classes of estimators in linear models, Statist. Neerlandica 51 (1997), 345- 355. Newey, W., and R. Smith, (2004). Higher Order Properties of GMM and Generalized Empirical Likelihood Estimators, Econometrica, 72, 219-255. Windmeijer, F.,(2000). Efficiency Comparisons for a System GMM Estimator in DynamicPanel Data Models. In Innovations in Multivariate Statistical Analysis, ed. by R.D.H. Heijmans, D.S.G. Pollock and A. Satorra, A Festschrift for Heinz Neudecker. Advanced Studiesin Theoretical and Applied Econometrics, vol. 36, Dordrecht: Kluwer Academic Publishers (IFS working paper W98/1). |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/68675 |