On the effect of mean-nonstationarity in dynamic panel data models
In this paper, we investigate the effect of mean-nonstationarity on the first-difference generalized method of moments (FD-GMM) estimator in dynamic panel data models. We find that when data is mean-nonstationary and the variance of individual effects is significantly larger than that of disturbances, the FD-GMM estimator performs quite well. We demonstrate that this is because the correlation between the lagged dependent variable and instruments gets larger owing to the unremoved individual effects, i.e.,Â instruments become strong. This implies that, under mean-nonstationarity, the FD-GMM estimator does not always suffer from the weak instruments problem even when data is persistent.
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- R Blundell & Steven Bond, .
"Initial conditions and moment restrictions in dynamic panel data model,"
W14&104., Economics Group, Nuffield College, University of Oxford.
- Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
- Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
- Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
- Manuel Arellano, 2003.
"Modelling Optimal Instrumental Variables For Dynamic Panel Data Models,"
- Arellano, Manuel, 2016. "Modelling optimal instrumental variables for dynamic panel data models," Research in Economics, Elsevier, vol. 70(2), pages 238-261.
- Robert J. Barro, 2013.
"Inflation and Economic Growth,"
Annals of Economics and Finance,
Society for AEF, vol. 14(1), pages 121-144, May.
- Bun, Maurice J.G. & Kiviet, Jan F., 2006.
"The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models,"
Journal of Econometrics,
Elsevier, vol. 132(2), pages 409-444, June.
- Maurice J.G. Bun & Jan F. Kiviet, 2002. "The Effects of Dynamic Feedbacks on LS and MM Estimator Accuracy in Panel Data Models," Tinbergen Institute Discussion Papers 02-101/4, Tinbergen Institute, revised 19 Feb 2004.
- Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d07-245, Institute of Economic Research, Hitotsubashi University.
- M Arellano & O Bover, 1990.
"Another Look at the Instrumental Variable Estimation of Error-Components Models,"
CEP Discussion Papers
dp0007, Centre for Economic Performance, LSE.
- Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
- Frank Kleibergen, 2005. "Testing Parameters in GMM Without Assuming that They Are Identified," Econometrica, Econometric Society, vol. 73(4), pages 1103-1123, 07.
- Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
- Alvarez, J. & Arellano, M., 1998.
"The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators,"
9808, Centro de Estudios Monetarios Y Financieros-.
- Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, 07.
- Manuel Arellano & Stephen Bond, 1991.
"Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,"
Review of Economic Studies,
Oxford University Press, vol. 58(2), pages 277-297.
- Tom Doan, . "RATS program to replicate Arellano-Bond 1991 dynamic panel," Statistical Software Components RTZ00169, Boston College Department of Economics.
- Kazuhiko Hayakawa, 2007. "A Simple Efficient Instrumental Variable Estimator in Panel AR(p) Models," Hi-Stat Discussion Paper Series d07-213, Institute of Economic Research, Hitotsubashi University.
- Hause, John C, 1980. "The Fine Structure of Earnings and the On-the-Job Training Hypothesis," Econometrica, Econometric Society, vol. 48(4), pages 1013-29, May.
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