Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T18:18:15.544Z Has data issue: false hasContentIssue false

GMM ESTIMATION AND INFERENCE IN DYNAMIC PANEL DATA MODELS WITH PERSISTENT DATA

Published online by Cambridge University Press:  01 October 2009

Hugo Kruiniger*
Affiliation:
Queen Mary, University of London
*
*Address correspondence to Hugo Kruiniger, Department of Economics, Queen Mary, University of London, Mile End Road, London E1 4NS, United Kingdom; e-mail: [email protected].

Abstract

In this paper we consider generalized method of moments–based (GMM-based) estimation and inference for the panel AR(1) model when the data are persistent and the time dimension of the panel is fixed. We find that the nature of the weak instruments problem of the Arellano–Bond (Arellano and Bond, 1991, Review of Economic Studies 58, 277–297) estimator depends on the distributional properties of the initial observations. Subsequently, we derive local asymptotic approximations to the finite-sample distributions of the Arellano–Bond estimator and the System estimator, respectively, under a variety of distributional assumptions about the initial observations and discuss the implications of the results we obtain for doing inference. We also propose two Lagrange multiplier–type (LM-type) panel unit root tests.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ahn, S.C. & Schmidt, P. (1995) Efficient estimation of models for dynamic panel data. Journal of Econometrics 68, 528.CrossRefGoogle Scholar
Ahn, S.C. & Schmidt, P. (1997) Efficient estimation of dynamic panel data models: Alternative assumptions and simplified estimation. Journal of Econometrics 76, 309321.CrossRefGoogle Scholar
Arellano, M. & Bond, S. (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58, 277297.CrossRefGoogle Scholar
Arellano, M. & Bover, O. (1995) Another look at the instrumental variable estimation of error- components models. Journal of Econometrics 68, 2951.CrossRefGoogle Scholar
Blundell, R.W. & Bond, S. (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87, 115143.CrossRefGoogle Scholar
Bond, S.R., Nauges, C., & Windmeijer, F. (2005) Unit Roots: Identification and Testing in Micro Panels. CEMMAP Working paper 07/05, Institute for Fiscal Studies, London.CrossRefGoogle Scholar
Breitung, J. & Meyer, W. (1994) Testing for unit roots using panel data: Are wages on different bargaining levels cointegrated? Applied Economics 26, 353361.CrossRefGoogle Scholar
Fieller, E.C. (1932) The distribution of an index in a normal bivariate population. Biometrika 24, 428440.CrossRefGoogle Scholar
Forchini, G. (2006) On the bimodality of the exact distribution of the TSLS estimator. Econometric Theory 22, 932946.CrossRefGoogle Scholar
Hahn, J., Hausman, J., & Kuersteiner, G. (2001) Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed Effects. Working paper, M.I.T.CrossRefGoogle Scholar
Han, C. & Phillips, P.C.B. (2006) GMM with many moment conditions. Econometrica 74, 147192.CrossRefGoogle Scholar
Han, C. & Phillips, P.C.B. (2007) GMM Estimation for Dynamic Panels with Fixed Effects and Strong Instruments at Unity. Cowles Foundation Discussion paper 1599, Yale University.Google Scholar
Harris, R.D.F. & Tzavalis, E. (1999) Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics 91, 201226.CrossRefGoogle Scholar
Hillier, G.H. (2006) Yet more on the exact properties of IV estimators. Econometric Theory 22, 913931.CrossRefGoogle Scholar
Hsiao, C., Pesaran, M.H., & Tahmiscioglu, A.K. (2002) Maximum likelihood estimation of fixed effects dynamic panel models covering short time periods. Journal of Econometrics 109, 107150.CrossRefGoogle Scholar
Kruiniger, H. (2003) On the Estimation of Panel Regression Models with Fixed Effects. Revised version of Working paper 450, Queen Mary, University of London.CrossRefGoogle Scholar
Kruiniger, H. (2008a) GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data. Revised version of Working paper 428, Queen Mary, University of London. Available at http://webspace.qmul.ac.uk/hkruiniger/.Google Scholar
Kruiniger, H. (2008b) Maximum likelihood estimation and inference methods for the covariance stationary panel AR(1)/unit root model. Journal of Econometrics 144, 447464.CrossRefGoogle Scholar
Madsen, E. (2003) Using GMM when Testing for a Unit Root in Panels Where the Time-Dimension is Fixed. CAM Working paper 2003-11, University of Copenhagen.Google Scholar
Marsaglia, G. (1965) Ratios of normal variables and ratios of sums of uniform variables. Journal of the American Statistical Association 60, 193204.CrossRefGoogle Scholar
Moon, H.R. & Phillips, P.C.B. (2000) Estimation of autoregressive roots near unity using panel data. Econometric Theory 16, 927997.CrossRefGoogle Scholar
Phillips, P.C.B. (2006) A remark on bimodality and weak instrumentation in structural equation estimation. Econometric Theory 22, 947960.CrossRefGoogle Scholar
Phillips, P.C.B. & Han, C. (2008) Gaussian inference in AR(1) time series with or without a unit root. Econometric Theory 24, 631650.CrossRefGoogle Scholar
Phillips, P.C.B. & Magdalinos, T. (2008) Unit Root and Cointegrating Limit Theory when Initialization is in the Infinite Past. Cowles Foundation Discussion paper 1655, Yale University.Google Scholar
Phillips, P.C.B. & Moon, H.R. (1999) Linear regression limit theory for nonstationary panel data. Econometrica 67, 10571111.CrossRefGoogle Scholar
Staiger, D. & Stock, J.H. (1997) Instrumental variables regression with weak instruments. Econometrica 65, 557586.CrossRefGoogle Scholar
Stock, J.H, Wright, J.H., & Yogo, M. (2002) A survey of weak instruments and weak identification in generalized method of moments. Journal of Business & Economic Statistics 20, 518529.CrossRefGoogle Scholar
Woglom, G. (2001) More results on the exact small sample properties of the instrumental variable estimator. Econometrica 69, 13811389.CrossRefGoogle Scholar