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Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects

Author

Listed:
  • Jinyong Hahn

    (UCLA)

  • Jerry Hausman
  • Guido Kuersteiner

    (Department of Economics, Boston University)

Abstract

This paper proposes a new instrumental variables estimator for a dynamic panel model with .xed e¤ects with good bias and mean squared error properties even when identi.cation of the model becomes weak near the unit circle. We adopt a weak instrument asymptotic approximation to study the behavior of various estimators near the unit circle. We show that an estimator based on long di¤erencing the model is much less biased than conventional implementations of the GMM estimator for the dynamic panel model. We also show that under the weak instrument approximation such conventional estimators are dominated in terms of mean squared error by an estimator with far less moment conditions. The long di¤erence estimator mimics the infeasible optimal procedure through its reliance on a small set of moment conditions.

Suggested Citation

  • Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    • Handle: RePEc:bos:wpaper:wp2005-024
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    References listed on IDEAS

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    4. Rodrigo Alfaro & Carlos García & Alejandro Jara & Helmut Franken, 2005. "The bank lending channel in Chile," BIS Papers chapters, in: Bank for International Settlements (ed.), Investigating the relationship between the financial and real economy, volume 22, pages 128-45, Bank for International Settlements.
    5. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    6. Phillips, Peter C.B. & Sul, Donggyu, 2007. "Bias in dynamic panel estimation with fixed effects, incidental trends and cross section dependence," Journal of Econometrics, Elsevier, vol. 137(1), pages 162-188, March.
    7. Philip Brock & Helmut Franken M., 2003. "Measuring the Determinants of Average and Marginal Bank Interest Rate Spreads in Chile, 1994-2001," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 6(3), pages 45-65, December.
    8. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    9. Daron Acemoglu & Suresh Naidu & Pascual Restrepo & James A. Robinson, 2019. "Democracy Does Cause Growth," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 47-100.
    10. Carlos Budnevich L. & Helmut Franken M., 2003. "Market Discipline in Depositors’ Behavior and the Role of Risk-Rating Agencies: The Case of Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 6(2), pages 45-70, August.
    11. Peter C.B.Phillips & Donggyu Sul, 2002. "Dynamic Panel Estimation and Homogeneity Testing Under Cross Section Dependence," Cowles Foundation Discussion Papers 1362, Cowles Foundation for Research in Economics, Yale University.
    12. Hyungsik Roger Moon & Peter C. B. Phillips, 2004. "GMM Estimation of Autoregressive Roots Near Unity with Panel Data," Econometrica, Econometric Society, vol. 72(2), pages 467-522, March.
    13. Chao, John & Swanson, Norman R., 2007. "Alternative approximations of the bias and MSE of the IV estimator under weak identification with an application to bias correction," Journal of Econometrics, Elsevier, vol. 137(2), pages 515-555, April.
    14. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    15. Kruiniger, Hugo, 2009. "Gmm Estimation And Inference In Dynamic Panel Data Models With Persistent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1348-1391, October.
    16. Rodrigo Alfaro & Helmut Franken & Carlos García & Alejandro Jara, 2003. "Bank Lending Channel and the Monetary Transmission Mechanism: the Case of Chile," Working Papers Central Bank of Chile 223, Central Bank of Chile.
    17. Hayakawa, Kazuhiko, 2007. "Small sample bias properties of the system GMM estimator in dynamic panel data models," Economics Letters, Elsevier, vol. 95(1), pages 32-38, April.

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    More about this item

    Keywords

    dynamic panel; bias correction; second order; unit root; weak instrument;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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