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The Weak Instrument Problem of the System GMM Estimator in Dynamic Panel Data Models

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  • Maurice J.G. Bun

    (University of Amsterdam)

  • Frank Windmeijer

    (University of Bristol)

Abstract

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error. However, we show in this paper that in the covariance stationary panel data AR(1) model the expected values of the concentration parameters in the differenced and levels equations for the cross section at time t are the same when the variances of the individual heterogeneity and idiosyncratic errors are the same. This indicates a weak instrument problem also for the equation in levels. We show that the 2SLS biases relative to that of the OLS biases are then similar for the equations in differences and levels, as are the size distortions of the Wald tests. These results are shown to extend to the panel data GMM estimators.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 09-086/4.

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Date of creation: 09 Oct 2009
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Handle: RePEc:dgr:uvatin:20090086

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Keywords: Dynamic Panel Data; System GMM; Weak Instruments;

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  1. 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.
  2. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
  3. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, 07.
  4. Rachel Griffith & Rupert Harrison & John Van Reenen, 2004. "How Special is the Special Relationship? Using the Impact of US R&D Spillovers on UK Firms as a Test of Technology Sourcing," CEP Discussion Papers dp0659, Centre for Economic Performance, LSE.
  5. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
  6. 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.
  7. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  8. Frank Kleibergen, 2005. "Testing Parameters in GMM Without Assuming that They Are Identified," Econometrica, Econometric Society, vol. 73(4), pages 1103-1123, 07.
  9. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
  10. Richard Blundell & Steve Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
  11. Thorsten Beck & Ross Levine & Norman Loayza, 1999. "Financial Intermediation and Growth: Causality and Causes," Working Papers Central Bank of Chile 56, Central Bank of Chile.
  12. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
  13. Stephen Bond & Frank Windmeijer, 2005. "Reliable Inference For Gmm Estimators? Finite Sample Properties Of Alternative Test Procedures In Linear Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 24(1), pages 1-37.
  14. 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.
  15. Whitney Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  16. Gabriel A. Picone & Frank Sloan & Justin G. Trogdon, 2004. "The effect of the tobacco settlement and smoking bans on alcohol consumption," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1063-1080.
  17. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  18. James Levinsohn & Amil Petrin, 2000. "Estimating Production Functions Using Inputs to Control for Unobservables," NBER Working Papers 7819, National Bureau of Economic Research, Inc.
  19. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
  20. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
  21. Peter C. B. Phillips & Chirok Han, 2004. "GMM with Many Moment Conditions," Econometric Society 2004 Far Eastern Meetings 525, Econometric Society.
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