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GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data

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  • Hugo Kruiniger

    (Queen Mary, University of London)

Abstract

In this paper we consider 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 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 LM type panel unit root tests.

Suggested Citation

  • Hugo Kruiniger, 2006. "GMM Estimation and Inference in Dynamic Panel Data Models with Persistent Data," Working Papers 560, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:560
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    1. Moon, Hyungsik R. & Phillips, Peter C.B., 2000. "Estimation Of Autoregressive Roots Near Unity Using Panel Data," Econometric Theory, Cambridge University Press, vol. 16(6), pages 927-997, December.
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    4. 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.
    5. Edith Madsen, 2003. "Using GMM when testing for a unit root in panels where the time-series dimension is fixed," CAM Working Papers 2003-11, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    6. 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.
    7. Stephen Bond & Frank Windmeijer, 2002. "Finite sample inference for GMM estimators in linear panel data models," CeMMAP working papers CWP04/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    9. Kruiniger, Hugo, 2008. "Maximum likelihood estimation and inference methods for the covariance stationary panel AR(1)/unit root model," Journal of Econometrics, Elsevier, vol. 144(2), pages 447-464, June.
    10. Hugo Kruiniger, 2000. "GMM Estimation of Dynamic Panel Data Models with Persistent Data," Working Papers 428, Queen Mary University of London, School of Economics and Finance.
    11. Hugo Kruiniger, 2002. "On the estimation of panel regression models with fixed effects," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-2, International Conferences on Panel Data.
    12. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
    13. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    14. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    15. Hahn, Jinyong & Hausman, Jerry, 2002. "Notes on bias in estimators for simultaneous equation models," Economics Letters, Elsevier, vol. 75(2), pages 237-241, April.
    16. Stephen Bond & Céline Nauges & Frank Windmeijer, 2005. "Unit roots: identification and testing in micro panels," CeMMAP working papers CWP07/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. 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.
    18. Ahn, Seung C. & Schmidt, Peter, 1997. "Efficient estimation of dynamic panel data models: Alternative assumptions and simplified estimation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 309-321.
    19. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Cited by:

    1. Peter C.B. Phillips, 2014. "Dynamic Panel GMM with Near Unity," Cowles Foundation Discussion Papers 1962, Cowles Foundation for Research in Economics, Yale University.
    2. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    3. Joakim Westerlund & Jörg Breitung, 2013. "Lessons from a Decade of IPS and LLC," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 547-591, August.
    4. Robertson, Donald & Sarafidis, Vasilis & Westerlund, Joakim, 2014. "GMM Unit Root Inference in Generally Trending and Cross-Correlated Dynamic Panels," MPRA Paper 53419, University Library of Munich, Germany.
    5. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    6. Sarafidis, Vasilis, 2016. "Neighbourhood GMM estimation of dynamic panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 526-544.
    7. Kruiniger, Hugo, 2013. "Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions," Journal of Econometrics, Elsevier, vol. 173(2), pages 175-188.
    8. In Choi, 2014. "Unit root tests for dependent and heterogeneous micropanels," Working Papers 1404, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    9. Kruiniger, Hugo, 2018. "A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions," MPRA Paper 110375, University Library of Munich, Germany, revised 15 Aug 2021.
    10. Ferdi Celikay, 2020. "Dimensions of tax burden: a review on OECD countries," Journal of Economics, Finance and Administrative Science, Emerald Group Publishing Limited, vol. 25(49), pages 27-43, March.
    11. Hayakawa, Kazuhiko & Nagata, Shuichi, 2016. "On the behaviour of the GMM estimator in persistent dynamic panel data models with unrestricted initial conditions," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 265-303.
    12. 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.
    13. Maurice J.G. Bun & Frank Kleibergen, 2013. "Identification and inference in moments based analysis of linear dynamic panel data models," UvA-Econometrics Working Papers 13-07, Universiteit van Amsterdam, Dept. of Econometrics.
    14. Ioana Octavia Popescu, 2023. "Fallacy of floating? Reconsidering the ability of flexible exchange rates to offset terms-of-trade volatility in developing countries," CSAE Working Paper Series 2023-01, Centre for the Study of African Economies, University of Oxford.
    15. Daniel Avdic & Martin Karlsson, 2017. "Growth in Earnings and Health: Nothing is as Practical as a Good Theory," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 777-787, December.
    16. Natalya Ketenci, 2015. "Capital mobility in the panel GMM framework: Evidence from EU members," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 12(1), pages 3-19, July.
    17. Bun, Maurice J.G. & Kleibergen, Frank, 2022. "Identification Robust Inference For Moments-Based Analysis Of Linear Dynamic Panel Data Models," Econometric Theory, Cambridge University Press, vol. 38(4), pages 689-751, August.
    18. Tue Gorgens & Chirok Han & Sen Xue, 2016. "Asymptotic distributions of the quadratic GMM estimator in linear dynamic panel data models," ANU Working Papers in Economics and Econometrics 2016-635, Australian National University, College of Business and Economics, School of Economics.
    19. Peter C. B. Phillips, 2020. "Dynamic Panel Modeling of Climate Change," Econometrics, MDPI, vol. 8(3), pages 1-28, July.

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    More about this item

    Keywords

    Dynamic panel data; GMM; Weak instruments; Weak identification; Local asymptotics; Multi-index asymptotics; Diagonal path asymptotics; LM test; Panel unit root test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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

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