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Unit Roots and Identification in Autoregressive Panel Data Models: A Comparison of Alternative Tests

Author

Listed:
  • Stephen Bond

    (Institute for Fiscal Studies)

  • Céline Nauges

    (LEERNA-INRA Toulouse)

  • Frank Windmeijer

    (Institute for Fiscal Studies)

Abstract

We compare the finite sample behaviour of various unit root tests for micro panels where the number of individuals is typically large, but the number of time periods is often very small. As in this case some econometric estimators do not identify the parameters of interest when the processes are random walks, it is important to test for unit roots/identification. We find that a t-test based on OLS estimation results provides a simple robust test with high power for cases when the variance of the unobserved heterogeneity is relatively small. Its behaviour is similar to the underidentification test as proposed by Arellano, Hansen and Sentana (1999) for the GMM estimator on a first-differenced model.

Suggested Citation

  • Stephen Bond & Céline Nauges & Frank Windmeijer, 2002. "Unit Roots and Identification in Autoregressive Panel Data Models: A Comparison of Alternative Tests," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C5-4, International Conferences on Panel Data.
  • Handle: RePEc:cpd:pd2002:c5-4
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    References listed on IDEAS

    as
    1. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(4), pages 795-837, August.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    4. 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.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. Frank Windmeijer, 2000. "A finite sample correction for the variance of linear two-step GMM estimators," IFS Working Papers W00/19, Institute for Fiscal Studies.
    7. 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.
    8. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    9. 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.
    10. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
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    More about this item

    Keywords

    Generalised Method of Moments; Identification; Unit Root Tests;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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