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Testing for unit roots in panel data using a GMM approach

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Abstract

For aggregated time series unit root tests are routinely applied to choose among trend and difference stationary models. Recent work demonstrates that such test can also be applied for testing panel data. However, it is well known that disaggregated data often exhibit a considerable amount of heterogeneity so that standard tests may perform poorly. To account for the heterogeneity in the data we allow for individual specific deterministics, that is, we let the time trends vary across the cross section units. It is shown that standard GMM estimators suggested for the dynamic panel data model may fail to give a valid test procedure. To overcome this difficulty, a modified GMM estimator is suggested. In a Monte Carlo study the finite sample properties of the alternative tests are compared.

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References

  • Ahn S, Schmidt P (1995) Efficient estimation of models for dynamic panel data. Journal of Econometrics 69: 5–27

    Article  MathSciNet  Google Scholar 

  • Anderson T W, Hsiao C (1992) Formulation and estimation of dynamic models using panel data. Journal of Econometrics 18: 47–82

    Article  MathSciNet  Google 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: 277–297

    Article  MATH  Google Scholar 

  • Arellano M, Bover O (1995) Annother look at the instrumental-variable estimation of error-components models. Journal of Econometrics 68 29–51

    Article  MATH  Google Scholar 

  • Breitung J, Meyer W (1994) Testing for unit roots in panel data: are wages on different bargaining levels cointegrated? Applied Economics 26: 353–361

    Article  Google Scholar 

  • Fuller W A (1976) Introduction to Statistical Time Series John Wiley, New York

    MATH  Google Scholar 

  • Hansen L P (1982) Large sample properties of generalized method of moment estimators. Econometrics 50: 1029–1054

    Article  MATH  Google Scholar 

  • Harris R, Tzavalis E (1996) Inference for unit roots in dynamic panels. Working Paper, University of Exeter

  • Im K S, Peseran, M H, Shin Y (1995) Testing for unit roots in heterogenous panels Working Paper. Department of Applied Economics, University of Cambridge

  • Lee K H, Peseran M H, Smith R (1995) Growth and convergence: A multi-country empirical analysis of the Solow growth model. Working Paper No 9531, Department of Applied Economics, University of Cambridge

  • Levin A, Lin C F (1994) Unit root tests in panel data: asymptotic and finite-sample properties. Working Paper, University of California, San Diego

    Google Scholar 

  • Newey W K, West K D (1987) Hypothesis testing with efficient method of moments estimation. International Economic Review 28: 777–787

    Article  MATH  MathSciNet  Google Scholar 

  • Quah D (1992) International patterns of growth: I Persistency in Cross-Country Disparities. Discussion Paper, London School of Economics

  • Quah D (1994) Exploiting cross-section variation for unit root inference in dynamic data. Economics Letters 44: 9–19

    Article  MATH  Google Scholar 

  • Zhang J (1994) Performing a unit root test in panel data—with an application to OECD convergence. Discussion Paper, Chinese University of Hong Kong

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Breitung, J. Testing for unit roots in panel data using a GMM approach. Statistical Papers 38, 253–269 (1997). https://doi.org/10.1007/BF02925268

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  • DOI: https://doi.org/10.1007/BF02925268

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