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Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary

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  • Badi Baltagi

    ()

  • Chihwa Kao

    ()

  • Sanggon Na

    ()

Abstract

This paper considers the problem of hypotheses testing in a simple panel data regression model with random individual effects and serially correlated disturbances. Following Baltagi, Kao and Liu (2008), we allow for the possibility of non-stationarity in the regressor and/or the disturbance term. While Baltagi et al. (2008) focus on the asymptotic properties and distributions of the standard panel data estimators, this paper focuses on test of hypotheses in this setting. One important finding is that unlike the time series case, one does not necessarily need to rely on the “super-efficient” type AR estimator by Perron and Yabu (2009) to make inference in panel data. In fact, we show that the simple t-ratio always converges to the standard normal distribution regardless of whether the disturbances and/or the regressor are stationary.

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File URL: http://hdl.handle.net/10.1007/s10182-011-0170-5
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Bibliographic Info

Article provided by Springer in its journal AStA Advances in Statistical Analysis.

Volume (Year): 95 (2011)
Issue (Month): 4 (December)
Pages: 329-350

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Handle: RePEc:spr:alstar:v:95:y:2011:i:4:p:329-350

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References

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  1. Pierre Perron & Tomoyoshi Yabu, . "Estimating Deterministic Trends with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2006-012, Boston University - Department of Economics, revised Feb 2006.
  2. Peter C.B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Cowles Foundation Discussion Papers 1222, Cowles Foundation for Research in Economics, Yale University.
  3. Badi H. Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test Of Hypotheses In Panel Data Models When The Regressor And Disturbances Are Possibly Nonstationary," Center for Policy Research Working Papers 128, Center for Policy Research, Maxwell School, Syracuse University.
  4. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 435-452, December.
  5. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
  6. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
  7. Badi H. Baltagi & Chihwa Kao & Long Liu, 2008. "Asymptotic properties of estimators for the linear panel regression model with random individual effects and serially correlated errors: the case of stationary and non-stationary regressors and residu," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 554-572, November.
  8. Hsiao,Cheng, 2003. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9780521818551, October.
  9. 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.
  10. Baltagi, Badi H. & Li, Qi, 1991. "A transformation that will circumvent the problem of autocorrelation in an error-component model," Journal of Econometrics, Elsevier, vol. 48(3), pages 385-393, June.
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Cited by:
  1. Harry Haupt & Cheng Hsiao, 2011. "Introduction to the special issue: interdisciplinary aspects of panel data analysis," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 325-327, December.
  2. Badi H. Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test Of Hypotheses In Panel Data Models When The Regressor And Disturbances Are Possibly Nonstationary," Center for Policy Research Working Papers 128, Center for Policy Research, Maxwell School, Syracuse University.
  3. Hermann Singer, 2011. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 375-413, December.

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