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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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Suggested Citation

  • Badi Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 329-350, December.
    • Handle: RePEc:spr:alstar:v:95:y:2011:i:4:p:329-350
    DOI: 10.1007/s10182-011-0170-5
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    1. Badi Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 329-350, December.
    2. Wansbeek, Tom & Kapteyn, Arie, 1983. "A note on spectral decomposition and maximum likelihood estimation in models with balanced data," Statistics & Probability Letters, Elsevier, vol. 1(4), pages 213-215, June.
    3. 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;German Statistical Society, vol. 95(4), pages 435-452, December.
    4. Eugene Canjels & Mark W. Watson, 1997. "Estimating Deterministic Trends In The Presence Of Serially Correlated Errors," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 184-200, May.
    5. 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.
    6. Perron, Pierre & Yabu, Tomoyoshi, 2009. "Estimating deterministic trends with an integrated or stationary noise component," Journal of Econometrics, Elsevier, vol. 151(1), pages 56-69, July.
    7. 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.
    8. 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.
    9. 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.
    10. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
    11. 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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    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;German Statistical Society, vol. 95(4), pages 325-327, December.
    2. Badi Baltagi & Chihwa Kao & Sanggon Na, 2011. "Test of hypotheses in panel data models when the regressor and disturbances are possibly non-stationary," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 329-350, December.
    3. Badi H. Baltagi & Chihwa Kao & Long Liu, 2017. "Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 85-102, March.
    4. Badi H. Baltagi & Chihwa Kao & Long Liu, 2014. "Test of Hypotheses in a Time Trend Panel Data Model with Serially Correlated Error Component Disturbances," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 347-394, Emerald Group Publishing Limited.
    5. Raffaela Giordano & Marcello Pericoli & Pietro Tommasino, 2013. "Pure or Wake-up-Call Contagion? Another Look at the EMU Sovereign Debt Crisis," International Finance, Wiley Blackwell, vol. 16(2), pages 131-160, June.
    6. Hermann Singer, 2011. "Continuous-discrete state-space modeling of panel data with nonlinear filter algorithms," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 375-413, December.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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