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On the Estimation of a Linear Time Trend Regression with a One-Way Error Component Model in the Presence of Serially Correlated Errors

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Abstract

In this paper we study the limiting distributions for ordinary least squares (OLS), fixed effects (FE), first difference (FD), and generalized least squares (GLS) estimators in a linear time trend regression with a one-way error component model in the presence of serially correlated errors. We show that when the error term is I(0), the FE is asymptotically equivalent to the GLS. However, when the error term is I(1) the GLS could be less efficient than the FD or FE estimators, and the FD is the most efficient estimator. However, when the intercept is included in the model and the error term is I(0), the OLS, FE, and GLS are asymptotically equivalent. Monte Carlo experiments are employed to compare the performance of these estimators in finite samples. The main findings are (1) the two-step GLS estimators perform well if the variance component, delta, is small and close to zero when rho

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  • Chihwa Kao & Jamie Emerson, 1999. "On the Estimation of a Linear Time Trend Regression with a One-Way Error Component Model in the Presence of Serially Correlated Errors," Center for Policy Research Working Papers 1, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:1
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    1. Suzanne McCoskey & Chihwa Kao, 1998. "A residual-based test of the null of cointegration in panel data," Econometric Reviews, Taylor & Francis Journals, vol. 17(1), pages 57-84.
    2. Kramer, Walter, 1982. "Note on Estimating Linear Trend When Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 50(4), pages 1065-1067, July.
    3. 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.
    4. Baltagi, Badi H., 1981. "Pooling : An experimental study of alternative testing and estimation procedures in a two-way error component model," Journal of Econometrics, Elsevier, vol. 17(1), pages 21-49, September.
    5. Maeshiro, Asatoshi, 1976. "Autoregressive Transformation, Trended Independent Variables and Autocorrelated Disturbance Terms," The Review of Economics and Statistics, MIT Press, vol. 58(4), pages 497-500, November.
    6. 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.
    7. Chipman, John S, 1979. "Efficiency of Least-Squares Estimation of Linear Trend when Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 47(1), pages 115-128, January.
    8. Baltagi, Badi H., 1989. "Applications of a necessary and sufficient condition for OLS to be BLUE," Statistics & Probability Letters, Elsevier, vol. 8(5), pages 457-461, October.
    9. Chihwa Kao & Min-Hsien Chiang, 1997. "On the Estimation and Inference of a Cointegrated Regression in Panel Data," Econometrics 9703001, University Library of Munich, Germany.
    10. Baltagi, Badi H. & Chang, Young-Jae & Li, Qi, 1992. "Monte Carlo evidence on panel data regressions with AR(1) disturbances and an arbitrary variance on the initial observations," Journal of Econometrics, Elsevier, vol. 52(3), pages 371-380, June.
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    12. 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.
    13. Robert Summers & Alan Heston, 1991. "The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950–1988," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 327-368.
    14. Park, Rolla Edward & Mitchell, Bridger M., 1980. "Estimating the autocorrelated error model with trended data," Journal of Econometrics, Elsevier, vol. 13(2), pages 185-201, June.
    15. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
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    Cited by:

    1. Galip Altinay, 2003. "Estimating growth rate in the presence of serially correlated errors," Applied Economics Letters, Taylor & Francis Journals, vol. 10(15), pages 967-970.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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