On the Estimation of a Linear Time Trend Regression with a One- Way Error Component Model in the Presence of Serially Correlated Errors
AbstractIn this paper, we study the limiting distributions for the ordinary least squares (OLS), the fixed effects (FE), first difference (FD), and the 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 GLS. However, when the error term is I(1), the GLS could be less efficient than FD or FE estimators and 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. The limiting distribution of the GLS depends on the initial condition significantly when the error term is I(1) and an intercept is included in the regression. Monte Carlo experiments are employed to compare the performance of these estimators in finite samples. The main findings are: (1) the two-steps GLS estimators perform well if the variance component is small and close to zero when autocorrelation coefficient is less than one, (2) the FD estimator dominates the other estimators when autocorrelation coefficient equals to one for all values of variance component and (3) the FE estimator is recommended in practice since it performs pretty well for all values of the autocorrelation coefficient and variance component.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9805004.
Length: 34 pages
Date of creation: 02 Jul 1998
Date of revision:
Note: Type of Document - postscript; prepared on PC-TEX; to print on HP/PostScript; pages: 34 ; figures: none. none
Contact details of provider:
Web page: http://220.127.116.11
Panel Time Series;
Other versions of this item:
- 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.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-1998-10-02 (All new papers)
- NEP-ECM-1998-10-02 (Econometrics)
- NEP-ETS-1998-10-02 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Summers, Robert & Heston, Alan, 1991. "The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950-1988," The Quarterly Journal of Economics, MIT Press, vol. 106(2), pages 327-68, May.
- Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
- 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.
- Chipman, John S, 1979. "Efficiency of Least-Squares Estimation of Linear Trend when Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 47(1), pages 115-28, January.
- 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.
- Suzanne McCoskey & Chihwa Kao, 1998.
"A residual-based test of the null of cointegration in panel data,"
Taylor & Francis Journals, vol. 17(1), pages 57-84.
- Chihwa Kao & Suzanne McCoskey, 1997. "A Residual-Based Test Of The Null Of Cointegration In Panel Data," Econometrics 9711002, EconWPA.
- 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.
- 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.
- 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.
- 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.
- 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.
- Kramer, Walter, 1982. "Note on Estimating Linear Trend When Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 50(4), pages 1065-67, July.
- Beach, Charles M & MacKinnon, James G, 1978. "A Maximum Likelihood Procedure for Regression with Autocorrelated Errors," Econometrica, Econometric Society, vol. 46(1), pages 51-58, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.