IDEAS home Printed from https://ideas.repec.org/p/max/cprwps/1.html
   My bibliography  Save this paper

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

Author

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

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://surface.syr.edu/cpr/150/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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., 1989. "Applications of a necessary and sufficient condition for OLS to be BLUE," Statistics & Probability Letters, Elsevier, vol. 8(5), pages 457-461, October.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Kramer, Walter, 1982. "Note on Estimating Linear Trend When Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 50(4), pages 1065-1067, July.
    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.
    11. 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.
    12. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Badi H. Baltagi & Chihwa Kao & Long Liu, 2007. "Asymptotic Properties of Estimators for the Linear Panel Regression Model with Individual Effects and Serially Correlated Errors: The Case of Stationary and Non-Stationary Regressors and Residuals," Center for Policy Research Working Papers 93, Center for Policy Research, Maxwell School, Syracuse University.
    2. Fried, Roland & Gather, Ursula, 2004. "Robust Trend Estimation for AR(1) Disturbances," Technical Reports 2004,64, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Phillips, Robert F., 2004. "Estimation of a generalized random-effects model: some ECME algorithms and Monte Carlo evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 28(9), pages 1801-1824, July.
    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. Roland Jeske & Seuck Song, 2003. "Relative efficiency of OLSE and COTE for seasonal autoregressive disturbances," Statistical Papers, Springer, vol. 44(3), pages 421-432, July.
    6. repec:ebl:ecbull:v:3:y:2006:i:14:p:1-12 is not listed on IDEAS
    7. 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.
    8. Suzanne McCoskey & Chihwa Kao, 1997. "A Monte Carlo Comparison of Tests for Cointegration in Panel Data," Econometrics 9712002, University Library of Munich, Germany.
    9. Yum K. Kwan, 2006. "The Direct Substitution Between Government and Private Consumption in East Asia," NBER Working Papers 12431, National Bureau of Economic Research, Inc.
    10. Muhammad Omer & Jakob de Haan & Bert Scholtens, 2014. "Testing uncovered interest rate parity using LIBOR," Applied Economics, Taylor & Francis Journals, vol. 46(30), pages 3708-3723, October.
    11. Robert J. Sonora & Josip Tica, 2014. "Harrod, Balassa, and Samuelson (re)visit Eastern Europe," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-17, December.
    12. Wang Shin-Huei & Hafner Christian, 2011. "Estimating Autocorrelations in the Presence of Deterministic Trends," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-25, April.
    13. Yongcheol Shin & Andy Snell, 2006. "Mean group tests for stationarity in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 9(1), pages 123-158, March.
    14. Xiao, Zhijie, 2004. "Estimating average economic growth in time series data with persistency," Journal of Macroeconomics, Elsevier, vol. 26(4), pages 699-724, December.
    15. Ho, Tsung-wu, 2001. "The government spending and private consumption: a panel cointegration analysis," International Review of Economics & Finance, Elsevier, vol. 10(1), pages 95-108.
    16. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
    17. Gabriel Bruneau & Kevin Moran, 2017. "Exchange rate fluctuations and labour market adjustments in Canadian manufacturing industries," Canadian Journal of Economics, Canadian Economics Association, vol. 50(1), pages 72-93, February.
    18. Florian Pelgrin & Sebastian Schich, 2002. "Panel Cointegration Analysis of the Finance-Investment Link in OECD Countries," Documents de Travail de l'OFCE 2002-02, Observatoire Francais des Conjonctures Economiques (OFCE).
    19. 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.
    20. Baltagi, Badi H. & Liu, Long, 2013. "Estimation and prediction in the random effects model with AR(p) remainder disturbances," International Journal of Forecasting, Elsevier, vol. 29(1), pages 100-107.
    21. Maeso-Fernandez, Francisco & Osbat, Chiara & Schnatz, Bernd, 2006. "Towards the estimation of equilibrium exchange rates for transition economies: Methodological issues and a panel cointegration perspective," Journal of Comparative Economics, Elsevier, vol. 34(3), pages 499-517, September.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:max:cprwps:1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Margaret Austin or Zia Jackson or Katrina Fiacchi (email available below). General contact details of provider: https://edirc.repec.org/data/cpsyrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.