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Estimating growth rate in the presence of serially correlated errors

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  • Galip Altinay

Abstract

The aim of this study is to address the difficulties frequently encountered in estimating average growth rates by a log-linear time trend in the presence of serially correlated errors. There are a few studies in the literature that provide some guidance on choosing the appropriate method depending on the degree of first order serial correlation. However, the higher order serial correlation case is generally ignored. This study proposes the Nelder-Mead simplex method as a general solution to estimating linear trend in the presence of serial correlation of any order. The proposed method and the conventional methods are applied to the real GDP per capita series of 27 OECD countries. Twelve series seem to be better modelled by a log-linear trend with AR(2) residuals, and five of them yield remarkably different growth rates.

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  • 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.
    • Handle: RePEc:taf:apeclt:v:10:y:2003:i:15:p:967-970
    DOI: 10.1080/1350485032000165485
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    References listed on IDEAS

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    1. 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.
    2. Russell R. Barton & John S. Ivey, Jr., 1996. "Nelder-Mead Simplex Modifications for Simulation Optimization," Management Science, INFORMS, vol. 42(7), pages 954-973, July.
    3. John Baffes & Jean-Charles Le Vallee, 2003. "Unit roots versus trend stationarity in growth rate estimation," Applied Economics Letters, Taylor & Francis Journals, vol. 10(1), pages 9-14.
    4. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
    5. 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.
    6. Chihwa Kao & Jamie Emerson, 1998. "On the Estimation of a Linear Time Trend Regression with a One- Way Error Component Model in the Presence of Serially Correlated Errors," Econometrics 9805004, University Library of Munich, Germany.
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    Cited by:

    1. Monojit Chatterji & Homagni Choudhury, 2010. "Growth Rate Estimation in the presence of Unit Roots," Dundee Discussion Papers in Economics 245, Economic Studies, University of Dundee.
    2. Vítor João Pereira Domingues Martinho, 2021. "Impact of Covid‐19 on the convergence of GDP per capita in OECD countries," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(S1), pages 55-72, November.

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