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Estimating Trend Stationary Models of Homogeneously Generated Samples

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  • Falk, Barry

Abstract

Sims (1991) conjectured that the conditional maximum likelihood estimator of trend stationary models of macroeconomic time series will tend to place initial observations relatively far from the estimated trend line. This can be misleading if the entire sample has been generated by the same data generating process and there is nothing unusual about the initial observations. We use the extended Nelson Plosser data set to evaluate Sims's conjecture. We consider the weighted symmetric estimator developed by Park and Fuller (1993) as an alternative approach to this estimation problem.

Suggested Citation

  • Falk, Barry, 1995. "Estimating Trend Stationary Models of Homogeneously Generated Samples," ISU General Staff Papers 199507010700001269, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genstf:199507010700001269
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    1. DeJong, David N. & Whiteman, Charles H., 1991. "Reconsidering 'trends and random walks in macroeconomic time series'," Journal of Monetary Economics, Elsevier, vol. 28(2), pages 221-254, October.
    2. Pantula, Sastry G & Gonzalez-Farias, Graciela & Fuller, Wayne A, 1994. "A Comparison of Unit-Root Test Criteria," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 449-459, October.
    3. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    4. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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