A note on the relative efficiency of the Cochrane-Orcutt and OLS estimators when the autocorrelation process has a finite past
AbstractThis note shows that the ordinary least squares estimator of a first-order autoregressive model is always more efficient relative to the Cochrane-Orcutt estimator if the autocorrelation process has a finite past than if its past is infinite. This result cast doubt on the usual suggestion that it might be better to delete the initial observation rather than weight it if the autocorrelation process has a finite past.
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Bibliographic InfoPaper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 1984-002.
Date of creation: 1984
Date of revision:
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- Fomby, Thomas B. & Guilkey, David K., 1983. "An examination of two-step estimators for models with lagged dependent variables and autocorrelated errors," Journal of Econometrics, Elsevier, vol. 22(3), pages 291-300, August.
- 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.
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