Estimating deterministic trends in the presence of serially correlated errors
AbstractThis paper studies the problems of estimation and inference in the linear trend model: yt=Ã +Ã¾t+ut, where ut follows an autoregressive process with largest root Ã¾, and Ã¾ is the parameter of interest. We contrast asymptotic results for the cases Ã¾Ã¾Ã¾
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Bibliographic InfoPaper provided by Federal Reserve Bank of Chicago in its series Working Paper Series, Macroeconomic Issues with number 94-19.
Date of creation: 1994
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Other versions of this item:
- 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.
- Eugene Canjels & Mark W. Watson, 1994. "Estimating Deterministic Trends in the Presence of Serially Correlated Errors," NBER Technical Working Papers 0165, National Bureau of Economic Research, Inc.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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- 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.
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