Forecasting with Difference-Stationary and Trend-Stationary Models
AbstractThe behavior of difference-stationary and trend-stationary processes has been the subject of considerable analysis in the literature. Nevertheless, there do not seem to be any direct comparisons of properties of each for both being potential data-generation processes. We look at the consequences of incorrect choice between these models for forecasting when parameters are known, and when parameters have to be estimated. The outcomes are surprisingly different from established results.
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Bibliographic InfoPaper provided by University of Warwick, Department of Economics in its series The Warwick Economics Research Paper Series (TWERPS) with number 516.
Length: 22 pages
Date of creation: 1998
Date of revision:
TIME SERIES ; STATISTICAL ANALYSIS ; ECONOMETRICS;
Other versions of this item:
- Michael P. Clements & David F.Hendry, 2001. "Forecasting with difference-stationary and trend-stationary models," Econometrics Journal, Royal Economic Society, vol. 4(1), pages S1-S19.
- David Hendry & Michael P. Clements, 2000. "Forecasting with Difference-Stationary and Trend-Stationary Models," Economics Series Working Papers 5, University of Oxford, Department of Economics.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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