Using All Observations when Forecasting under Structural Breaks
AbstractWe extend the idea of the trade-off window approach by Pesaran and Timmermann (2007) of using observations preceding the last structural break to estimate model parameters for the purpose of forecasting. Our weighted least squares method utilizes information in all observations but with weights varying from one to another interval between breaks. This leads to a smaller mean squared prediction error which is illustrated by simulations. The proposed procedure is computationally simple having a convenient associated optimization program. We also describe and evaluate a cross-validation analog of the proposed method.
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Bibliographic InfoArticle provided by Finnish Economic Association in its journal Finnish Economic Papers.
Volume (Year): 20 (2007)
Issue (Month): 2 (Autumn)
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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