The cyclical component factor model
AbstractForecasting using factor models based on large data sets have received ample attention due to the models’ ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly outperform the simple autoregressive model when using data from other countries. In this paper we propose to estimate the factors based on the pure cyclical components of the series entering the large data set. Monte Carlo evidence and an empirical illustration using Danish data shows that this procedure can indeed improve on pseudo real time forecast accuracy.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2008-44.
Date of creation: 02 Sep 2008
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Web page: http://www.econ.au.dk/afn/
Factor model; Cyclical components; Estimation; Real time forecasting;
Other versions of this item:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-09-05 (All new papers)
- NEP-ECM-2008-09-05 (Econometrics)
- NEP-ETS-2008-09-05 (Econometric Time Series)
- NEP-FOR-2008-09-05 (Forecasting)
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