Return
The cyclical component factor model
DOI:10.1016/j.ijforecast.2008.11.011.png)
Abstract
En 中文
Forecasting using factor models based on large data sets has 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. (C) 2008 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keywords:
Factor model
Cyclical components
Estimation
Real time forecasting
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
3.1K
Citations:
9.9K

