This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components. The dynamic principal components are obtained using time and frequency domain methods. The forecasting accuracy is evaluated in two ways for GDP growth. First, we question whether it is more appropriate to use aggregate or disaggregate data (with three disaggregating levels) to extract the factors. Second, we focus on the determination of the number of factors obtained either from various criteria or from a fixed choice.
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Paper provided by Banque de France in its series Documents de Travail with number
232.
Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation
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