Finite Sample Performance of Small Versus Large Scale Dynamic Factor Models
Universidad de Alicante
Autonomous University of Barcelona - Department of Economics; Universidad de Murcia - Departamento de Metodos Cuantitativos
Bank of Spain
February 10, 2012
Banco de Espana Working Paper No. 1204
We examine the finite-sample performance of small versus large scale dynamic factor models. Our Monte Carlo analysis reveals that small scale factor models out-perform large scale models in factor estimation and forecasting for high levels of cross-correlation across the idiosyncratic errors of series belonging to the same category, for oversampled categories and, especially, for high persistence in either the common factor series or the idiosyncratic errors. Using a panel of 147 US economic indicators, which are classified into 13 economic categories, we show that a small scale dynamic factor model that uses one representative indicator of each category yields satisfactory or even better forecasting results than a large scale dynamic factor model that uses all the economic indicators.
Number of Pages in PDF File: 53
Keywords: business cycles, output growth, time series
JEL Classification: E32, C22, E27working papers series
Date posted: February 12, 2012
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