Finite sample performance of small versus large scale dynamic factor models

Rocio Alvarez (), Maximo Camacho and Gabriel Perez-Quiros ()
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Rocio Alvarez: Universidad de Alicante
Gabriel Perez-Quiros: Banco de España and CEPR
Authors registered in the RePEc Author Service: Gabriel Perez Quiros

No 1204, Working Papers from Banco de España

Abstract: 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.

Keywords: Business cycles; output growth; time series (search for similar items in EconPapers)
JEL-codes: C22 E27 E32 (search for similar items in EconPapers)
Pages: 53 pages
Date: 2012-02
References: Add references at CitEc
Citations: View citations in EconPapers (23)

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Related works:
Working Paper: Finite sample performance of small versus large scale dynamic factor models (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:bde:wpaper:1204

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