Finite sample performance of small versus large scale dynamic factor models

Pérez-Quirós, Gabriel, Maximo Camacho and Rocio Alvarez
Authors registered in the RePEc Author Service: Gabriel Perez Quiros

No 8867, CEPR Discussion Papers from C.E.P.R. Discussion Papers

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 indicator

Keywords: Business cycles; Output growth; Time series (search for similar items in EconPapers)
JEL-codes: C22 E27 E32 (search for similar items in EconPapers)
Date: 2012-03
New Economics Papers: this item is included in nep-ecm and nep-for
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Citations: View citations in EconPapers (27)

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Working Paper: Finite sample performance of small versus large scale dynamic factor models (2012)
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