RT Generic
T1 Accurate Subsampling Intervals of Principal Components Factors
A1 Maldonado, Javier
A1 Ruiz Ortega, Esther
A2 Universidad Carlos III de Madrid. Departamento de Estadística, 
AB In the context of Dynamic Factor Models (DFMs), one of the most popular procedures for factor extraction is Principal Components (PC). Measuring the uncertainty associated to PC factor estimates should be part of interpreting them. However, the asymptotic distribution of PC factors could not be an appropriate approximation to the finite sample distribution for the sample sizes and cross-sectional dimensions usually encountered in practice. The main problem is that parameter uncertainty is not taken into account. We show that several bootstrap procedures proposed in the context of DFM with goals related to inference are not appropriate to measure the uncertainty ofPC factor estimates. In this paper, we propose an asymptotically validsubsampling procedure designed with this purpose. The finite sampleproperties of the proposed procedure are analyzed and compared with those of the asymptotic and alternative extant bootstrap procedures. The results are empirically illustrated obtaining confidence intervals of the underlying factor in a system of Spanish macroeconomic variables.
SN 2387-0303
YR 2017
FD 2017-12
LK https://hdl.handle.net/10016/23974
UL https://hdl.handle.net/10016/23974
LA eng
NO Both authors acknowledge financial support from the Spanish Ministry of Education and Science, research project ECO2015-70331-C2-2-R.
DS e-Archivo
RD 19 may. 2024