Back to Search Start Over

Bias correction for time series factor models.

Authors :
Alonso, Andrés M.
Bastos, Guadalupe
García-Martos, Carolina
Source :
Journal of Statistical Computation & Simulation. May2018, Vol. 88 Issue 8, p1576-1602. 27p.
Publication Year :
2018

Abstract

In this paper we work with multivariate time series that follow a Factor Model. In particular, we consider the setting where factors are dominated by highly persistent AutoRegressive (AR) processes and samples that are rather small. Therefore, the factors' AR models are estimated using small sample bias correction techniques. A Monte Carlo study reveals that bias-correcting the AR coefficients of the factors allows to obtain better results in terms of prediction interval coverage. As expected, the simulation shows that bias-correction is more successful for smaller samples. We present the results assuming the AR order and number of factors are known as well as unknown. We also study the advantages of this technique for a set of Industrial Production Indexes of several European countries. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00949655
Volume :
88
Issue :
8
Database :
Academic Search Index
Journal :
Journal of Statistical Computation & Simulation
Publication Type :
Academic Journal
Accession number :
128634586
Full Text :
https://doi.org/10.1080/00949655.2018.1442467