Cointegrating rank selection in models with time-varying variance

A-Tier
Journal: Journal of Econometrics
Year: 2012
Volume: 169
Issue: 2
Pages: 155-165

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Reduced rank regression (RRR) models with time varying heterogeneity are considered. Standard information criteria for selecting cointegrating rank are shown to be weakly consistent in semiparametric RRR models in which the errors have general nonparametric short memory components and shifting volatility provided the penalty coefficient Cn→∞ and Cn/n→0 as n→∞. The AIC criterion is inconsistent and its limit distribution is given. The results extend those in Cheng and Phillips (2009a) and are useful in empirical work where structural breaks or time evolution in the error variances is present. An empirical application to exchange rate data is provided.

Technical Details

RePEc Handle
repec:eee:econom:v:169:y:2012:i:2:p:155-165
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25