Time-Varying Cointegration and the Kalman Filter

Year: 
2019
Working Paper Number: 
WP 19-05
Abstract: 

We show that time-varying parameter state-space models estimated using the Kalman filter are particularly vulnerable to the problem of spurious regression, because the integrated error is transferred to the estimated state equation. We offer a simple yet effective methodology to reliably recover the instability in cointegrating vectors. In the process, the proposed methodology successfully distinguishes between the cases of no cointegration, fixed cointegration, and time-varying cointegration. We apply these proposed tests to elucidate the relationship between concentrations of greenhouse gases and global temperatures, an important relationship to both climate scientists and economists.

JEL Codes: 
C12, C32, C51, Q54
Authors: 

Burak Alparslan Eroglu

Taner Yigit

PDF: