Time-varying cointegration and the Kalman filter

Burak Alparslan Eroğlu, J. Miller and Taner Yigit

Econometric Reviews, 2022, vol. 41, issue 1, 1-21

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.

Date: 2022
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Working Paper: Time-Varying Cointegration and the Kalman Filter (2019)
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DOI: 10.1080/07474938.2020.1861776

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