Eroğlu, B. A.Miller, J. I.Yiğit, Taner2021-02-172021-02-172022http://hdl.handle.net/11693/75407We 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.EnglishClimate changeKalman filterSpurious regressionTime-varying cointegrationArticle10.1080/07474938.2020.1861776