Eroğlu, Burak Alparslan2021-06-292021-06-2920200747-4938https://hdl.handle.net/11411/3908https://doi.org/10.1080/07474938.2020.1861776We 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.eninfo:eu-repo/semantics/openAccessClimate changeKalman filterspurious regressiontime-varying cointegrationArticle2-s2.0-8509946663610.1080/07474938.2020.1861776Q1WOS:000607701900001