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Time-Varying Cointegration and the Kalman Filter

Burak Eroglu, J. Miller () and Taner Yigit

No 1905, Working Papers from Department of Economics, University of Missouri

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.

Keywords: : time-varying cointegration; Kalman filter; spurious regression (search for similar items in EconPapers)
JEL-codes: C12 C32 C51 Q54 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-env, nep-ets and nep-ore
Date: 2019-06-27
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