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Time-Varying Cointegration and the Kalman Filter

Author

Listed:
  • Burak Alparslan Eroglu
  • J. Isaac Miller

    (Department of Economics, University of Missouri)

  • Taner Yigit

Abstract

Published in Econometric Reviews (https://doi.org/10.1080/07474938.2020.1861776) 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.

Suggested Citation

  • Burak Alparslan Eroglu & J. Isaac Miller & Taner Yigit, 2019. "Time-Varying Cointegration and the Kalman Filter," Working Papers 1905, Department of Economics, University of Missouri.
    • Handle: RePEc:umc:wpaper:1905
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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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