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Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods

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  • G. EVERAERT

Abstract

A regression including integrated variables yields spurious results if the residuals contain a unit root. Although the obtained estimates are unreliable, this does not automatically imply that there is no long-run relation between the included variables as the unit root in the residuals may be induced by omitted or unobserved integrated variables. This paper uses an unobserved component model to estimate the partial long-run relation between observed integrated variables. This provides an alternative to standard cointegration analysis. The proposed methodology is described using a Monte Carlo simulation and applied to investigate purchasing-power parity.

Suggested Citation

  • G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
    • Handle: RePEc:rug:rugwps:07/452
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    Cited by:

    1. Mitra, Sinchan & Sinclair, Tara M., 2012. "Output Fluctuations In The G-7: An Unobserved Components Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 16(3), pages 396-422, June.

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    More about this item

    Keywords

    Spurious Regression; Cointegration; Unobserved Component Model; PPP.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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

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