Estimation and Inference in Time Series with Omitted I(1) Variables
AbstractStandard cointegration analysis yields spurious results when relevant I(1) variables are omitted from the model. As an alternative, an unobserved components approach is proposed where the error term is modelled as the sum of a transitory and a random walk component. The latter should capture omitted I(1) variables and is allowed to be correlated with the observed I(1) variables. Provided that the model is correctly specified and identified, the long-run relation between the non-cointegrated variables can be estimated consistently with maximum likelihood using the Kalman filter. The robustness of this approach to the integration properties of the error terms is supported for small samples via an extensive Monte Carlo study. The proposed methodology is applied to testing purchasing power parity.
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Bibliographic InfoArticle provided by De Gruyter in its journal Journal of Time Series Econometrics.
Volume (Year): 2 (2011)
Issue (Month): 2 (January)
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Web page: http://www.degruyter.com
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- G. Everaert, 2012. "A Panel Analysis of the Fisher Effect with an Unobserved I(1) World Real Interest Rate," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/782, Ghent University, Faculty of Economics and Business Administration.
- Herzer, Dierk & Strulik, Holger, 2013. "Religiosity and income: A panel cointegration and causality analysis," Center for European, Governance and Economic Development Research Discussion Papers 168, University of Goettingen, Department of Economics.
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