A new approach to robust inference in cointegration
AbstractA new approach to robust testing in cointegrated systems is proposed using nonparametric HAC estimators without truncation. While such HAC estimates are inconsistent, they still produce asymptotically pivotal tests and, as in conventional regression settings, can improve testing and inference. The present contribution makes use of steep origin kernels which are obtained by exponentiating traditional quadratic kernels. Simulations indicate that tests based on these methods have improved size properties relative to conventional tests and better power properties than other tests that use Bartlett or other traditional kernels with no truncation.
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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 91 (2006)
Issue (Month): 2 (May)
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Web page: http://www.elsevier.com/locate/ecolet
Other versions of this item:
- Sainan Jin & Peter C.B. Phillips & Yixiao Sun, 2005. "A New Approach to Robust Inference in Cointegration," Cowles Foundation Discussion Papers 1538, Cowles Foundation for Research in Economics, Yale University.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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