A Gaussian Test for Cointegration
AbstractWe use a mixed-frequency regression technique to develop a test for cointegration under the null of stationarity of the deviations from a long-run relationship. What is noteworthy about this MA unit root test, based on a variance-difference, is that, instead of having to deal with non-standard distributions, it takes the testing back to the normal distribution and offers a way to increase power without having to increase the sample size substantially. Monte Carlo simulations show minimal size distortions even when the AR root is close to unity and that the test offers substantial gains in power against near-null alternatives in moderate size samples. An empirical exercise illustrates the relative usefulness of the test further.
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Bibliographic InfoPaper provided by East Asian Bureau of Economic Research in its series Microeconomics Working Papers with number 22013.
Date of creation: Jan 2009
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Null of stationarity; MA unit root; mixed-frequency regression; variance difference; normal distribution; power.;
Other versions of this item:
- Tilak Abeysinghe & Gulasekaran Rajaguru, 2010. "A Gaussian Test for Cointegration," Macroeconomics Working Papers 23040, East Asian Bureau of Economic Research.
- Gulasekaran Rajaguru & Tilak Abeysinghe, 2009. "A Gaussian Test for Cointegration," SCAPE Policy Research Working Paper Series 0905, National University of Singapore, Department of Economics, SCAPE.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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