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 National University of Singapore, Department of Economics, SCAPE in its series SCAPE Policy Research Working Paper Series with number 0905.
Length: 32 pages
Date of creation: Dec 2009
Date of revision:
Null of stationarity; MA unit root; mixed-frequency regression; variance difference; normal distribution; power.;
Other versions of this item:
- Tilak Abeysinghe & Gulasekaran Rajaguru, 2009. "A Gaussian Test for Cointegration," Microeconomics Working Papers 22013, East Asian Bureau of Economic Research.
- Tilak Abeysinghe & Gulasekaran Rajaguru, 2010. "A Gaussian Test for Cointegration," Macroeconomics Working Papers 23040, East Asian Bureau of Economic Research.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-01-23 (All new papers)
- NEP-ECM-2010-01-23 (Econometrics)
- NEP-ETS-2010-01-23 (Econometric Time Series)
- NEP-SEA-2010-01-23 (South East Asia)
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