No-Cointegration Test Based on Fractional Differencing: Some Monte Carlo Results

This paper examines the use of the t-statistic in the Geweke-Porter-Hudak regression for the estimation of the fractional differencing parameter as a test for cointegration. The critical values of the test statistic are estimated using Monte Carlo methods. The results confirm that the test will over...

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Bibliographic Details
Main Authors: TSE, Yiu Kuen, Anh, V. V., Tieng, Q. M.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1999
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Online Access:https://ink.library.smu.edu.sg/soe_research/314
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Institution: Singapore Management University
Language: English
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Summary:This paper examines the use of the t-statistic in the Geweke-Porter-Hudak regression for the estimation of the fractional differencing parameter as a test for cointegration. The critical values of the test statistic are estimated using Monte Carlo methods. The results confirm that the test will over-reject the null hypothesis of no cointegration if the standard-normal critical values are used. The estimated critical values are generally robust to the nuisance parameters in the autoregressive or moving average specification of the error process of the component time series. Exceptions occur when the dependent variable in the cointegration regression follows an autoregressive process with a large positive parameter or a moving average process with a large negative parameter.