Some effects of lagged relationship on the cointegration inferences in small samples
A Monte Carlo simulation is performed in order to investigate the effects of lagged relationship on the cointegration inference in a single equation. Given a small data sample the standard application of Engle–Granger cointegration testing procedure is significantly affected by the presence of lag...
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Vilnius University Press
2004-12-01
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| Series: | Lietuvos Matematikos Rinkinys |
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| Online Access: | https://www.journals.vu.lt/LMR/article/view/32086 |
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| author | Virmantas Kvedaras |
| author_facet | Virmantas Kvedaras |
| author_sort | Virmantas Kvedaras |
| collection | DOAJ |
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A Monte Carlo simulation is performed in order to investigate the effects of lagged relationship on the cointegration inference in a single equation. Given a small data sample the standard application of Engle–Granger cointegration testing procedure is significantly affected by the presence of lagged relationship. For instance, in a sample size of 30 observations, the power of the two-step Engle–Granger cointegration testing procedure, using the Dickey–Fuller (DF) or Augmented DF (ADF) test statistic in the second step, drops from almost one hundred percent, when the correct lag structure of cointegration relationship is respected, to around sixty percent, when the effect of 4 lags is ignored.
A simple parametric correction is proposed allowing avoiding the negative influence. When the cointegration parameters are known, the correction is applied directly to DF and ADF regressions. Whenever the parameters are estimated in the first step of Engle–Granger procedure, the cointegration regression should be modified instead in order to avoid the autocorrelation caused bias of parameter estimates. A Monte Carlo simulation reveals that such simple correction retains the power of the cointegration testing procedure without having a negative effect on the nominal size.
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| format | Article |
| id | doaj-art-b07820f955254af0ab19063d3ed4ef31 |
| institution | Kabale University |
| issn | 0132-2818 2335-898X |
| language | English |
| publishDate | 2004-12-01 |
| publisher | Vilnius University Press |
| record_format | Article |
| series | Lietuvos Matematikos Rinkinys |
| spelling | doaj-art-b07820f955254af0ab19063d3ed4ef312025-01-20T18:16:33ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2004-12-0144spec.10.15388/LMR.2004.32086Some effects of lagged relationship on the cointegration inferences in small samplesVirmantas Kvedaras0Vilnius University A Monte Carlo simulation is performed in order to investigate the effects of lagged relationship on the cointegration inference in a single equation. Given a small data sample the standard application of Engle–Granger cointegration testing procedure is significantly affected by the presence of lagged relationship. For instance, in a sample size of 30 observations, the power of the two-step Engle–Granger cointegration testing procedure, using the Dickey–Fuller (DF) or Augmented DF (ADF) test statistic in the second step, drops from almost one hundred percent, when the correct lag structure of cointegration relationship is respected, to around sixty percent, when the effect of 4 lags is ignored. A simple parametric correction is proposed allowing avoiding the negative influence. When the cointegration parameters are known, the correction is applied directly to DF and ADF regressions. Whenever the parameters are estimated in the first step of Engle–Granger procedure, the cointegration regression should be modified instead in order to avoid the autocorrelation caused bias of parameter estimates. A Monte Carlo simulation reveals that such simple correction retains the power of the cointegration testing procedure without having a negative effect on the nominal size. https://www.journals.vu.lt/LMR/article/view/32086cointegration testslagged relationshipMonte Carlo simulationEngle–Granger procedure |
| spellingShingle | Virmantas Kvedaras Some effects of lagged relationship on the cointegration inferences in small samples Lietuvos Matematikos Rinkinys cointegration tests lagged relationship Monte Carlo simulation Engle–Granger procedure |
| title | Some effects of lagged relationship on the cointegration inferences in small samples |
| title_full | Some effects of lagged relationship on the cointegration inferences in small samples |
| title_fullStr | Some effects of lagged relationship on the cointegration inferences in small samples |
| title_full_unstemmed | Some effects of lagged relationship on the cointegration inferences in small samples |
| title_short | Some effects of lagged relationship on the cointegration inferences in small samples |
| title_sort | some effects of lagged relationship on the cointegration inferences in small samples |
| topic | cointegration tests lagged relationship Monte Carlo simulation Engle–Granger procedure |
| url | https://www.journals.vu.lt/LMR/article/view/32086 |
| work_keys_str_mv | AT virmantaskvedaras someeffectsoflaggedrelationshiponthecointegrationinferencesinsmallsamples |