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A1342
Title: Multiple structural breaks in cointegrating regressions: A model selection approach Authors:  Alexander Schmidt - University of Hohenheim (Germany) [presenting]
Karsten Schweikert - University of Hohenheim (Germany)
Abstract: A new comprehensive treatment of structural change in cointegrating regressions is proposed. First, we consider a setting with fixed breakpoint candidates and show that a modified adaptive lasso estimator can consistently estimate structural breaks in the intercept and slope coefficient of a cointegrating regression. Second, we extend our approach to a diverging amount of breakpoint candidates and provide simulation evidence that timing and magnitude of structural breaks are estimated consistently. Third, we use the adaptive lasso estimation to design new tests for cointegration in the presence of multiple structural breaks, derive the asymptotic distribution of our test statistics and show that the proposed tests have power against the null of no cointegration. Finally, we use our new methodology to study the effects of structural breaks on the long-run PPP relationship.