Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/22691 
Year of Publication: 
2006
Series/Report no.: 
Technical Report No. 2006,47
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
We use recent advances in multiple testing to identify the countries for which Purchasing Power Parity (PPP) held over the last century. The approach controls the multiplicity problem inherent in simultaneously testing for PPP on several time series, thereby avoiding spurious rejections. It has higher power than traditional multiple testing techniques by exploiting the dependence structure between the countries with a bootstrap approach. We use a sieve bootstrap approach to account for nonstationarity under the null hypothesis. Our empirical results show that, plausibly, controlling for multiplicity in this way leads to a number of rejections of the null of no PPP that is intermediate between that of traditional multiple testing techniques and that which results if one tests the null on each single time series at some level.
Subjects: 
Multiple Testing
Bootstrap
PPP
Panel Data
JEL: 
C23
C12
F31
Document Type: 
Working Paper

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