In this paper we introduce a sequential seasonal unit root testing approach which explicitly addresses its application to high frequency data. The main idea is to see which unit roots at higher frequency data can also be found in temporally aggregated data. We illustrate our procedure to the analysis of monthly data, and we find, upon analysing the aggregated quarterly data, that a smaller amount of test statistics can sometimes be considered. Monte Carlo simulation and empirical illustrations emphasize the practical relevance of our method.

Additional Metadata
Keywords Monte Carlo method, data analysis, estimation theory, mathematical statistics, numerical analysis, seasonal unit roots, temporal aggregation
Persistent URL dx.doi.org/10.1080/02664760500078912, hdl.handle.net/1765/13751
Journal Journal of Applied Statistics
Citation
Rodrigues, P.M.M, & Franses, Ph.H.B.F. (2005). A sequential approach to testing seasonal unit roots in high frequency data. Journal of Applied Statistics, 32(6), 555–569. doi:10.1080/02664760500078912