Alexander Aue, PhD
Department of Statistics
University of California, Davis


Title: Sequential procedures for multiple time series regressions

Abstract: We consider a multiple regression model in which the explanatory variables are specified by
time series. To sequentially test for the stability of the regression parameters in time, we introduce a
detector which is based on the first excess time of a CUSUM-type statistic over a suitably constructed
threshold function. In this talk, we study the delay time associated with this detector. As our main
result, we discuss the limit distribution of the delay time and provide thereby a theory that extends the
benchmark average run length concept utilized in most of the sequential monitoring literature. To
highlight the applicability of the limit results in finite samples, we present a Monte Carlo simulation
study and an application to macroeconomic data.