PARAMETRIC CHANGE POINT ESTIMATION, TESTING AND CONFIDENCE INTERVAL APPLIED IN BUSINESS

Abstract

In many applications like finance, industry and medicine, it is important to considerthat the model parameters may undergo changes at unknown moment in time.This paper deals with estimation, testing and confidence interval of a change pointfor a univariate variable which is assumed to be normally distributed. To detect apossible change point, we use a Schwarz Information Criterion (SIC) statistic whoseasymptotic distribution under the null hypothesis is determined. The percentilebootstrap method is used to construct the confidence interval of the estimatedchange point. The developed tools and methods are applied to the 1987 – 1988 UStrade deficit data. Our results show that a significant change in US trade deficitoccurred in November 1987. Further, it is shown that the percentile bootstrapconfidence intervals are not always symmetrical.