Bootstrap confidence intervals in a switching regressions model

Traditional switching regression methods produce slope and intercept estimates conditional on the change point estimate, with confidence intervals that overstate their precision. This paper describes the problem and a bootstrap alternative. Extensive sampling experiments confirm that the traditional methods overstate precision, and that bootstrap confidence intervals are far more accurate.