摘要：The problem of detecting structural changes arises most often when analyzing time series data with linear regression models, especially in econometrics. Consider the standard linear regression model yi = x> i i + ui (i = 1, . . . , n), where at time i, yi is the observation of the dependent variable, xi is a vector of regressors, i is the kdimensional vector of regression coefficients and ui is an iid error term. Tests on structural change are concerned with testing the null hypothesis of “no structural change” H0 : i = 0 (i = 1, . . . , n), i.e., that the regression coefficients remain constant, against the alternative that the coefficient vector varies over time.
