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    Testing and dating of structural changes in practice

    implements the algorithm described in Bai & Perron (2003) for simultaneous estimation of multiple breakpoints.

    Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. Power and size properties are derived using Monte Carlo simulations.Thus, there are $m 1$ segments in which the regression coefficients are constant, and the model can be rewritten as $$y_i = x_i^\top \beta_j u_i \qquad (i = i_ 1, \dots, i_j, \quad j = 1, \dots, m 1)$$ where $j$ denotes the segment index.In practice the breakpoints $i_j$ are rarely given exogenously, but have to be estimated.We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power.While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper.

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