### Abstract

unconditional and the conditional mean tests detect a break in the mean of interest rates. However, for the other two series, the unconditional mean test does not detect a break, while the conditional mean tests based on dynamic regression models occasionally detect a break, with the implied break-point estimator varying across different dynamic specifications. For all series, the unconditional variance does not detect a break while most tests for the conditional variance do detect a break which also varies across specifications.

Original language | English |
---|---|

Article number | 27 |

Number of pages | 39 |

Journal | Econometrics |

Volume | 6 |

Issue number | 2 |

DOIs | |

Publication status | Published - Jun 2018 |

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### Keywords

- structural change; sup Wald test; dynamic misspecification

### Cite this

*Econometrics*,

*6*(2), [27]. https://doi.org/10.3390/econometrics6020027

}

*Econometrics*, vol. 6, no. 2, 27. https://doi.org/10.3390/econometrics6020027

**Structural break tests robust to regression misspecification.** / Abi Morshed, Alaa; Andreou, E.; Boldea, Otilia.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Structural break tests robust to regression misspecification

AU - Abi Morshed, Alaa

AU - Andreou, E.

AU - Boldea, Otilia

PY - 2018/6

Y1 - 2018/6

N2 - Structural break tests for regression models are sensitive to model misspecification. We show—analytically and through simulations—that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits severe size distortions when the conditional mean dynamics are misspecified. We also show that the sup Wald test for breaks in the unconditional mean and variance does not have the same size distortions, yet benefits from similar power to its conditional counterpart in correctly specified models. Hence, we propose using it as an alternative and complementary test for breaks. We apply the unconditional and conditional mean and variance tests to three US series: unemployment, industrial production growth and interest rates. Both theunconditional and the conditional mean tests detect a break in the mean of interest rates. However, for the other two series, the unconditional mean test does not detect a break, while the conditional mean tests based on dynamic regression models occasionally detect a break, with the implied break-point estimator varying across different dynamic specifications. For all series, the unconditional variance does not detect a break while most tests for the conditional variance do detect a break which also varies across specifications.

AB - Structural break tests for regression models are sensitive to model misspecification. We show—analytically and through simulations—that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits severe size distortions when the conditional mean dynamics are misspecified. We also show that the sup Wald test for breaks in the unconditional mean and variance does not have the same size distortions, yet benefits from similar power to its conditional counterpart in correctly specified models. Hence, we propose using it as an alternative and complementary test for breaks. We apply the unconditional and conditional mean and variance tests to three US series: unemployment, industrial production growth and interest rates. Both theunconditional and the conditional mean tests detect a break in the mean of interest rates. However, for the other two series, the unconditional mean test does not detect a break, while the conditional mean tests based on dynamic regression models occasionally detect a break, with the implied break-point estimator varying across different dynamic specifications. For all series, the unconditional variance does not detect a break while most tests for the conditional variance do detect a break which also varies across specifications.

KW - structural change; sup Wald test; dynamic misspecification

U2 - 10.3390/econometrics6020027

DO - 10.3390/econometrics6020027

M3 - Article

VL - 6

JO - Econometrics

JF - Econometrics

IS - 2

M1 - 27

ER -