Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments
Abstract
We review recent developments in detecting and estimating multiple change-points in time series models with exogenous and endogenous regressors, panel data models, and factor models. This review differs from others in multiple ways: (1) it focuses on inference about the change-points in slope parameters, rather than in the mean of the dependent variable - the latter being common in the statistical literature; (2) it focuses on detecting - via sequential testing and other methods - multiple change-points, and only discusses one change-point when methods for multiple change-points are not available; (3) it is meant as a practitioner's guide for empirical macroeconomists first, and as a result, it focuses only on the methods derived under the most general assumptions relevant to macroeconomic applications.
Cite
@article{arxiv.2507.22204,
title = {Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments},
author = {Otilia Boldea and Alastair R. Hall},
journal= {arXiv preprint arXiv:2507.22204},
year = {2025}
}