xtbreak: Testing and estimating structural breaks in time-series and panel data in Stata

Jan Ditzen

Italian Stata Users' Group Meetings 2025 from Stata Users Group

Abstract: Identifying structural change is a crucial step in analysis of time series and panel data. The longer the time span, the higher the likelihood that the model parameters have changed as a result of major disruptive events, such as the 2007–2008 financial crisis and the 2020 COVID-19 outbreak. Detecting the existence of breaks and dating them is therefore necessary not only for estimation purposes but also for understanding drivers of change and their effect on relationships. This talk introduces a new community-contributed command called xtbreak, which provides researchers with a complete toolbox for analyzing multiple structural breaks in time-series and panel data. xtbreak can detect the existence of breaks, determine their number and location, and provide break date confidence intervals. A special emphasis of the talk will be put on Python integration to gain speed advantages.

Date: 2025-10-01
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