Testing and estimating structural breaks in time series and panel data in Stata

Identifying structural change is a crucial step when analyzing time series and panel data. The longer the time span, the higher the likelihood that the model parameters have changed because 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 for not only estimation but also understanding drivers of change and their effect on relationships. In this article, we introduce 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,…

• MD
  Ministero dell’Istruzione, dell’Università e della Ricerca

  Award: 2017TA7TYC
• KO
  Knut och Alice Wallenbergs Stiftelse