Abstract: Structural breaks in economics can occur for a variety of reasons, such as changes in economic policy, changes in the structure of the economy or an invention that changes a specific industry. As a result, this concept has a widespread use in economics. In econometrics, a popular way to model such changes is to include dummy variables in the regression function. If such breaks occur then a regression model that neglects those changes can provide a misleading basis for inference and forecasting. As a result, correctly detecting and identifying the nature of the structural breaks may have important effects on policy evaluation and recommendation. In this talk I start by motivating the theoretical and practical relevance of structural breaks in economic time series. Then, I will identify some of the main challenges related with the estimation of the number of structural breaks and corresponding break dates. Finally, I will present some suggestions from the econometric literature to deal with these issues and I will highlight my own research work and agenda.