Does Modelling a Structural Break Improve Forecasting Accuracy?

Seminar abstract

Mean square forecast error loss implies a bias-variance trade off that suggests that structural breaks of small magnitude should be ignored.

In this presentation, we provide a test ti determine whether modelling a break improves forecast accuracy.

The test is near optimal even when the date of a local-to-zero break is not consistently estimable.

The results extend to forecast combinations that weight the post-break sample and the full sample forecasts by our test statistic. In a large number of macroeconomic time series, we find that structural breaks that are relevant for forecasting occur much less frequently than existing test indicate.

Booking

This is a free event. Please feel free to join us and bring along your colleagues, classmates and friends.

Speaker bio

Dr Andreas Pick is an Associate Professor at the Econometric Institute of the Erasmus School of Economics. He is also the Director of Graduate Studies of the Tinbergen Institute as well as and Economist at the research department of De Nederlandsche Bank and an affiliate with ERIM and the CESifo Institute.

He has been a research fellow at the University of Cambridge and a research economist at the UK Data Management Office.

His research interest are in the areas of applied and theoretical econometrics.

Dr Pick has been published in the Journal of Econometrics and the Journal of Business and Economic Statistics.