Research

Matei Demetrescu's research interests mainly concern econometric forecasting methodology. Currently, inferential aspects in predictive regressions with persistent predictors are studied in particular, without, however, neglecting other related topics such as forecast comparisons under non-stationarity or when using machine learning methods. Last but not least, methods for "large-N large-T" panels (as can also be used in spatial statistics) are developed, often with reference to the analysis of financial data. The research takes place in close cooperation with the Chair of Business and Social Statistics and the Chair of Econometrics.

Further details on the individual research interests of the chair can be found in the respective staff websites.