The chair of Empirical Economics is primarily concerned with applied econometric research. Fields of application are topics in empirical industrial organization and innovation economics as well as empirical growth economics. Focus lies on the analysis of productivity and efficiency differences of decision making units and processes of structural change. Decision making units are taken to represent input-output relations and can be of a very different nature, e.g. individuals, production units (industrial robots), production processes, establishments, firms, cities, regions or countries. Various econometric, especially microeconometric, methods are used. Efficiency analysis is performed with nonparametric methods which require only very weak assumptions about functional forms.

Research on productivity and efficiency is concerned with the following projects:

• productivity measurement with stochastic nonparametric methods (applied to the relations between firm productivity, market share dynamics and market entry and exit)
• comparison of different methods for productivity and efficiency analysis using Monte-Carlo-Simulations
• engineering applications of efficiency measurement
• efficiency measurement with undesired outputs (applied to energy efficiency of automobiles)
• application of efficiency analysis methods for the comparison of cities, i.e. growth, innovation and change in the industrial composition of cities
• statistical analysis of innovator networks using patent data, thereby exploring the role of “gatekeepers” in innovation systems

A second branch of reserach activities ist about time-series forecasting, focusing on methods that are suited to establish stable leading indicator series by combining the information of a multitude of predictor series.

Research on forecasting is pursued on the following topics:

• forecasting using many time series (forecast combination methods, thick modeling and dynamic factor models)
• forecast evaluation under asymmetric loss