MACHINE LEARNING IN LABOR, EDUCATION, AND HEALTH ECONOMICS

Datum der Konferenz: 
19.11.2020 bis 20.11.2020
Deadline zur Einreichung von Beiträgen (Datum): 
01.08.2020
Art der Konferenz: 
Konferenzen in A,CH,D
Inhaltliche Beschreibung: 

The Institute of Employment Research (IAB), the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), and the Labour and Socio-Economic Research Center (LASER) are pleased to announce a workshop on machine learning in economics. Empirical research in economics typically focuses on the unbiased estimation of causal effects. In contrast, statistics and computer science place more value on prediction (especially out-of-sample) and data-driven selection of models and variables.

 

So far, only few studies apply these methods in empirical economic research, but their importance is growing. This holds in particular with the increasing availability of big data for economic research. The two-day workshop seeks to bring together researchers who apply machine learning methods in the following fields: Labor economics, economics of education and health economics.

Land der Konferenz: 
Germany
Name: 
Felicitas Kötzsch / Regina T. Riphahn
Institution: 
FAU Erlangen-Nürnberg
Ort der Konferenz: 
IAB - Institute for Employment Research, Regensburger Str. 100, D-90478 Nuremberg, Germany