The Econometrics and Data Science research platform at the Department of Economics focuses on producing high quality research and teaching in Econometrics, Statistics, Causal Inference, Machine Learning and Big Data Analytics.

There is an increased demand both in the private and public sector for data science and machine learning. Following the lead of big tech companies, an increasing number of private companies and public institutions have either been using or are planning to employ machine learning and data science methods to run their day-to-day business more efficiently. Our research platform has done pioneering work on the use of machine learning in economics. For example, we are at the research frontier in terms of the application of image recognition algorithms to transcribe historical documents.

While data science methods are great for solving prediction problems, it is often necessary to uncover causal relationships in order to give empirically-based policy recommendations. Our research group develops new methods and applies state-of-the-art causal inference in the fields of Health and Labour Economics to answer important questions.

In recent years, the members of the platform have consistently published articles in highly ranked journals in Economics and have attracted a vast number of research grants from the Danish Research Council and other external funding sources.

The platform is also responsible for the data collection Survey of Health, Ageing and Retirement in Europe (SHARE).

The platform is chaired by Professor Giovanni Mellace.