Data science in agricultural economics

Junior Research Group , PhenoRob (Cluster of Excellence), University of Bonn

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Welcome to our group page!

The research of the group focuses on developing and applying novel data science tools in the area of agricultural and environmental economics. One particular focus is on applying econometric and machine learning tools to answer causal research questions.

We are part of the Cluster of Excellence “PhenoRob – Robotics and Phenotyping for Sustainable Crop Production” at the University of Bonn and Forschungszentrum Jülich. PhenoRob aims to enhance the sustainability of crop production by optimizing breeding and farm management using new technologies. Our focus in in PhenoRob is on studying the economic and environmental aspects of farm level agricultural technology. Here, we aim to understand under which conditions farmers adopt novel technologies, how they are used in practice and what economic and environmental consequences result from this. With this we aim to contribute to answering the simple, but challenging, question of “how to produce more with less”.


Hugo Storm, PhD
Research Group Leader
Niebuhrstraße 1a
53115 Bonn, Germany Phone: +49 228 60828

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Sep 6, 2021 Looking for a master thesis topic? Check out our new topic on “Measuring the risk of labor automation through skills required in job postings”, click here for more information.
Interested in this or a related topic, write an email to:
Jun 2, 2021 We are currently advertising a master thesis topic on the effects of improved water irrigation. For more information, click here.
Jun 1, 2021 New paper! How important are peer effects for farms organic conversion decision? Existing research primarily looked at positive spatial spillovers, however, we find empirical evidence that seeing neighbours “dis-adopting” might be the more important peer effect.
Check out “The case of organic dairy conversion in Norway: Assessment of multivariate neighbourhood effects”
May 17, 2021 New online lecture: How to use LASSO for model selection when you are interested in causal model interpretation

Lecture video
Slides and R code examples
May 5, 2021 Interested in working with us? We are looking for student assistance to support our work. For more details see here and here.