Graduate Research Group

Behavioral Measurement and Field Experimentation in Finance and Economics

Funded by Gutenberg Council for Young Researchers (GNK)
Start: October 2024


Precise measurement is a hallmark of empirical scientific practice. Inspired by economics' strong emphasis on individual choice behavior as main object of investigation, recent years have seen rapid developments in the design and application of novel measurement protocols based on experimental economic methods, capturing differences in individual characteristics, and applied to better understand differences in economically relevant domains.

As an apparently independent development, quantitative social science research and specifically economics have by now broadly adopted the experimental approach for the identification of causal effects. In recent years experimentation has also increasingly moved outside the laboratory and is regularly applied to field settings, having become a common tool to evaluate policy and understand behavior of individuals, firms, and organizations.

While randomized experiments have classically focused on estimating average treatment effects, attention is now shifting towards also analyzing their heterogeneity. This is particularly relevant for the application of research findings to practice as it allows for tailoring programs to individual characteristics and overcome “one-size-fits-all” approaches.

By starting this graduate group we aim to lay the grounds for building and institutionalizing an active young researcher community, systematically fostering and advancing the development and utilization of behavioral measurement tools and its application to field experiments in empirical social science research. Notably, the group will not only focus on the application of these two methodological paradigms in isolation but also utilize their synergies: If behavioral measures are helpful in detecting individual heterogeneity, embedding them within randomized control trials in the field constitutes a promising approach to systematically analyze systematic heterogeneity of treatment effects.