I am always open to informal inquiries regarding new projects in any of the fields below. Please contact me.
- Behavioral and experimental economics, especially:
- Positive welfare economics, behavioral public economics
- Interventions and paternalism
- Fairness and justice
Publications in peer-reviewed journals
Find me on Google Scholar and Semantic Scholar.
z-Tree unleashed: A novel client-integrating architecture for conducting z-Tree experiments over the Internet
We present z-Tree unleashed, a novel approach and set of scripts to aid the implementation of computerized behavioral experiments outside the laboratory. z-Tree unleashed enables subjects to join the experiment using a web portal that requires no software apart from a web browser. Experimenters are likewise enabled to administer their experiments from anywhere in the world. Except for z-Tree itself, z-Tree unleashed is entirely based on free and open-source software. In this paper we give a high-level overview of z-Tree unleashed’s features and benefits and its design. We also show how to set up the server and demonstrate the steps required for conducting an entire experiment. We subsequently explain how to leverage the security and routing features of a virtual private network with z-Tree unleashed, enabling servers to securely run behind routers.
Paternalism in Data Sharing
with Ockenfels, A.
Dynamic treatment assignment
with Schneider, S. O.
AnonPay: Enhancing participant privacy in online experiments
Stochastic volatility with mixed frequency data
Master’s thesis, University of Cologne. September 16, 2019.
This thesis focuses on two extensions to the stochastic volatility (SV) model: First, explanatory variables are introduced in the form of a low-frequency mixed-data sampling (MIDAS) term along with the daily autoregressive component of the SV model. Second, we consider a model in which an additional autoregressive term is introduced, but it evolves in a low-frequency manner compared to the daily term. Additional macro variables permit the identification of this supplementary term. Chapter 1 introduces the basic models and provides an overview of previous approaches. Chapter 2 presents the new models and discusses some of their properties. All SV models are estimated using the Kálmán filter; moreover, it is shown how volatility forecasts can be obtained. In chapter 3, we study the models using Monte Carlo simulations. In chapter 4, we apply the models to financial series. Finally, we summarize the results in chapter 5. Proofs, additional figures and tables, and the code of the reference implementation are provided.