We conduct a laboratory experiment to study how demand for redistribution of income depends on self-interest, insurance motives, and social concerns relating to inequality and efficiency. Our choice environments feature large groups of subjects and real world framing, and differ with respect to...

Sequential experiments are deployed in a variety of practices, including for optimizing product recommendations and pricing in online platforms. Such experiments are often characterized by an exploration-exploitation tradeoff that is well-understood when at each time period feedback is received...

Portfolio optimization has been a central problem in finance, often approached with two steps: calibrating the parameters and then solving an optimization problem. Yet, the two-step procedure sometimes encounter the ``error maximization'' problem where inaccuracy in parameter estimation...

I propose a flexible non-parametric method using Recurrent Neural Networks (RNN) to estimate a generalized model of expectation formation. This approach does not rely on restrictive assumptions of functional forms and parametric methods yet nests the standard approaches of empirical studies on...

We study a membrane voltage potential model by means of stochastic control of meanfield stochastic differential equations (SDEs) and by deep learning techniques. The mean-field stochastic control problem is a new type, involving the expected value of a combination of the state X(t) and the...

Individuals often have to decide to which degree of risk they want to expose others, or how much risk to accept if their choice has an externality on third parties. One typical application is a household. We run an experiment in the German Socio-Economic Panel with two members from 494...

Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms...

We propose a new paradigm to study coordination in complex social systems, such as financial markets, that accounts for fundamental uncertainty. This new context has features from prediction markets that have been shown previously to mitigate price bubbles in classical asset market experiments....

Randomised controlled or clinical trials (RCTs) are generally viewed as the most reliable method to draw causal inference as to the effects of a treatment, as they should guarantee that the individuals being compared differ only in terms of their exposure to the treatment of interest. This...