Nash equilibrium takes optimization as a primitive, but suboptimal behavior can persist in simple stochastic decision problems. This has motivated the development of other equilibrium concepts such as cursed equilibrium and behavioral equilibrium. We experimentally study a simple adverse...

The literature on proper scoring rules has mostly studied the case of risk neutral agents. We analytically investigate how risk averse, expected utility maximizing forecasters behave when presented with risk neutral proper scoring rules. If the state variable is binary, risk averse agents shade...

Decision makers in health, public policy, technology, and social science are increasingly interested in going beyond ‘one-size-fits-all' policies to personalized ones. Thus, they are faced with the problem of estimating heterogeneous causal effects. Unfortunately, estimating heterogeneous...

How can behavioral scientists incorporate tools from machine learning (ML)? We propose that ML models can be used as upper bounds for the “explainable” variance in a given data set and thus serve as upper bounds for the potential power of a theory. We demonstrate this method in the domain of...

Human information processing is often modeled as costless Bayesian inference. However, research in psychology shows that attention is a computationally costly and potentially limited resource. We thus study Bayesian agents for whom computing posterior beliefs is costly; such agents face a...