This paper explores a general model of the evolution and adaption of hedonic utility. It is shown that optimal utility will be increasing strongly in regions where choices have to be made often and decision mistakes have a severe impact on fitness. Several applications are suggested. In the context of intertemporal preferences, the model offers an evolutionary explanation for the existence of conflicting short- and long-run interests that lead to dynamic inconsistency. Concerning attitudes toward risk, an evolutionary explanation is given for S-shaped value functions that adjust to the decision maker's environment. (JEL D81, D83)

In the presence of a time-inconsistency problem with agency contracts, we show that competitive markets can implement allocations that Pareto-dominate those achieved by a benevolent government, and they induce more effort. We analyze a model with moral hazard and a two-sided lack of commitment. After agents have chosen their work, firms can modify contracts and agents can switch firms. If the ex post market outcome satisfies a weak notion of competitiveness and sufficiently separates individuals, it is Pareto superior to a government’s allocation with a complete breakdown of incentives. Moreover, competitive markets without commitment implement more effort in equilibrium under general conditions.

Surveys measuring happiness or preferences generate discrete ordinal data. Ordered response models, which are used to analyze such data, suffer from an identification problem. Their conclusions depend on distributional assumptions about a latent variable. We propose using response times to solve that problem. Response times contain information about the distribution of the latent variable through a chronometric effect. Using an online survey experiment, we verify the chronometric effect. We then provide theoretical conditions for testing conventional distributional assumptions. These assumptions are rejected in some cases, but overall our evidence is consistent with the qualitative validity of the conventional models. (JEL C14, D60, D91, I31)

A nudge is a paternalistic government intervention that attempts to improve choices by changing the framing of a decision problem. We propose a welfare-theoretic foundation for nudging similar in spirit to the classical revealed preference approach, by investigating a framework in which preferences and mistakes of an agent can be elicited from her choices under different frames. We provide characterizations of the classes of behavioral models in which the information required for nudging can or cannot be deduced from choice data.

When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.