Decoupling cooperation and punishment in humans shows that punishment is not an altruistic trait

Economic experiments have suggested that cooperative humans will altruistically match local levels of cooperation (conditional cooperation) and pay to punish non-cooperators (altruistic punishment). Evolutionary models have suggested that if altruists punish non-altruists this could favour the evolution of costly helping behaviours (cooperation) among strangers. An often-key requirement is that helping behaviours and punishing behaviours form one single conjoined trait (strong reciprocity). Previous economics experiments have provided support for the hypothesis that punishment and cooperation form one conjoined, altruistically motivated, trait. However, such a conjoined trait may be evolutionarily unstable, and previous experiments have confounded a fear of being punished with being surrounded by cooperators, two factors that could favour cooperation. Here, we experimentally decouple the fear of punishment from a cooperative environment and allow cooperation and punishment behaviour to freely separate (420 participants). We show, that if a minority of individuals is made immune to punishment, they (i) learn to stop cooperating on average despite being surrounded by high levels of cooperation, contradicting the idea of conditional cooperation and (ii) often continue to punish, ‘hypocritically’, showing that cooperation and punishment do not form one, altruistically motivated, linked trait.

Social Structures and Reputation in Expert Review Systems

We model an expert review system where two producers competing for market share each are evaluated by two raters. Employing economics experiments, the paper examines how the rater’s incentive to provide objective feedback can be distorted in the presence of social ties and different penalty structures for assigning unobjective ratings. The results reject the self-interested model. We find that raters assign more biased ratings to help the producer they know compete, and this distortion is exacerbated when the reputation cost for rating unobjectively is lowered. Counterintuitively, when both of the raters know the same producer, the likelihood of biased ratings drops significantly. To explain the empirical regularities, we develop a behavioral economics model and show that the rater’s utility function should account not only for social preferences toward the producer, but also the rater’s psychological aversion toward favoring a producer more than the other rater. Our findings demonstrate that it is critical for policymakers to be cognizant of the nonpecuniary factors that can influence behavior in expert review systems. This paper was accepted by John List, behavioral economics.

Becoming Just by Eliminating Injustice

This chapter explores how property emerges as a moral convention. Several laboratory experiments on property in its nascence are used to understand this process. A key feature of these economics experiments is that the participants can chat in real time with one another regarding their activities. These candid conversations in the heat of the moment make up the data by which I explain how anonymous strangers in a group become just by mutually respecting what is mine and what is thine. The dialogue also illustrates what it means for someone to be unjust, namely, inflicting real and positive harm on others. As a window into the minds of the participants, the language further supports Adam Smith’s claim that the resentment of harm undergirds our moral sense of property. We become just in terms of respecting the boundaries of property through the fellow feeling of the ill desert of harm.

A comment on randomization checks in economics experiments

This note deals with baseline comparisons in randomized controlled trials in economics. Although widely spread in the literature, resorting to p-values is an inadequate procedure to assess whether randomization was successfully carried out. Instead, it is promising to use standardized differences. In addition, challenges to evaluate the quality of randomization appear if self-selection is systematically different across the com-pared treatments.

Adapting neuroeconomics for environmental and energy policy

Neuroimaging methods provide insight into the neural mechanisms underlying the decision process, characterizing choice at the individual level and, in a growing number of contexts, predicting national- and market-level behavior. This dual capacity to examine heterogeneity while forecasting aggregate choice is particularly beneficial to those studying environmental decision-making. To effectively reduce residential energy usage and foster other pro-environmental behaviors, policy-makers must understand the effects of information frames and behavioral nudges across individuals who hold a diverse array of attitudes toward the environment and face a broad range of barriers to action. This paper articulates the potential of neuroeconomic methods to aid environmental policy-makers interested in behavior change, especially those interested in closing the energy efficiency gap. Investigation into the roles of affect, eco-labeling and social norms will be discussed, as well as personal identity and climate change beliefs. Combining neuroimaging with behavioral economics experiments can inform the development of effective messaging, characterize the influence of individual differences on the decision process and aid in forecasting the efficacy of policy interventions at scale.