with Ivana Logar, Klaus Glenk and Jürgen Meyerhoff
Discrete-choice experiments are a standard method to derive willingness-to-pay estimates for non-market goods like environmental quality or ecosystem services. Estimation of respondents’ willingness-to-pay requires that the researcher defines a cost attribute with a series of levels – the cost vector. Several studies have shown that such estimates derived from choice experiments can be sensitive to the cost vector, which raises concerns about their reliability. We show that cost-vector effects may arise if respondents try to infer what to pay for a certain combination of attribute levels from the design of the choice experiment and present cognitive models of Bayesian updating that correct for such inferences. Using data from a choice experiment on micro- and nanoplastic pollution of freshwater systems in Switzerland, we demonstrate how willingness-to-pay estimates can be corrected for anchoring or learning and discuss several implications for welfare analysis and policy design.
with Urs Fischbacher, Katrin Schmelz and Georg Sator
Morality is one of the key features of the human species. It enables us to live in and benefit from social groups and thereby constitutes the foundation of social coexistence and civilization. The starting point of our study is the notion that many important moral choices are not made in social isolation, but in the presence of other people and other people’s moral judgments. This poses the question whether moral judgment and decision-making is prone to social influence. We conduct an online experiment which allows us to identify the effect of social information on people’s publicly stated moral convictions. The experimental design uses a battery of moral trilemmas allowing use to separate conformity, anticonformity and independence in moral judgments without drawing on deceptive methods.
Matthew Embrey, Friederike Mengel and Ronald Peeters
We introduce a novel method to elicit strategies in indefinitely repeated games and apply it to games of strategic substitutes and complements. We find that out of 256 possible unit recall machines (and 1024 full strategies) participants could use, only five machines are used more than 5 percent of the time. Those are ‘static Nash’, ‘myopic best response”, ’Tit-for-Tat’ and two ‘Nash reversion” strategies. We compare outcome data with ’hot’ treatments and find that the fact that we elicit strategies did not affect the path of play. We further compare the frequencies of the elicited strategies with results of the strategy frequency estimation method. We also discuss applications to IO literature and compare insights to previous literature on strategy elicitation mostly focused on the prisoner’s dilemma.