Economic theory is built on the assumption that people are omniscient utility maximizers. In reality, this is unlikely to be true and often people lack information about all alternatives that are available to them; either because the information is unavailable or that the cost of searching for and evaluating that information is high. In this paper, we develop a simple and tractable model that captures satisficing behavior. We show that the model can retrieve consistent parameters under a large range of experimental conditions. We test our model on synthetic data and present an empirical application. We discuss the implications of our results for the use of satisficing choice models in explaining choice.

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An influential body of literature in moral psychology suggests that decision makers consider trade-offs morally problematic, or taboo, when the attributes traded off against each other belong to different 'spheres', such as friendship versus market transactions. This study is the first to model and empirically explore taboo trade-off aversion in a discrete choice context. To capture possible taboo trade-off aversion, we propose to extend the conventional linear in parameters logit model by including penalties for taboo trade-offs. Using this model, we then explore the presence (and size) of taboo trade-off aversion in a data set specifically collected for this purpose. Results, based on estimation of a variety of (Mixed) Logit models with and without taboo trade-off penalties, suggest that there is indeed a significant and sizeable taboo trade-off aversion underlying choice behaviour of respondents.@en