What Can Be Learned From Observed Behavior: Essays on the Predictive Ability of the Utility Maximization Model and Testing for Satisficing

Boccardi Chalela, Maria Jose

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Year:: 2016
Contributor:: Boccardi Chalela, Maria Jose (creator); Dean, Mark (Director); Serrano, Roberto (Reader); Norets, Andriy (Reader); Brown University. Economics (sponsor)
Genre:: theses
Subject:: Behavioral Economics; Axiomatizations; Prediction; Satisficing; Economics--Psychological aspects; Forecasting; Testing; Consumer behavior
Extent:: x, 148 p.
DOI: https://doi.org/10.7301/Z0TM78JV

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Abstract:: An economic model can be understood as a theoretical construct that, by simplifying a complex reality, seeks to aid in the understanding and/or prediction of economic processes. As such, these models are not meant to replicate an intricate reality but intend to help in the understanding of the processes that drive observed outcomes and, if desired, to be used in the prediction of responses to unobserved economic environments. Therefore special interest lies in understanding the behavioral implications of the models. Axiomatizations provide a description of the implications of the model in terms of observable behavior, delivering necessary and sufficient conditions that are equivalent to the theoretical model. Consider, for example, the utility maximization model. Utility functions are unobservable, but their behavioral manifestation -choices- are not. The Generalized Axiom of Revealed Preference provides the necessary and sufficient conditions on observed behavior for it to be consistent with a decision maker that behaves as if her choices maximize her utility function among feasible alternatives. Chapter 1 discusses the limitations of goodness of fit approach for axiomatic models when dealing with incomplete data sets. The lack of power to identify inconsistent behavior with limited data sets can be captured by uncertainty to predict behavior based in the model. By accounting for this uncertainty and allowing for empirically inaccurate behavior, the predictive ability approach proposed in the chapter provides a meaningful criterion to study the suitability of a theory to model observed behavior. Understanding the behavioral implications of the model is also relevant when selecting among theories for modeling behavior. Two seemingly distinct behavioral models cannot be teased apart if they result in the same observed data. For example, the satisficing model is a highly influential and intuitive model of bounded rationality, but it cannot be tested using standard choice data; its behavioral implications are indistinguishable from those of a standard utility maximizer. Chapter 2 provides a novel set of conditions to identify whether a decision maker behaves as satisficing, in contrast to standard utility maximizer exploiting the structure of stochastic choice data without requiring data on the decision process itself.
Notes:: Thesis (Ph.D. -- Brown University (2016)

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Boccardi Chalela, Maria Jose, "What Can Be Learned From Observed Behavior: Essays on the Predictive Ability of the Utility Maximization Model and Testing for Satisficing" (2016). Economics Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.7301/Z0TM78JV

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Economics Theses and Dissertations

Theses and Dissertations for the Economics department.
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