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Measuring and Modeling Decision Making


This dissertation studies individual decision making over risky assets in the context of choices from continuous budget sets.

The first chapter presents theoretical work modeling deviations from rational decision-making as errors in an individual's choices. In this chapter, I address the fundamental question, how can we identify mistakes from irrational behavior? Numerous studies in both the lab and field have found evidence of behavior that is inconsistent with rational choice. In a departure from existing indices of goodness-of-fit, this paper develops an intuitive measure of rationality estimated on a revealed preference relation. The proposed metric is a set estimate of the error rate necessary to explain deviations from economic rationality. The error rate arises as a parameter in a contaminated choice model and appears again in the resultant revealed preference relation, which is also contaminated with error. This random revealed preference is a new type of random graph with a unique dependency structure. The random graph is distributed on a space of feasible revealed preference relations and the distribution is identified by the unknown error rate and some ``true'' deterministic relation. Applying weak assumptions on this random graph model equates acyclicity with the general axiom of revealed preferences. A proposed hypothesis test estimates the unknown error rate conditional on the true relation begin acyclic using the expected number of cycles of length two. The result is a set estimate bounding the unknown error rate under the null. A proposed subsampling approach is shown through simulations to be computationally efficient. % emperical results from a lab experiment verify the simulations.

The second chapter presents empirical work measuring decision-making outside the lab, using a smartphone lab-in-field design. This is based on joint work with Shachar Kariv and Raja Sangupta. At the heart of Economics is the principle of rationality, namely that an individual's choices are determined by a fixed, if unknown, set of preferences over alternatives. Numerous lab experiments have found that most people demonstrate rational decision making, even when allowing for individual heterogeneity in preferences. However, questions of external validity remain- is the observed rationality due to the lab setting itself and the short time period over which choices are typically observed? To answer this we leverage the recent widespread adoption of smartphones and the resulting unprecedented access to individuals as they go about their daily lives. We present an experiment that takes a computer-based experiment measuring rationality out of the lab and onto the smartphone. Individuals participate in the experiment on their smartphones, while going about their lives, over a period of five days. We measure the rationality of each individual's choices over this period and find that the distribution of rationality across the sample does not differ from that found in lab experiments. The results of our experiment provide evidence for temporal and environmental external validity of lab experiments. Additionally we collect background data from built-in phone sensors and find no significant correlations between observable behavior and rationality.

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