Paulo Natenzon

Random Evolving Lotteries and Intrinsic Preference for Information, with Faruk Gul and Wolfgang Pesendorfer.
Econometrica, Vol. 89, No. 5 (September, 2021), 2225–2259.

Random Choice and Learning.
Journal of Political Economy, Vol. 127, No. 1, (February, 2019), 419–457.

Subjective Ambiguity and Preference for Flexibility, with Leandro Gorno.
Journal of Economic Behavior & Organization, Vol. 154, (October, 2018), 24–32.

Random Choice as Behavioral Optimization, with Faruk Gul and Wolfgang Pesendorfer.
Econometrica, Vol. 82, No. 5 (September, 2014), 1873–1912.

With Junnan He.

The degree to which consumers treat different options as distinct or differentiated is a key determinant of market competition and pricing. To facilitate the measurement of differentiation, we develop a flexible yet tractable model of random choice in a multi-attribute setting. We show the analyst can separately identify vertical and horizontal differentiation from binary comparison data alone. We characterize the binary choice rules that arise from our model using four easily understood axioms. In multinomial choice, we show the intersection of our model with the classic random utility framework yields random coefficients with an elliptical distribution. We provide applications to consumer demand with differentiated products and to measuring the complexity faced by an agent in individual decision-making problems.

• New Working Paper (PDF), July 2023.

With Junnan He.

Hotelling’s and Salop’s spatial competition models as well as nested logit, covariance probit, elimination-by-aspects, and several other well-known discrete choice models belong to the class of moderate utility models, where binary choices are a function of the ratio between utility difference and a product differentiation index satisfying the properties of a distance metric. We provide a behavioral foundation for this class of models. Our main result establishes that moderate utility has a single, directly testable implication: choice probabilities are moderately transitive. We use our characterization to show how the model achieves a useful compromise between explanatory power and predictive power.

• Working paper (PDF) updated July 2023.
• Accepted at the American Economic Review: Insights.

With Christopher Chambers, Yusufcan Masatlioglu and Collin Raymond.

We introduce a new model of stochastic choice. The model modifies the Luce model by adding one additional parameter reflecting salience or other economic frictions involved in choice. The model is consistent with many classical approaches, including random utility as well as preference maximization as in Machina, 1985. We characterize our model behaviorally and investigate its comparative statics properties. The model generates intuitive closed-form solutions in equilibrium settings where firms can choose price, quality, and advertising, is consistent with data that many typical discrete choice approaches cannot accommodate, and allows for simple preference parameter identification.

• Revise and Resubmit at the American Economic Review.
• New version coming soon.

With Faruk Gul, Erkut Ozbay, and Wolfgang Pesendorfer.

We report on an experiment that shows subjects prefer a gradual resolution of uncertainty when information about winning yields decisive bad news but inconclusive good news. This behavior is difficult to reconcile with existing theories of choice under uncertainty, including the Kreps-Porteus model. We show how the behavioral patterns uncovered by our experiment can be understood as arising from subjects’ special emphasis on their best (peak) and worst (trough) experiences along the realized path of uncertainty.

• Working paper (PDF) updated April 2022.

Lea and Ryan (Science, Reports, 28 August 2015, p. 964) interpret mate choice data collected from frogs in the laboratory as being incompatible with rational choice models currently used in sexual selection theory. A close look at their data supports the hypothesis that some options offered in the lab are easier to compare than others. If we take into account that some pairs of options are easier to compare, and that frogs operate under conditions of uncertainty, we can restore rationality to túngara frogs.

• This working paper is superseded by Random Choice and Learning (see publications, above).
• Non-technical summary (PDF) updated September 2015.
• Slides (PDF) updated September 2016.
• Podcast interview by Claire Gauen in Hold That Thought.