arXiv subjects

Gerelt Tserenjigmid

Publications and source records attributed to Gerelt Tserenjigmid.

10 recordsLinked to original sources

arXiv2026

Learning from an Unknown DGP: Experimental Evidence on Belief Updating with AI Recommendations

We use a controlled experiment to study how beliefs are updated after receiving qualitative information (AI recommendations) from an unknown data-generating process (DGP). Across 60,252 pairs of prior and posterior beliefs, we document three behavioral patterns: updates close to zero when recommendations confirm extreme priors, larger updates when recommendations contradict extreme priors, and smaller updates for intermediate priors. These three behavioral patterns suggest four testable properties of belief updating, which we assess at the aggregate and individual levels. Finally, we examine how well updates are captured by three models of belief updating.

econ.GN↗

arXiv2026

Price Heterogeneity as a Source of Heterogeneous Demand

We explore heterogeneous prices as a source of heterogeneous or stochastic demand. Heterogeneous prices could arise either because there is actual price variation among consumers or because consumers (mis)perceive prices differently. Our main result says the following: if heterogeneous prices have a distribution among consumers that is (in a sense) stable across observations, then a model where consumers have a common utility function but face heterogeneous prices has precisely the same implications as a heterogeneous preference/random utility model (with no price heterogeneity).

econ.TH↗

arXiv2026

The Focal Quantal Response Equilibrium

We propose a generalization of Quantal Response Equilibrium (QRE) built on a simple premise: some actions are more focal than others. In our model, which we call the Focal Quantal Response Equilibrium (Focal QRE), each player plays a stochastic version of Nash equilibrium as in the QRE, but some strategies are focal and thus are chosen relatively more frequently than other strategies after accounting for expected utilities. The Focal QRE is able to systematically account for various forms of bounded rationality of players, especially regret-aversion, salience, or limited consideration. The Focal QRE is also useful for explaining the observed heterogeneity of bounded rationality of players across different games. We show that regret-based focal sets perform relatively well at predicting strategies that are chosen more frequently relative to their expected utilities.

econ.TH↗

arXiv2026

Robust Testing Of the Allais Paradox By Paired Choices vs. Paired Valuations

McGranaghan, Nielsen, O'Donoghue, Somerville, and Sprenger [2024] show that standard paired choice tests for the common ratio effect are structurally biased when choice is stochastic, proposing valuation tests as a robust alternative. Using valuation tests, they find no systematic evidence for the common ratio effect, seemingly overturning much of the extant literature. We evaluate this conclusion in light of stochastic choice theory. We argue that valuation tests are inherently biased and lack predictive power under standard expected utility assumptions. In contrast, we advocate for a ``strong'' paired choice test, proving it remains robustly unbiased across common models of stochastic choice. Applying this strong test to existing experimental data, we find that the common ratio effect remains highly prevalent.

econ.TH↗

arXiv2025

Inertial Updating with General Information

We study belief revision when information is represented by a set of probability distributions, or general information. General information extends the standard event notion while including qualitative information (A is more likely than B), interval information (A has a ten-to-twenty percent chance), and more. We behaviorally characterize Inertial Updating: the decision maker's posterior is of minimal subjective distance from her prior, given the information constraint. Further, we introduce and characterize a notion of Bayesian updating for general information and show that Bayesian agents may disagree. We also behaviorally characterize f-divergences, the class of distances consistent with Bayesian updating.

econ.TH↗

arXiv2023

Measuring Stochastic Rationality

Our goal is to develop a partial ordering method for comparing stochastic choice functions on the basis of their individual rationality. To this end, we assign to any stochastic choice function a one-parameter class of deterministic choice correspondences, and then check for the rationality (in the sense of revealed preference) of these correspondences for each parameter value. The resulting ordering detects violations of (stochastic) transitivity as well as inconsistencies between choices from nested menus. We obtain a parameter-free characterization and apply it to some popular stochastic choice models. We also provide empirical applications in terms of two well-known choice experiments.

econ.TH↗

arXiv2023

Revealed preferences for dynamically inconsistent models

We study the testable implications of models of dynamically inconsistent choices when planned choices are unobservable, and thus only "on path" data is available. First, we discuss the approach in Blow, Browning and Crawford (2021), who characterize first-order rationalizability of the model of quasi-hyperbolic discounting. We show that the first-order approach does not guarantee rationalizability by means of the quasi-hyperbolic model. This motivates consideration of an abstract model of intertemporal choice, under which we provide a characterization of different behavioral models -- including the naive and sophisticated paradigms of dynamically inconsistent choice.

econ.TH↗

arXiv2023

Inertial Updating

We introduce and characterize inertial updating of beliefs. Under inertial updating, a decision maker (DM) chooses a belief that minimizes the subjective distance between their prior belief and the set of beliefs consistent with the observed event. Importantly, by varying the subjective notion of distance, inertial updating provides a unifying framework that nests three different types of belief updating: (i) Bayesian updating, (ii) non-Bayesian updating rules, and (iii) updating rules for events with zero probability, including the conditional probability system (CPS) of Myerson (1986a,b). We demonstrate that our model is behaviorally equivalent to the Hypothesis Testing model (HT) of Ortoleva (2012), clarifying the connection between HT and CPS. We apply our model to a persuasion game.

econ.TH↗

arXiv2022

Ordered Surprises and Conditional Probability Systems

We study conditioning on null events, or surprises, and behaviorally characterize the Ordered Surprises (OS) representation of beliefs. For feasible events, our Decision Maker (DM) is Bayesian. For null events, our DM considers a hierarchy of beliefs until one is consistent with the surprise. The DM adopts this prior and applies Bayes' rule. Unlike Bayesian updating, OS is a complete updating rule: conditional beliefs are well-defined for any event. OS is (behaviorally) equivalent to the Conditional Probability System (Myerson, 1986b) and is a special case of Hypothesis Testing (Ortoleva, 2012), clarifying the relationships between the various approaches to null events.

econ.TH↗

arXiv2022

Behavioral Foundations of Nested Stochastic Choice and Nested Logit

We provide the first behavioral characterization of nested logit, a foundational and widely applied discrete choice model, through the introduction of a non-parametric version of nested logit that we call Nested Stochastic Choice (NSC). NSC is characterized by a single axiom that weakens Independence of Irrelevant Alternatives based on revealed similarity to allow for the similarity effect. Nested logit is characterized by an additional menu-independence axiom. Our axiomatic characterization leads to a practical, data-driven algorithm that identifies the true nest structure from choice data. We also discuss limitations of generalizing nested logit by studying the testable implications of cross-nested logit.

econ.TH↗