Yutaro AKITA

Bio

Ph.D. student in Economics at Penn State

ytrakita (at) gmail (dot) com

Fields: Decision theory · Microeconomic theory

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Working papers

Randomization and ambiguity perception

w/ Kensei Nakamura | September 2025

We provide a model of preferences over lotteries of acts in which a decision maker behaves as if optimally filtering her ambiguity perception. She has a set of plausible ambiguity perceptions and a cost function over them, and chooses multiple priors to maximize the minimum expected utility minus the cost. We characterize the model by axioms on attitude toward randomization and its timing, uniquely identify the filtering cost from observable data, and conduct several comparatives. Our model can explain Machina's (2009) two paradoxes, which are incompatible with many standard ambiguity models.

PDF BIB DOI
```
@unpublished{AkitaNakamura2025,
  author = {Akita, Yutaro and Nakamura, Kensei},
  doi = {10.48550/arxiv.2509.05076},
  note = {arXiv:2509.05076},
  title = {Randomization and Ambiguity Perception},
  year = {2025},
}
```

A simple proof of the representation theorem for betweenness preferences

January 2025

This paper presents a simple proof of Dekel's (1986) representation theorem for betweenness preferences. The proof is based on the separation theorem.

PDF BIB DOI

@unpublished{Akita2025,
  author = {Akita, Yutaro},
  doi = {10.48550/arxiv.2405.11371},
  note = {arXiv:2405.11371},
  title = {A Simple Proof of the Representation Theorem for Betweenness Preferences},
  year = {2025},
}

Work in progress

Experiments, decision rules, and costly information acquisition

This paper examines the behavioral implications of costly information acquisition on information acquisition problems. The primitive of my model is a preference relation over pairs of a decision rule and an experiment, which I call strategies. I develop axiomatic foundations for a model of costly information acquisition by a Bayesian decision maker. She chooses strategies as if balancing the benefit and cost of information. I also characterize the special cases of the costly information acquisition model where (i) the payoff and the cost are additively separable; (ii) the payoff and the cost are additively separable and the cost is posterior separable.
Bayesian representations of preferences over experiments

This paper examines the behavioral implications of Bayesian decision making on the choice of information. I develop axiomatic foundations for a model of information choice by a Bayesian decision maker. She behaves as if maximizing the expected payoff given a decision problem and a prior belief. I characterize the class of preferences over information structures that can be rationalized by the Bayesian framework. I also discuss how much the parameters of the model can be identified from the preference and how to elicit them through choice data.