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Events

Home Events
Constrained Data-Fitters
Constrained Data-Fitters
Constrained Data-Fitters
Constrained Data-Fitters
Constrained Data-Fitters
13Dec
Economics

Constrained Data-Fitters

13 December 2024 | 11:30 AM - 12:15 PM
KK1119, 11/F, K. K. Leung Building, HKU
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Speaker:
Jakub Steiner

Professor
Department of Economics
University of Zurich

Abstract:

We study maximum-likelihood estimation and updating, subject to computational, cognitive, or behavioral constraints. We jointly characterize constrained estimates and updating within a framework reminiscent of a machine learning algorithm. Without frictions, the framework simplifies to standard maximum-likelihood estimation and Bayesian updating. Our central finding is that under certain intuitive cognitive constraints, simple models yield the most effective constrained fit to data—more complex models offer a superior fit, but the agent may lack the capability to assess this fit accurately. With some additional structure, the agent’s problem is isomorphic to a familiar rational inattention problem.

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Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
18Jun
Economics | Seminar
Semiparametric Identification of the Discount Factor and Payoff Function in Dynamic Discrete Choice Models
18 June 2025 | 2:15 PM - 3:30 PM
KK 910 K. K. Leung Building, HKU
Prof. Katsumi Shimotsu
Constrained Data-Fitters
About Speaker
Jakub Steiner

Professor, Department of Economics, University of Zurich

Constrained Data-Fitters
13 December 202411:30 AM - 12:15 PM
KK1119, 11/F, K. K. Leung Building, HKU
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