Identifying Dynamic Discrete Choice Models with Hyperbolic Discounting

Taiga Tsubota

Papers from arXiv.org

Abstract: We study identification of dynamic discrete choice models with hyperbolic discounting. We show that the standard discount factor, present bias factor, and instantaneous utility functions for the sophisticated agent are point-identified from observed conditional choice probabilities and transition probabilities in a finite horizon model. The main idea to achieve identification is to exploit variation in the observed conditional choice probabilities over time. We present the estimation method and demonstrate a good performance of the estimator by simulation.

Date: 2021-11, Revised 2024-10
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-upt
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