高等经济研究院教师论文被国际权威经济学期刊接收发表

2025年08月04日

近日，东北财经大学高等经济研究院王超助理教授与Keystone AI 高级经济学者（Senior Economist）Stefan Weiergraeber 、印第安纳大学经济系肖如丽副教授合作的论文 “Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action” 被国际权威期刊 Journal of Business & Economic Statistics 接收并正式线上发表。

该论文研究使用终止行为以识别具有双曲贴现的动态离散选择模型。在当期效用函数稳定的假设下，作者提供了在有限期模型中关于sophisticated 和 naive 决策者的折现因子的识别结果。与现有文献的识别策略相比，该研究不需要观察 sophisticated 决策者在最后一期的决策。此外，对于 sophisticated和 naive 决策者，该研究无需将参考行为的当期效用函数进行归一化处理。作者提出了两种简单估计并证明它们在模拟中表现良好。

 

Assistant Professor Chao Wang's Paper Accepted for Publication in Journal of Business & Economic Statistics

August 4, 2025 

Chao Wang, Assistant Professor of IAER, had his paper accepted for publication in Journal of Business & Economic Statistics recently. Entitled "Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action", the paper was co-authored with Stefan Weiergraeber, Senior Economist of Keystone AI and Ruli Xiao, Associate Professor of Economics at Indiana University.

 

We study the identification of dynamic discrete choice models with hyperbolic discounting using a terminating action. We provide novel identification results for both sophisticated and naive agents' discount factors and their utilities in a finite horizon framework under the assumption of a stationary flow utility. In contrast to existing identification strategies we do not require to observe the final period for the sophisticated agent. Moreover, we avoid normalizing the flow utility of a reference action for both the sophisticated and the naive agent. We propose two simple estimators: one that estimates the two discount factors without specifying the flow utilities, and another that jointly estimates both the discount factors and the flow utilities. We show that both estimators perform well in simulations.