Dynamic Decisions Under Subjective Expectations: A Structural Analysis

CAEPR WORKING PAPER 2018-001

55 Pages Posted: 22 Feb 2018

See all articles by Yonghong An

Yonghong An

Texas A&M University

Yingyao Hu

Johns Hopkins University - Department of Economics

Ruli Xiao

Indiana University

Date Written: January 2018

Abstract

his paper studies dynamic discrete choices by relaxing the assumption of rational expectations. That is, agents’ subjective expectations about the state transition are unknown and allowed to differ from their objectively estimable counterparts. We show that agents’ subjective expectations and preferences can be identified and estimated from the observed conditional choice probabilities in both finite and infinite horizon cases. Our identification of subjective expectations is nonparametric and can be expressed as a closed-form function of the observed conditional choice prob-abilities. We estimate the model primitives using maximum likelihood estimation and illustrate the good performance of estimators using Monte Carlo experiments. We apply our model to Panel Study of Income Dynamics (PSID) data and analyze women’s labor participation. We find systematic differences between agents’ subjective expectations about their income transition from those under rational expectations. A counterfactual analysis suggests that women with low and medium incomes would increase the probability of working under rational expectations, and that the probability would decrease for women with high income.

Keywords: Dynamic discrete choice models, subjective expectations, rational expectations, nonparametric identification, estimation.

Suggested Citation

An, Yonghong and Hu, Yingyao and Xiao, Ruli, Dynamic Decisions Under Subjective Expectations: A Structural Analysis (January 2018). CAEPR WORKING PAPER 2018-001. Available at SSRN: https://ssrn.com/abstract=3122701 or http://dx.doi.org/10.2139/ssrn.3122701

Yonghong An (Contact Author)

Texas A&M University ( email )

3051 Allen Building
4428 TAMU
College Station, TX Texas 77843
United States

Yingyao Hu

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States

Ruli Xiao

Indiana University ( email )

100 S Woodlawn Ave
Bloomington, IN 47405
United States

HOME PAGE: http://https://sites.google.com/site/iueconomicsrulixiao/

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