Yucheng Liang

Stanford University
Graduate School of Business
655 Knight Way
Stanford, CA 94305
650-391-3306
ycliang@stanford.edu

I will join briq (Bonn) as a post-doc researcher in 2020 and Carnegie Mellon University as an assistant professor in 2021.

This website will no longer be updated. Please visit my new website.


Curriculum Vitae

Fields:
Behavioral Economics, Experimental Economics, Theory

Education:
Stanford Graduate School of Business
Ph.D. in Economics (2020, expected)

Peking University
B.A. in Economics and B.S. in Applied Mathematics (2015)

References:
B. Douglas Bernheim:
bernheim@stanford.edu

Muriel Niederle:
niederle@stanford.edu

Michael Ostrovsky:
ostrovsky@stanford.edu

Charles Lee:
clee8@stanford.edu

Working Papers

Learning from Unknown Information Sources [paper with online appendices][experimental instructions]

When an agent receives information generated by a source whose accuracy might either be high or low, standard economic theory dictates that she update as if the source has medium accuracy. In a lab experiment, I find that subjects' updating behaviors deviate from this benchmark. First, subjects under-react to information when the source is uncertain. Second, the under-reaction is more pronounced for good news than for bad news. These two patterns, under-reaction and pessimism, are consistent with a theory of belief updating where agents are insensitive and averse to compound uncertainty and ambiguity. I also find that subjects' reactions to information with uncertain accuracy are uncorrelated with their evaluations of bets with uncertain odds. This suggests that people have distinct attitudes toward uncertainty in information accuracy and uncertainty in economic fundamentals. The experimental results are validated using observational data on stock price reactions to analyst earnings forecasts, where analysts with no forecast records are classified as uncertain information sources.e distinct attitudes toward uncertainty in fundamentals and uncertainty in information accuracy.

Information-Dependent Expected Utility

In decision problems under uncertainty, the subjective evaluation of an outcome can depend on the information content of its realization. To accommodate this dependence, we introduce and axiomatize a model of information-dependent expected utility by allowing the utility of an outcome to flexibly depend on its information content in an (Anscombe-Aumann) act. Subjective beliefs are identified in a special class of our model where the utility of an outcome can be decomposed as the sum of consumption utility and information utility. Our model allows for both information seeking and information averse preferences, as well as a comparative theory of information preferences. For information seeking preferences, we introduce a Hidden Acts representation where the value of information is as if induced from the expected utility of the optimal choice in a fictitious future decision problem given that information.


Work-in-Progress

Social Comparison, Employee Attrition and Productivity: A Workplace Experiment (with Shannon X. Liu and Hugh Xiaolong Wu) [Status: fieldwork completed]

How should firms shape the social comparison process in the workplace to improve employee productivity and to reduce turnover? We conduct a 7-month field experiment in a multi-national spa chain with 160 stores and 5000 spa workers in China. We provide spa workers with bi-weekly messages on either the current performance of a co-worker with similar work experience (T1) or the performance trajectory of a senior co-worker (T2). First, we study how workers' outlook about their future performances and reference points for performance comparison depend on their knowledge about their co-workers' current and past performance. Second, we measure the effects of information treatments on the workers' beliefs about their own future productivity, reference points, stress levels, productivity, attrition, and pro-social behaviors.
[AEA RCT Registration]

Truth-Telling and the Design of Flexible Commitment Contracts: A Field Experiment (with Shengmao Cao and Tony Fan) [Status: pilot completed]

We propose a novel commitment contract (CC) with exemption clauses to provide incentives for physical exercise while retaining flexibility. Like a traditional, rigid CC, some money is deposited into an account (by the participant or by a third party) and the participant is allowed to withdraw the money if she attends the gym. Unlike a rigid CC, if a participant reports that she did not go to the gym because of illnesses, injuries, unanticipated obligations, or other pre-specified conditions, she is allowed to withdraw the deposit as well. The participants' reports are not verified, so the effectiveness of such a CC depends on the participants' aversion to lying. We conduct a field experiment at the Stanford athletic facilities to evaluate the demand for and the effectiveness of a CC with exemptions, in comparison to a rigid CC and a control contract without incentives.


Over-Detection of Causal Patterns (with Collin Raymond)