Published

Blame and Praise: Responsibility Attribution Patterns in Decision Chains

with Urs Fischbacher, Jan Hausfeld and Regina Stumpf

How do people attribute responsibility when an outcome is not caused by a single person but results from a decision chain involving several people? We study this question in an experiment, in which five voters sequentially decide on how to distribute money between them and five recipients. The recipients can reward or punish each voter, which measures responsibility attribution. In the aggregate, we find that responsibility is attributed mostly according to the voters’ choices and the pivotality of the decision, but not for being the initial voter. On the individual level, we find substantial heterogeneity with three overall patterns: Little to no responsibility attribution, pivotality-driven, and focus on choices. These patterns are similar when praising voters for good outcomes and blaming voters for bad outcomes.

Experimental Economics | published paper

Work in Progress

Does Inequality of Opportunity Affect Discrimination? Experimental Evidence from India

with Ankush Asri and Urs Fischbacher 

We study caste-based discrimination and belief updating using a lab experiment in India. We introduce inequality of opportunity by exogenously varying the degree of advantage in a previously performed task. We test whether providing information about an advantage affects the likelihood of hiring potential employees and whether employers update their beliefs over time. In aggregate, we find no discrimination, regardless of the information provided. However, a detailed analysis shows that when informed about the advantages, all employers initially favor employees from their own caste. Over time, they update their beliefs about the true ability distribution, leading to statistical discrimination in favor of upper-caste employees.

Under review | working paper

Task Assignment at the Workplace: Does Gender Matter?

Through a lab experiment, this paper investigates how employers allocate challenging and routine tasks among employees and whether gender discrimination exists in task assign- ment within organizations. In addition, the experimental design enables the examination of gender stereotypes not only in a static context but also in a dynamic setting where learning and task allocation interact. As experience in performing challenging tasks is considered crucial for career advancement, I analyze employers’ promotion decisions under three treat- ments that vary the information available to them. I find that, in aggregate, male employers display in-group bias by assigning fewer challenging tasks to females, while female employers have a positive but insignificant effect on assignment of challenging tasks to females. Over time, employers learn about the abilities of workers and their task assignment decisions are significantly shaped by their experience gained during the course of the experiment. Employers accurately integrate the information provided to them in their promotion decisions, but in the treatment where they observe only the number of challenging tasks assigned to workers, male employers exhibit a preference for promoting male workers over female workers. The results reiterate the need and importance of unbiased assignment of challenging tasks at the workplace and highlight the potential long-term impact on career advancement.

Draft available on request

Diversity in Teams: Theory & Experiment 

with Doruk Cetemen and Fabio Tufano

Social Image Concerns & AI Adoption

with Mert Gumren

How do you pay? Exploring the link between payment modes and food choices