Latest Research Publications

This paper studies the impact of the US-China tariff war on China, using high-frequency night lights data and grid-level measures of tariff exposure. Exploiting within-grid variation over time and controlling extensively for grid-specific contemporaneous trends, we find that each one-percentage-point increase in exposure to the US tariffs was associated with a 0.59% reduction in night-time luminosity. This impact was highly skewed across locations: Grids with negligible direct exposure to the US tariffs accounted for 70% of China’s population. But the tail 2.5% of China’s population with the highest exposure saw an implied 2.52% (1.62%) decrease in income per capita (employment) relative to unaffected grids. These effects were moreover concentrated in locations with a high commuting openness. By contrast, we do not find significant effects from China’s retaliatory tariffs, and offer evidence of several channels through which the impact on imported inputs was mitigated. In a parallel analysis at the prefecture level, we confirm that the US tariffs had discernible negative aggregate consequences.

Using firm-level earnings forecasts and managerial guidance data, we construct guidance surprises for analysts, i.e., differences between managerial guidance and analysts' initial forecasts. We document new evidence on expectation formation: (i) analysts overreact to managerial guidance and the overreaction is state-dependent, i.e., it is stronger for negative guidance surprises but weaker for surprises that are larger in size; and (ii) forecast revisions are neither symmetric in guidance surprises nor monotonic. We organize these facts with a model where analysts are uncertain about the quality of managerial guidance. We show that a reasonable degree of ambiguity aversion is necessary to account for the documented heterogeneous overreaction pattern.

Many consumers are caregivers and, as part of caregiving, frequently make food choices for their dependents. This research examines how food choices made for children influence the healthiness of parents’ subsequent self-choices. Whereas prior work focuses on choices for the self (others) as based on self-needs (other-needs), the authors theorize when and why self-choices involve consideration of other-needs. Five studies, including a nursery school field study, test the effect of choosing healthy food for a child on the healthiness of parents’ self-choices, focusing on the role of anticipating potentially sharing self-choices with one's child. Potential sharing increased parents’ likelihood of making an unhealthy subsequent self-choice if they first made a healthy choice for their child. This effect was driven by parents’ present-focused parenting concerns about whether one's child would eat and enjoy healthy options chosen for them. This effect was mitigated when parents instead had future-focused parenting concerns. Additionally, this effect was mitigated after making an initial choice for the child that was (1) unhealthy or (2) healthy but relatively liked by the child. This research contributes to understanding how choices for others shape choices for the self and offers important marketing and policy implications.

The current research examines the relationship between crowding and consumers’ responsiveness to sales promotions. Six studies show that the experience and feeling of crowdedness reduce the impact of sales promotions, demonstrating that consumers’ product/service purchase intention changes to a lesser extent in response to such promotions. This effect is found to be driven by consumers shifting their attention from the external environment to their internal feelings and thoughts when experiencing crowdedness. As a result, consumers rely more on their internal feelings and thoughts than on external cues in judgment, and consequently their purchase intention becomes less susceptible to external sales promotion information. In addition, this effect is found to be attenuated in situations where product attitudes are detached from consumers’ own preferences, such as in the context of gift choices, and when the experience of crowding is not aversive (e.g., watching an exciting football game in a bar).

This paper studies the unintended effect of English language requirement on educational inequality by investigating how the staggered rollout of English listening tests in China’s high-stakes National College Entrance Exam (NCEE) affected the rural–urban gap in college access. Leveraging administrative data covering the universe of NCEE participants between 1999 and 2003, we find that the introduction of English listening tests significantly lowered rural students’ exam score percentile ranks relative to their urban counterparts, resulting in a 30% increase in the rural–urban gap in college access. Our back-of-the-envelope calculations suggest that, as a result of this policy change, more than 54,000 rural students lost college seats to their urban peers between 1999 and 2003, and another 11,000 rural students who elite colleges could have admitted ended up in non-elite colleges, causing them significant future income losses.

This paper explores the effects of public information such as accounting earnings in a competitive lending setting with risk shifting. Debt financing creates incentives for borrowers to take on excessive risks, in particular in bad states of the world. If a privately informed inside creditor bids against outside creditors to extend a loan, public information levels the playing field, which affects the bidding and risk shifting. Nonetheless, a perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting outside creditors to the winner’s curse, allowing borrowers in bad states cheaper access to loans. However, for pessimistic priors about the borrower, greater public signal precision can alleviate risk shifting, at the margin. We discuss implications for financial reporting regulations along the business cycle and for creditor turnover.

In 2013, the U.S. Consumer Financial Protection Bureau released a database of consumer complaints filed against banks under its supervision (“CFPB banks”). We find that after the disclosure, rival banks exhibit a greater increase in mortgage approval rates in markets with more intensive mortgage complaints about CFPB banks. The effect is weaker when rivals have more expertise in the local market, are less concerned about credit risk due to mortgage sales, and locate in areas with more alternative information about the CFPB banks. The effect is concentrated in severe complaints and complaints related to loan underwriting practices. In addition to approving more loans, rivals also open more branches and are more likely to post a job opening in these markets. The findings suggest that these banks learn from the nonfinancial disclosures about operational deficiencies of peers (i.e., CFPB banks) in local markets, which alleviates their adverse selection concern about expanding.

We introduce a novel stakeholder-oriented framework that highlights variance in the application and expression of gender bias in the upper echelons. Directed by their relationship with the firm’s leadership, we theorize that stakeholders’ appraisals of top female leaders map onto a categorical and complex continuum. At the “categorical” end of this continuum, stakeholders neither have access nor are attentive to capability cues from the leader, increasing their reliance on stereotypes and gender biases in their leader evaluations. At the “complex” end of the continuum, stakeholders have access and are attentive to capability cues from the leader, decreasing their reliance on stereotypes and increasing their ability to accurately evaluate the leader. Between these ends, stakeholders evaluate female leaders by applying stereotypes and striving for accuracy to varying degrees. Each region on this continuum is linked to an array of behavioral responses, directed by stakeholders toward a target leader, that differ in valence and intensity. Our framework has significant implications for understanding a variety of social biases beyond gender, and enables the development of tailored strategies that can be used to facilitate accurate leader evaluations by all stakeholders.

Disputes over transactions on two-sided platforms are common and usually arbitrated through platforms’ customer service departments or third-party service providers. This paper studies crowd-judging, a novel crowdsourcing mechanism whereby users (buyers and sellers) volunteer as jurors to decide disputes arising from the platform. Using a rich data set from the dispute resolution center at Taobao, a leading Chinese e-commerce platform, we aim to understand this innovation and propose and analyze potential operational improvements with a focus on in-group bias (buyer jurors favor the buyer, likewise for sellers). Platform users, especially sellers, share the perception that in-group bias is prevalent and systematically sways case outcomes as the majority of users on such platforms are buyers, undermining the legitimacy of crowd-judging. Our empirical findings suggest that such concern is not completely unfounded: on average, a seller juror is approximately 10% likelier (than a buyer juror) to vote for a seller. Such bias is aggravated among cases that are decided by a thin margin and when jurors perceive that their in-group’s interests are threatened. However, the bias diminishes as jurors gain experience: a user’s bias reduces by nearly 95% as experience grows from zero to the sample median level. Incorporating these findings and juror participation dynamics in a simulation study, the paper delivers three managerial insights. First, under the existing voting policy, in-group bias influences the outcomes of no more than 2% of cases. Second, simply increasing crowd size through either a larger case panel or aggressively recruiting new jurors may not be efficient in reducing the adverse effect of in-group bias. Finally, policies that allocate cases dynamically could simultaneously mitigate the impact of in-group bias and nurture a more sustainable juror pool.