Publications

Reading disabilities affect 10%–20% of students in the US. Untreated students fall behind their typically developing peers, leading to poor long-term outcomes. While instructional interventions can help, they are most effective when implemented early. Inexpensive screening tests can be used to monitor and flag at-risk students who may need expensive follow-up diagnostic evaluations that determine eligibility for intervention. However, conventional wisdom holds that the accuracy of these tests increase with grade level. Schools that do not have the capacity to do follow-up evaluations on every student flagged by screening are therefore believed to face an operational trade-off in allocating resources for evaluations, balancing the need for early intervention against budget constraints and legal obligations to honor direct parent or teacher requests. We examine how school administrators can choose evaluation policies to maximize benefits from intervention for students and ensure equitable allocation across diverse backgrounds. We model identification by optimizing over a time-dependent Bernoulli process which incorporates the screening test accuracy and the benefits from intervention at different grade levels. In collaboration with researchers from the Florida Center for Reading Research, we use longitudinal data from school districts across the state to empirically estimate these parameters and numerically solve for the optimal policies. Our study provides actionable insights for school administrators making resource allocation decisions and policy makers considering changes to laws governing the identification process. In this context, counter to conventional wisdom the screening test accuracy does not increase with grade level. To maximize the benefit to students under the current identification process, schools should simply evaluate as many students as their budget allows as early as possible. At existing budget levels, this policy also results in maximally equitable allocations. Changes to the identification process that ease legal obligations can increase benefits by up to 66% and decrease disparities by up to 100% without additional funding.

Persuasive communication functions not only through content but also delivery, e.g., facial expression, tone of voice, and diction. This paper examines the persuasiveness of delivery in start-up pitches. Using machine learning (ML) algorithms to process full pitch videos, we quantify persuasion in visual, vocal, and verbal dimensions. Positive (i.e., passionate, warm) pitches increase funding probability. Yet conditional on funding, high-positivity startups underperform. Women are more heavily judged on delivery when evaluating single-gender teams, but they are neglected when co-pitching with men in mixed-gender teams. Using an experiment, we show persuasion delivery works mainly through leading investors to form inaccurate beliefs.

We investigate the role of private equity (PE) in the resolution of failed banks after the 2008
financial crisis. Using proprietary failed bank acquisition data from the FDIC combined with data
on PE investors, we find that PE investors made substantial investments in underperforming and
riskier failed banks. Further, these acquisitions tended to be in geographies where the other local
banks were also distressed. Our results suggest that PE investors helped channel capital to
underperforming failed banks when the “natural” potential bank acquirers were themselves
constrained, filling the gap created by a weak, undercapitalized banking sector. Next, we use a
quasi-random empirical design based on proprietary bidding data to examine ex post performance
and real effects. We find that PE-acquired banks performed better ex post, with positive real effects
for the local economy. Our results suggest that private equity investors had a positive role in
stabilizing the financial system in the crisis through their involvement in failed bank resolution.

Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling influences consumer choice in e-commerce settings even when there is no face-to-face interaction. In this paper, we use a longitudinal Airbnb dataset and a facial attribute classifier to quantify the effect of a smile in the host's profile photo on property demand and identify factors that influence when a host's smile is likely to have the biggest effect. A smile in the host's profile photo increases property demand by 3.5% on average. This effect is moderated by a variety of host and property characteristics that provide evidence for the role of uncertainty underlying why smiling increases demand. Specifically, when there is greater uncertainty regarding either the quality of the accommodations or the interaction with the host, a host smile will have a greater effect on demand. Online experiments confirm this pattern, offering further support for uncertainty perceptions driving the effect of smiling on increased Airbnb demand, and show that the effect of smiling on demand generalizes beyond Airbnb.

We study an advertiser’s targeting strategy and its effects on consumer data privacy choices, both of which determine the advertiser’s targeting accuracy. Targeted ads, serving as implicit recommendations when consumer preferences are uncertain, not only influence the consumer’s beliefs and purchasing decisions but also amplify the advertiser’s temptation towards strategic mistargeting—sending ads to poorly matched consumers. Our analysis reveals that advertisers may, paradoxically, choose less precise targeting as accuracy improves. Even if prediction is perfect, the advertiser still targets the wrong consumers, leading to strategic mistargeting. Nev- ertheless, consumer surplus can remain positive due to improved identification of well-matched consumers, thereby reducing the incentive for consumers to withhold information. However, the scenario shifts with endogenous pricing; better prediction leads to more precise targeting, although mistargeting persists. To exploit the recommendation effect of advertising, the ad- vertiser raises prices instead of diluting recommendation power, lowering consumer welfare and prompting consumers to opt out of data collection. Furthermore, we investigate the impact of consumer data opt-out decisions under varying privacy policy defaults (opt-in vs. opt-out). These decisions significantly affect equilibrium outcomes, influencing both the advertiser’s tar- geting strategies and consumer welfare. Our findings highlight the complex relationship between targeting accuracy, privacy choices, and advertisers’ incentives

Migration and pollution are two defining features of China's impressive growth performance over the last 30 years. In this paper we study the migration response to pollution in Chinese cities, and its consequences for productivity and welfare. We document a robust pattern in which skilled workers emigrate more in response to pollution than the unskilled. Their greater sensitivity to air quality holds up in cross-sectional variation across cities, panel variation with individual fixed-effects, and when instrumenting for pollution using distant power-plants upwind of cities, or thermal inversions that trap pollution. Pollution therefore changes the spatial distribution of skilled and unskilled workers, which results in higher returns to skill in cities that the educated migrate away from. We quantify the loss in aggregate productivity due to this re-sorting by estimating a model of demand and supply of skilled and unskilled workers across Chinese cities. Counterfactual simulations from the estimated model show that reducing pollution would increase productivity through spatial re-sorting by approximately as much as the direct health benefits of clean air. Physical and institutional restrictions on mobility exacerbate welfare losses. People's dislike of pollution explains a substantial portion of the wage gap between cities.

Europe can improve its innovation systems, but should not try to copy the US approach

This paper studies the optimal bundling of products with nonadditive values. Under monotonic preferences and single-peaked profits, I show that a monopolist finds pure bundling optimal if and only if the optimal sales volume for the grand bundle is larger than the optimal sales volume for any smaller bundle. I then detail how my analysis relates to ratio monotonicity results on bundling and describe the implications for nonlinear pricing.

We investigate a firm’s optimal product portfolio design on a Hotelling line that can affect consumers’ search decisions. Consumers form their perceptions of a brand from interactions with all products in the portfolio. We conceptualize the average location of the products as the brand position that represents the aggregate information about characteris- tics common to the product portfolio. Then, we propose a mechanism for why and how brand positioning induced by a firm’s product portfolio design can deliver credible infor- mation that guides consumer search. We show that niche positioning naturally conveys more information than mainstream positioning. A mainstream brand has incentives to opportunistically dilute its brand by offering a wide range of products. Even in a monopo- listic market, a niche brand positioning may arise as an equilibrium because it serves as a commitment device that prevents brand dilution

We propose a model of how multiple societies respond to a common crisis. A gov- ernment faces a “damned-either-way” policymaking dilemma: aggressive intervention contains the crisis, but the resulting good outcome makes people skeptical about the costly response; light intervention worsens the crisis and causes the government to be faulted for not doing enough. When multiple societies encounter the crisis sequentially, due to this policymaking dilemma, late societies may underperform despite having more information, while early societies can benefit from a dynamic counterfactual effect.

We study optimal monetary policy during temporary supply contractions when aggregate demand has inertia and the central bank is concerned about future constraints on expansionary policy. In this environment, it is optimal to run the economy hot until supply recovers. However, the policy does not remain loose throughout the low-supply phase. Overall, when the initial aggregate demand is low, the goal is to frontload the rate cuts to raise demand in anticipation of the recovery of supply. If inflation also has inertia, the central bank still overheats the economy during the low-supply phase but gradually cools it down over time.

While promotive voice is conventionally considered a favourable work behaviour to the organisation, whether engaging in promotive voice will help employees move up the career ladder is inconclusive across a handful of studies. Drawing on a psychological contract perspective, this study aims to understand why and when employees' promotive voice can contribute to supervisor‐rated employees' promotability. We propose that employees' engagement in promotive voice will strengthen supervisor‐sponsored balanced psychological contract with the employees and thus employees' promotability, and these effects will be stronger when the employees and supervisors have higher versus lower quality of leader‐member exchange (LMX) relationship. Results of a three‐wave field study with 281 employees and their 59 supervisors supported our hypotheses. We conclude by discussing the important implications of these findings for theory and practice.

We derive a new formula for the optimal uniform tariff in a small-country, heterogeneous-firm
model with a traded and a nontraded sector, and with roundabout production in both. Tariffs
are applied on the imported differentiated inputs in the traded sector, which are bundled with
domestic inputs to produce a nontraded finished good. First-best policy requires that markups
on domestic intermediate inputs are offset by subsidies. We compare the optimal second-best
tariff – when such subsidies are not used – to the first-best tariff from a one-sector, no roundabout
model. Under a wide range of parameter values the second-best import tariff is lower. In a 186-
country, 15-sector quantitative version of our model, the optimal uniform tariff has a median
value of 10% (7.5% for countries with above-median shares of manufacturing production), and
it is negative for five countries.

Ad targeting technology has enabled a highly personalized delivery of online ads. Behind this development is the belief that better targeting will lead to more relevant ads. This paper challenges this lay belief by showing that irrelevant advertising can arise not necessarily from technological imperfection but also from the incentive problem embedded in the ad agency-advertisers relationship. We first demonstrate that the ad agency serving multiple advertisers may strategically allocate an ad impression to a lesser-matched, sometimes totally irrelevant, niche advertiser because future impressions can match better with the mainstream advertiser. We further find that, without a contractual obligation to serve both advertisers, the agency may not deliver completely irrelevant ads to consumers. However, another type of inefficiency can arise where the agency may not send any ad to potentially interested consum- ers who have a strictly positive match probability with advertisers. These inefficiencies arise due to contractual restrictions, either contractual obligations or budget constraints, when the agency serves multiple advertisers. As such, we endogenize the advertisers’ contractual requirement choices and show how the contractual obligation(s) can arise in equilibrium. Finally, we show that irrelevant ads will not disappear simply because more impressions are available in the market. Our analysis suggests that as the number of impressions increases, the irrelevant ads can persist, but the probability of receiving irrelevant ads decreases.

Motivated by a collaboration with the San Francisco Unified School District (SFUSD), this paper presents an interactive optimization framework for addressing complex public policy problems. These problems suffer from a chicken-and-egg dilemma, where policymakers understand the objectives and constraints but lack the ability to solve them (“the optimization problem”), while researchers possess the necessary algorithms but lack the necessary insights into the policy context (“the policy problem”). Our framework addresses this challenge by combining three key elements: (1) an efficient optimization algorithm that can solve the problem given certain known objectives, (2) a method for generating a large set of diverse, near-optimal solutions, and (3) an interface that facilitates exploration of the solution space. We illustrate the effectiveness of this framework by applying it to the problem of improving school schedules at SFUSD. The resulting schedule, implemented in August 2021, saved the district over $5 million and, to our knowledge, represents the first successful optimization-driven school start time change in the United States.

While breastfeeding is recognized as providing optimal nutrition for infants and toddlers, maternal employment is a commonly mentioned barrier to breastfeeding. The goal was to (a) identify key actors participating in the design and implementation of workplace breastfeeding interventions in Mexico, (b) understand the complexity of interactions between the actors, and (c) map the connections and influence between the actors when looking into networks of Advice, Command, Funding, and Information.

Past research has found that employees who view themselves as overqualified for their jobs tend to hold negative job attitudes and be unwilling to go beyond the call of duty. In challenging situations such as during the COVID-19 crisis, when having “all hands-on deck” may be important to an organization’s survival, mitigating the negative tendencies of these employees becomes important. Adopting a sensemaking perspective on crisis management, we examine whether supervisors’ self-sacrificial leadership can mitigate these negative tendencies. First, we propose that employee perceived overqualification is associated with lower levels of felt obligation to the organization and thereby lower levels of extra-role behaviors (i.e., helping and proactivity). We next propose that supervisors’ self-sacrificial leadership during the COVID-19 crisis can evoke, especially when COVID-19 more strongly impacts the organization, a sense of collectivism toward the organization, which mitigates the negative association of perceived overqualification with felt obligation and thus extra-role behaviors. We tested our theorizing in samples from the UK (n = 121, Pilot Study) and US (n = 382, Main Study) in studies with a multi-wave, time-lagged design. Findings from both studies provide support for our theorizing. We discuss implications for research and practice concerning perceived overqualification during a crisis.

Low-income and Black households are less likely to visit bank branches than high-income and White households, despite the former two groups appearing to rely more on branches as means of bank participation. We assess whether unequal branch access can explain that disparity. We propose a measure of bank branch access based on a gravity model of consumer trips to bank branches, estimated using mobile device geolocation data. Residents have better branch access if branches are closer or have superior qualities that attract more visitors. Because the geolocation data is distorted to protect user privacy, we estimate the gravity model with a new econometric method that adapts the Method of Simulated Moments to handle high-dimensional fixed effects. We find no evidence that low-income communities lack access to bank branches and instead find that lower demand for bank branch products or services explains their lower branch use. But in Black communities, worse access explains their entire drop-off in branch use. For residents of these areas, weaker access is not from having lower quality branches, but from branches being located farther away from them. The results highlight parts of the country that would benefit the most from policies that expand access to banking.