Publications

We study how global changes in information acquisition costs through disclosure technologies affect price informativeness. To provide evidence on this issue, we examine worldwide adoptions of centralized electronic disclosure systems, which significantly reduce the cost of and broaden access to financial disclosures. Consistent with extant theory, we show a significant reduction in private information acquisition around earnings announcements as a result of these adoptions. These effects are most pronounced in countries with the most substantial reductions in information acquisition costs and where we find more significant decreases in informed trade. Overall, we highlight an important, unintended cost of broadening access to financial disclosures through technology adoptions.

Emergency Department (ED) crowding is recognized as a national crisis. Load-leveling is the process of transferring patients between campuses in the same hospital system for admission to redistribute patient capacity. Our study evaluates the impact of this load-leveling on ED throughput from the transferred patient perspective and on ED operations to evaluate operational benefits and drawbacks.

This paper examines which municipal disclosures provide informational value to investors. Using the entire universe of post-issuance financial and event disclosures from 2009 to 2022, we find that most municipal bonds do not trade in the weeks following a disclosure. However, some disclosures do provide enough new information to increase trading. Investors trade more on credit-relevant disclosures, such as adverse credit event disclosures, and less on required annual financial statements. Trading after disclosures also increases more when a bond is large or risky. Moreover, we find that credit rating agencies do respond to disclosures, lending support to the idea that some disclosures have informational value. In further analyses, we find that trading before the disclosure, lack of timeliness, illiquidity, and information processing constraints contribute to the limited trading on the average disclosure. The findings suggest that reconsidering a one-size-fits-all approach to regulating post-issuance municipal disclosures may be worthwhile.

We propose a novel, theory-based approach to the reinforcement learning problem of maximizing profits when faced with an unknown demand curve. Our method, rooted in multi-armed bandits, balances exploration and exploitation across various prices (arms) to maximize rewards. Traditional Gaussian process bandits cap- ture one informational externality in price experimentation – correlation of rewards through an underlying demand curve. We extend this framework by incorporating a second externality, monotonicity, into Gaussian process bandits by introducing monotonic versions of both the GP-UCB and GP-TS algorithms. Through reduction of the demand space, this informational externality limits exploration and experimentation, out- performing benchmarks by enhancing profitability. Moreover, our approach can also complement methods such as partial identification. Additionally, we present algorithm variants that account for heteroscedastic noise in purchase data. We provide theoretical guarantees for our algorithm, and empirically demonstrate its improved performance across a broad range of willingness-to-pay distributions (including discontinuous, time-varying, and real-world) and price sets. Notably, our algorithm increased profits, especially for distribu- tions where the optimal price lies near the lower end of the considered price set. Across simulation settings, our algorithm consistently achieved over 95% of the optimal profits.

We examine political affiliation’s role in venture team formation and success. Using data from Crunchbase and L2 on 1,125 US-based startups, we investigate political homophily in team assembly and its association with startup outcomes. Our analysis reveals strong political homogeneity in founding teams: teams with similar political views form more frequently than diverse teams, even after controlling for founders’ gender, age, location, and industry. This political homophily relates to venture performance. Startups with politically heterogeneous founding teams are more likely to shut down. Across additional performance measures (capital funding, employee size, Crunchbase rankings), we observe directionally consistent associations with worse outcomes, though these secondary findings vary in robustness. These findings highlight the dual role of founders’ political affiliations: their relationship with team composition and startup performance.

We examine how political heterogeneity in groups affects individual performance in settings where people work alongside others. Leveraging the random assignment of golfers to groups in Professional Golfers’ Association Tour tournaments, we find that golfers score 0.2 strokes better per round when playing in politically homogeneous versus heterogeneous groups. This corresponds to a five-rank improvement before the tournament cut and an additional $13,000–$23,400 in tournament earnings. The effect intensifies during periods of high societal political polarization and diminishes when polarization is low. We propose that politically heterogeneous groups create a more stressful and less psychologically safe environment, reducing focus and leading to reduced performance. Consistent with this mechanism, analyses of shot-level data reveal that this effect is strongest during driving and putting shots when players are in close physical proximity. Our study contributes to the understanding of how political heterogeneity in groups affects individual performance in competitive settings, with implications for managing ideological differences in organizations.

This paper studies access to services across geographical regions, using both theoretical and empirical analyses. We model and examine the effects of economies of density in ridesharing markets. Our model predicts that (i) economies of density skew access to rideshareing service away from less dense regions, (ii) the skew will be more pronounced for smaller platforms (i.e., “thinner markets”), and (iii) rideshare platforms do not find this skew efficient and thus use prices and wages to mitigate (but not eliminate) it. We show that these insights are robust to whether the source of economies of density is the supply-side or the demand-side. We then calibrate our model using ride-level Uber data from New York City. We devise an identification strategy based on relative flows of rides among regions which allows us to infer unobsrevable potential demand in different boroughs. We use the model to simulate counterfactual scenarios providing insights on platform optimal pricing with and without spatial price discrimination, the role of market thickness, the impact of prices/wages on access to rides, and the effects of minimum-wage regulations on access equity across regions.

This paper proposes a new measure of technological obsolescence using detailed patent data. Using this measure, we present two sets of results. First, firms' technological obsolescence foreshadows substantially lower growth, productivity, and reallocation of capital. This finding applies mainly for obsolescence of core innovation and embodied innovation, and it is stronger in competitive product markets. Second, in stock markets, high-obsolescence firms under-perform low-obsolescence firms by 7 percent annually. Using analyst forecast data, we show this is due to a systematic overestimation of future profits of obsolescent firms. The measure contains incremental information about firm innovation relative to measures focusing on new innovation.

We conduct a systematic re-analysis of intervention-based studies that promote hygienic latrines and evaluate via experimental methods. We impose systematic inclusion criteria to identify such studies and compile their microdata to harmonize outcome measures, covariates, and estimands across studies. We then re-analyze their data to report metrics that are consistently defined and measured across studies. We compare the relative effectiveness of different classes of interventions implemented in overlapping ways across four countries: community-level demand encouragement, sanitation subsidies, product information campaigns, and microcredit to finance product purchases. In the sample of studies meeting our inclusion criteria, interventions that offer financial benefits generally outperform information and education campaigns in increasing adoption of improved sanitation. Contrary to a policy concern about sustainability, financial incentives do not undermine usage of adopted latrines. Effects vary by share of women in the household, in both positive and negative directions, and differ little by poverty status.

Business managers and policymakers must often communicate magnitudes. Yet conveying large relative magnitudes without desensitizing people to further increases can be challenging because of diminishing sensitivity to large numbers. In this research, we propose that percentage expressions not only make large relative magnitudes (e.g., 500%) appear larger than equivalent non-percentage expressions but also make large increases in relative magnitudes (e.g., from 500% to 600%) appear larger. We posit an explanation: percentages typically have values between 0% and 100%, so when percentages and percentage-point differences reach 100% or more, they seem unusually large. This hypothesis is supported by data scraped from New York Times articles and a series of online experiments employing both management-relevant scenarios and incentive-compatible decisions. Existing theories of magnitude perception either cannot predict all the results of these studies (e.g., numerosity and unitosity) or need further specification to do so (e.g., decision-by-sampling and range-frequency theory). We discuss implications for the theory of magnitude and difference perception and the practice of communicating large magnitudes and changes.

The fact that Amazon was allowed to acquire hundreds of companies as it rose to become the fourth most valuable U.S. company in terms of market capitalization and a leader in three lines of business has been viewed by some as damning evidence of underenforcement by the United States antitrust authorities. In this article we ask the obvious question: If the 2023 Guidelines had been in place instead of prior guidelines, what effects would they have had on Amazon’s development? To provide an answer, we identify relevant changes in the guidelines and then select for review a subset of Amazon’s 280 acquisitions over the period 1998 to 2022. In our counterfactual, we analyze five horizontal acquisitions, four vertical acquisitions, and two sets of serial acquisitions. We find that the 2023 Guidelines would have broadened the bases for potential challenges and thereby would have increased the likelihood that Amazon would have faced greater resistance from antitrust authorities. The lack of safe harbors, the plasticity of individual Guidelines, and the optionality to challenge mergers under alternative theories would have exposed most of Amazon’s acquisitions to challenge. The lack of meaningful guidance about which individual transactions would have been challenged suggests that going forward enforcer discretion will play a yet larger role. Regarding Amazon’s serial acquisitions of nearly one hundred technology firms, we find that the 2023 Guidelines would have provided multiple rationales for intervention. Therein lies a weakness in the Guidelines and in antitrust policy: the lack of a framework for assessing both the anticompetitive and procompetitive effects of such acquisitions in high-tech industries.

Healthcare is one of the largest global industries, encompassing a wide range of occupations, organizational designs, and advanced technologies within different types of systems and forms of ownership (public, for-profit, non-profit). The complexity, range, scale, and importance of the work conducted in the healthcare sector render it an ideal context for scholars engaged in management and organizational research to develop novel, generalizable, and useful theories aligned with the mission of Administrative Science Quarterly.

We are thrilled to feature seven insightful and impactful papers that showcase healthcare as an important context to advance the study of organizations and management.

This context was long the purview of scholars in other disciplines writing solely for healthcare audiences, but management scholars recently have given increased attention to studying healthcare organizations and their management. We were ecstatic to discover that the publication rate of ASQ articles featuring research conducted in healthcare contexts has increased in the last decade relative to prior decades.

Global powers, like the United States and China, exert influence on other countries by threatening the suspension or alteration of financial and trade relationships. We show that the mechanisms that generate gains from integration and specialization, such as external economies of scale, also increase these countries’ power to exert economic influence because in equilibrium they make other relationships poor substitutes for those with a global hegemon. We study how smaller countries can insulate themselves from geoeconomic pressure from the great powers by pursuing anti-coercion policy. We show that while an individual country can make itself better off, uncoordinated attempts by multiple countries to limit their dependency on the hegemon lead to unwinding the global gains from integration and fragmenting the global financial and trade system. Countries resort to inefficient home alternatives the more so hegemons are expected to want to exert their influence in disruptive ways. An integrated liberal world order emerges as an equilibrium when the hegemon’s incentives are well aligned with the world economy, politically and economically. Generically, the world economy fragments along political and economic alignments. We study a leading application focusing on financial services and payment systems as both a tool of coercion by the hegemon and an industry with strong strategic complementarities at the global level.

Fundraising campaigns draw support from a wide pool of contributors. Some contributors are interested in private rewards offered in exchange for contributions (buyers), whereas others are publicly-minded and value success (donors). Buyers face a coordination problem because of the positive externalities of campaign success. A leadership donor who strategically times contributions can promote coordination by dynamically signaling his valuation. The ability to signal increases the probability of success and benefits all participants relative to the donor valuation being known. We validate our modeling assumptions and theoretical predictions using Kickstarter data.

Economics Job Market Rumors (EJMR) is an online forum and clearing house for infor-
mation about the academic job market for economists. It also includes content that is
abusive, defamatory, racist, misogynistic, or otherwise “toxic.” Almost all of this content
is created anonymously by contributors who receive a four-character username when post-
ing on EJMR. Using only publicly available data we show that the statistical properties of
the scheme by which these usernames were generated allows the IP addresses from which
most posts were made to be determined with high probability.1 We recover 47,630 distinct
IP addresses of EJMR posters and attribute them to 66.1% of the roughly 7 million posts
made over the past 12 years. We geolocate posts and describe aggregated cross-sectional
variation—particularly regarding toxic, misogynistic, and hate speech—across sub-forums,
geographies, institutions, and IP addresses. Our analysis suggests that content on EJMR
comes from all echelons of the economics profession, including, but not limited to, its elite
institutions.

An influential emerging literature documents strong correlations between carbon emissions and stock returns. We re-examine those data and conclude that these associations are driven by two factors. First, stock returns are correlated only with unscaled emissions estimated by the data vendor, but not with unscaled emissions actually disclosed by firms. Vendor-estimated emissions systematically differ from firm-disclosed emissions and are highly correlated with financial fundamentals, suggesting that prior findings primarily capture the association between such fundamentals and returns. Second, unscaled emissions, the variable typically used in academic literature, is correlated with stock returns but emissions intensity (emissions scaled by firm size), an equally important measure used in practice, is not. While unscaled emissions represent an important metric for society, we argue that, for individual firms, emissions intensity is an appropriate measurement choice to assess carbon performance. The associations between emissions and returns disappear after accounting for either of the issues above.

We present a new database of banking-crisis interventions from the Roman Empire
to the present, covering 1,946 interventions in 20 categories across 143 countries.
We demonstrate that crisis-intervention patterns are significantly related to income
and fiscal variables and to measures of the political system and currency regime.
GDP losses following crises are economically significant and are larger for
wealthier countries, with some evidence that these losses are mitigated by
democratic political systems and liberal currency regimes. Finally, intervention
frequencies reached an apex during the post-Bretton Woods era, continuing a
secular increase since at least the late 17th century.

A buyer procures a good owned by a group of sellers whose hetero- geneous cost of trade is private information. The buyer must either buy the whole good or nothing, and sellers share the transfer in pro- portion to their share of the good. We characterize the optimal mech- anism: trade occurs if and only if the buyer’s benefit of trade exceeds a weighted average of sellers’ virtual costs. These weights are endog- enous, with sellers who are ex ante less inclined to trade receiving higher weight. This mechanism always outperforms posted-price mechanisms. An extension characterizes the entire Pareto frontier.

Can information from a credible messenger shift behavior in an information-saturated environment? In a randomized controlled trial involving twenty-eight million individuals in West Bengal, we find that SMS-delivered video messages containing information about COVID-19 symptoms and health-preserving behaviors recorded by a credible messenger increased adherence to targeted and non- targeted preventive behaviors, measured by two objective measures (symptoms reported to a health worker, and phone usage at home), as well as self-reported behaviors. We find large spillovers onto non- targeted recipients. Credible light-touch messaging can play an important role in crisis response, even when similar information is widely available.

This book offers a radical thesis: Technological innovation often benefits elites while worsening conditions for workers, challenging the common view that technology always improves living standards. Through historical transitions like the Industrial Revolution, the authors illustrate how innovations have frequently led to worker exploitation. They argue that governance, rather than competition, determines whether technological advances benefit society. In the digital age, platforms exploit user data without fair compensation, causing harm through addictive services and poor regulation. The book calls for stronger regulations to protect consumers and ensure that innovation aligns with societal well-being, especially as artificial intelligence spreads.