Publications

Using comprehensive data on U.S. corporate bond trades since 2002, we find evidence that retail bond investors overrely on untimely credit ratings to their financial detriment. Specifically, they appear to select bonds by first screening on a credit rating and then sorting by yield, buying the highest-yielding bonds within each rating level. Because yields lead credit rating changes, selecting on yield-within-rating means that retail investors systematically trade in the opposite direction of changing fundamentals, buy in advance of credit downgrades and defaults, and materially underperform a diversified portfolio. Our study provides new evidence of ill-informed retail trading in a market that is thought to be relatively sophisticated, corroborates regulators' concerns about investor overreliance on credit ratings, and contributes to the academic literature on the roles and consequences of credit ratings in debt markets.

South Asians working temporarily in richer Asian nations is the world's largest international migration corridor. We track down 3,512 (of 1.4 million) applicants to a government lottery that randomly allocated visas to Bangladeshis for low-skilled, temporary labor contracts in Malaysia, five years after the lottery. Most lottery winners migrate and migrants' earnings triple. Their remittance raises their family's standard of living in Bangladesh. The migrant's absence pauses marriage and childbirth, and shifts decision-making power towards females. Migration removes enterprising individuals, lowering household entrepreneurship, but does not crowd out other family members' labor supply. One group of applicants were offered deferred migration that never materialized. Improved migration prospects induce pre-migration investments in skills that generate no returns in the domestic market.

This paper estimates the causal effect of equalizing revenues across public school districts on students’ intergenerational mobility. I exploit differences in exposure to equalization across seven cohorts of students in 20 US states, generated by 13 state-level school finance reforms passed between 1980 and 2004. Since these reforms create incentives for households to sort across districts and this sorting affects property values, post-reform revenues are endogenous to an extent that varies across states. I address this issue with a simulated instruments approach, which uses newly collected data on states’ funding formulas to simulate revenues in the absence of sorting. I find that equalization has a large effect on mobility of low-income students, with no significant changes for high-income students. Reductions in the gaps in inputs (such as the number of teachers) and in college attendance between low-income and high-income districts are likely channels behind this effect.

Municipal bond markets began pricing sea-level rise (SLR) exposure risk in 2013, coinciding with upward revisions to worst-case SLR projections and accompanying uncertainty around these projections. The effect is larger for long-maturity bonds and not solely driven by near-term flood risk. We use a structural model of credit risk to quantify the implied economic impact and distinguish between the effects of underlying asset values and of uncertainty. The SLR exposure premium exhibits a trend different from house prices and is unaffected by house price controls. Together, our results highlight the importance of climate uncertainty in driving municipal bond prices.

Addressing public health externalities often requires community-level collective action. Due to social norms, each person’s sanitation investment decisions may depend on the decisions of neighbors. We report on a cluster randomized controlled trial conducted with 19,000 households in rural Bangladesh where we grouped neighboring households and introduced (either financial or social recognition) rewards with a joint liability component for the group, or asked each group member to make a private or public pledge to maintain a hygienic latrine. The group financial reward has the strongest impact in the short term (3 months), inducing a 7.5–12.5 percentage point increase in hygienic latrine ownership, but this effect dissipates in the medium term (15 months). In contrast, the public commitment induced a 4.2–6.3 percentage point increase in hygienic latrine ownership in the short term, but this effect persists in the medium term. Non-financial social recognition or a private pledge has no detectable effect on sanitation investments.

Social progress through improved treatment of minority groups (e.g., forbidding racial or sexual harassment) may or may not spread to corporate cultures through competition. We provide a theory of corporate culture, and we show that emergent, progressive corporate cultures can displace existing, regressive ones when the prevailing wage gap is large between majority and minority groups. The model provides testable predictions on racial and gender wage gaps across firms.

Importance  Emergency department (ED) triage models are intended to queue patients for treatment. In the absence of higher acuity, patients of the same acuity should room in order of arrival.

Objective  To characterize disparities in ED care access as unexplained queue jumps (UQJ), or instances in which acuity and first come, first served principles are violated.

This paper proposes a theory of large-scale government bond purchases by central banks in an environment with endogenous information acquisition. Information acquisition by private investors lowers risk premia by reducing uncertainty, but also makes prices more sensitive to new information. This can drive the sovereign into costly roll-over crises. Asset purchases by the central bank discourage private information acquisition, impairing price informative- ness. This, however, points to a benefit of such large scale programs: by im- plementing purchases, the central bank can avoid the occurrence of roll-over crises in the event of bad news, generating large welfare gains. A key property of the model is that substantial purchases may be required, while small inter- ventions have ambiguous welfare consequences. When the sovereign expects the central bank to carry such programs, it leads to excessive indebtedness, forcing the central bank to run an inflated balance sheet to avoid roll-over crises

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.

An archeologist discovers a 1,500-year-old Viking sword at the bottom of a lake. Would people be more drawn to the sword if they knew that the discovery was intentional, or unintentional? The current research examines this previously unexplored type of biographical narrative-the biography of the discovery of historical and natural resources. We propose that unintentionality in the discovery of a resource can shape choice and preference. We focus our investigation on resources because the event of discovery is an inherent component in the biography of all known historical and natural resources, and because these resources are either themselves already objects (like historical artifacts) or are the building blocks of virtually all objects. Eight laboratory studies and one field experiment indicate that the unintentional discovery of resources heightens the choice of and preference for the resources. We find that the unintentional discovery of a resource triggers counterfactual thoughts about how the discovery might not have occurred, increasing perceptions that the discovery was fated, consequently driving choice of and preference for the resource. Further, we identify the level of expertise of the discoverer as a theoretically relevant moderator of this effect, finding that the effect is eliminated in the case of novice discoverers. It arises for resources discovered by experts with the rationale that unintentional discovery by an expert is unexpected, and therefore prompts heightened counterfactual thoughts. However, resources discovered by novices for which discovery is unexpected whether it is intentional or unintentional are preferred at equally high rates.

This paper studies the dissemination of frontier knowledge through higher education. Apply- ing natural language processing (NLP) techniques to the text of 1.7M university course syllabi and 20M academic articles, we construct the “education-innovation gap,” a measure of a syl- labus’s distance from frontier knowledge. Using this measure, we document four new facts. First, courses differ greatly in their education-innovation gap, even after controlling for field, course-level, and time. Second, instructors play an important role in shaping course content. Research-active instructors teach more frontier knowledge, particularly when their research is close to the course topic. Third, access to frontier knowledge is unequal: Schools enrolling more socio-economically advantaged students offer courses with a lower gap. Lastly, students from lower-gap schools are more likely to complete a doctoral degree, produce more patents, and earn more after graduation

Using detailed transactions data across the United States, we find that single women earn 1.5 percentage points lower annualized returns on housing relative to single men. Forty-five percent of the gap is explained by transaction timing and location. The remaining gap arises from a 2% gender difference in execution prices at purchase and sale. Consistent with a negotiation channel, women list for less and experience worse negotiated discounts. The gender gap shrinks in tight markets, where negotiation is replaced by quasi-auctions. Overall, gender differences in housing explain 30% of the gender gap in wealth accumulation for the median household.

We examine the demand-side implications of Amazon's distribution and logistics investments. Our results indicate that online demand—transactions at Amazon and its competitors—does not respond to the consumer's proximity to Amazon's upstream fulfillment distribution facilities, suggesting that their densification did not differentially improve local shipping times and on-time delivery. Instead, we find that investments in last-mile delivery facilities and services allow the company to improve shipping times more directly in the urban markets served by these facilities, simultaneously increasing demand through the rollout of same-day service options and reducing the visits to traditional brick-and-mortar retail.

This paper seeks to demonstrate the impact of the gig economy on product qual- ity in seemingly unrelated local industries through the labor market. Our empirical context is the quality of service for restaurants in the city of Austin, and we examine how they were impacted by the exogenous exit and reentry of rideshare platforms, Uber and Lyft, because of regulatory changes. We leverage these exogenous shocks and combine them with sentiment-analyzed data from Yelp reviews that capture how customers assess the quality of service at each restaurant. We show that, compared with control cities, customers in Austin become more negative about service quality when Uber and Lyft are present in the city. Additionally, we use rich data on employee turnover and wages to demonstrate that service staff turnover increases in Austin when Uber and Lyft are present compared with the control cities. We also conduct several additional studies and robustness checks that are all congruent with our hypothesis that Uber and Lyft lower the quality of service in Austin restaurants by raising their staff turnover. Together, these results suggest signifi- cant ramifications of the gig economy on the broader industries through the labor market.

This paper studies the welfare effects of encouraging rural-urban migration in the develop-
ing world. To do so, we build a dynamic incomplete-markets model of migration in which
heterogeneous agents face seasonal income fluctuations, stochastic income shocks, and disu-
tility of migration that depends on past migration experience. We calibrate the model to
replicate a field experiment that subsidized migration in rural Bangladesh, leading to signif-
icant increases in both migration rates and consumption for induced migrants. The model’s
welfare predictions for migration subsidies are driven by two main features of the model and
data: first, induced migrants tend to be negatively selected on income and assets; second, the
model’s non-monetary disutility of migration is substantial, which we validate using newly
collected survey data from this same experimental sample. The average welfare gains are
similar in magnitude to those obtained from an unconditional cash transfer, and greater than
from policies that discourage migration, though migration subsidies lead to larger gains for
the poorest households, which have the greatest propensity to migrate.

The ability of recent Large Language Models (LLMs) such as GPT-3.5 and GPT-4 to generate human-like texts suggests that social scientists could use these LLMs to construct measures of semantic similarity that match human judgment. In this article, we provide an empirical test of this intuition. We use GPT-4 to construct a measure of typicality—the similarity of a text document to a concept. We evaluate its performance against other model-based typicality measures in terms of the correlation with human typicality ratings. We conduct this comparative analysis in two domains: the typicality of books in literary genres (using an existing dataset of book descriptions) and the typicality of tweets authored by US Congress members in the Democratic and Republican parties (using a novel dataset). The typicality measure produced with GPT-4 meets or exceeds the performance of the previous state-of-the art typicality measure we introduced in a recent paper [G. Le Mens, B. Kovács, M. T. Hannan, G. Pros Rius, Sociol. Sci. 2023, 82–117 (2023)]. It accomplishes this without any training with the research data (it is zero-shot learning). This is a breakthrough because the previous state-of-the-art measure required fine-tuning an LLM on hundreds of thousands of text documents to achieve its performance.

Consensus analyst target prices are widely available online at no cost to investors. In this paper we examine how the amount of dispersion in the individual target prices comprising the consensus affects the predictive association between the consensus target price and future returns. We find that returns implied by consensus target prices and realized future returns are positively correlated when dispersion is low, but they become highly negatively correlated when dispersion is high. Further analyses suggest that the differing effect of dispersion stems from incentive-driven staleness in price targets by some analysts after bad news. As a stock performs poorly and some analysts are slow to update their target prices, dispersion increases, and the consensus target price becomes too high. This has important implications for how consensus analyst target prices should inform investment decisions. We show that a hedge strategy taking a long (short) position in stocks with the highest predicted returns among stocks with the lowest (highest) dispersion earns more than 11% annually. Finally, we show that the negative correlation between consensus-based predicted returns and future realized returns for high-dispersion stocks exists mainly for stocks with high retail interest, suggesting that unsophisticated investors are misled by inflated target prices that are available freely online.