ABSTRACT In April 2016, the European Union adopted the General Data Protection Regulation (GDPR), significantly expanding privacy protections for personal data handled by firms. I examine the regulation’s impact on U.S. firms’ internal information quality (IIQ) and operational efficiency. Although privacy regulations target one subset of firms’ information assets (i.e., personal data), they may spur broad improvements in firms’ information governance practices and systems, resulting in higher quality information available for decision-making and, by extension, more efficient operations. Using a difference-in-differences design, I find that U.S. firms with European operations (i.e., treated firms) exhibit improvements in IIQ around the adoption of the GDPR. Furthermore, although the GDPR’s regulatory burden is overall costly to firms, GDPR-induced improvements in IIQ contribute positively to operational efficiency. These findings highlight that privacy regulation can act as a catalyst for firms to improve IIQ, yielding operational benefits that may partially offset the regulation’s costs. Data Availability: All data are available from public sources discussed in the text. JEL Classifications: L51; M40; M41; K24.

Research shows that access to high-quality financial services varies with local income and wealth. We study how financial firms’ internal allocation of human capital contributes to these disparities. Using a near-comprehensive panel of over 350,000 U.S. mortgage loan officers, we document large and persistent differences in productivity and performance. We find that firms’ hiring and promotion practices allocate workers with less experience or poor track records to branches serving low-income customers. Further, the consequences of poor performance differ by location: low sales, bad loans, and misconduct are more tolerated in low-income branches, exacerbating income-based disparities in financial services.

Many ideas succeed in small trials but weaken considerably at scale. Using early childhood investment as a case study, this paper develops a dynamic microfounded human capital model stylized in the Chicago tradition. The framework features optimizing agents, complementary skill formation, and a policymaker choosing scaling strategies. The model shows that naive extrapolation from pilots systematically overestimates societal impact by overlooking voltage drops: declining benefit-cost profiles due to unrepresentative samples and contexts. Optimal scaling requires option C thinking, a mechanism-based design approach that anticipates these failures through backward induction from real-world implementation constraints. Studies in this special issue enrich the model’s insights.

• We investigate illegal insider trading in China’s stock market. • Cross-provincial variation in legal quality affects insider-trading profitability and risk. • Stronger legal environments raise regulatory risk and enhance pricing efficiency. • Results show evidence consistent with deterrence in the form of fewer low-return trades. • Lower information efficiency enhances the positive impact of legal quality on insider-trading profitability. This study examines how provincial legal environments shape the profitability of illegal insider trading in China. Using 521 adjudicated insider-trading cases from 2006 to 2018, we hand-collect detailed information from court judgments and CSRC sanction documents to reconstruct holding-period returns and illicit gains. We combine these data with established provincial indices of legal development and firm-level measures of ex ante litigation risk to test whether legal risk is priced in illegal insider trades. We find that stronger provincial legal environments are associated with significantly higher per-trade profitability among illegal trades that insiders execute after accounting for enforcement risk. This pattern is consistent with a risk-compensation mechanism rather than a failure of enforcement, as stricter legal environments deter low-return trades and leave only trades with sufficiently high expected gains. Firm-level litigation exposure further strengthens this effect. The results remain robust to sample-selection corrections, alternative return measures and a range of heterogeneity tests. Overall, our findings show how institutional variation in enforcement shapes insider incentives and the risk–return trade-off of illegal trading.

Many social insurance programs have low take-up, but it is unclear whether this is due to administrative barriers, information, or low insurance valuations. We study a Thai policy that offered large incentives for informal workers in selected provinces to enroll. The incentives increased insurance coverage by 67 percentage points- from 6 percent of informal workers to 73 percent- within two months. However, 12 months later, only 13 percent remained insured. Using choices among insurance tiers to back out revealed valuations, we find that low social insurance enrollment may be due to low ex-ante valuations of insurance, rather than administrative barriers.

In the U.S. airline industry, independent regional airlines fly passengers on behalf of several national airlines across different markets, giving rise to common subcontracting. On the one hand, we find that subcontracting is associated with lower prices, consistent with the notion that regional airlines tend to fly passengers at lower costs than major airlines. On the other hand, we find that common subcontracting is associated with higher prices. These two countervailing effects suggest that the growth of regional airlines can have anticompetitive implications for the industry.

ABSTRACT Results from multiple experiments demonstrate that evaluators more favorably evaluate creative output produced by designers with higher expertise, even when the underlying creativity of the output is held constant (hereafter, expertise bias). We find, however, that this bias is mitigated when evaluators know that Artificial Intelligence (AI) can augment creative design processes, because AI’s capabilities reduce the perceived exclusivity of designers’ domain expertise. We also show that designers can restore the perceived exclusivity of their expertise, reestablishing the expertise bias, by choosing not to use available AI tools. Although prior research focuses on AI’s ability to enhance or inhibit the creativity of output, we highlight that it can enhance the creative process by mitigating a prevalent human bias in the subjective evaluation of this output. We also contribute to a better understanding of why some experienced designers refuse to utilize AI. Data Availability: Data are available upon request. JEL Classifications: L29; M41; M55.

This paper reports causal evidence on how the extent of hybrid work—the number of days worked from home relative to days worked from office—affects employee attitudes and performance. Workers who spent around two days in the office each week on average self-reported greater work-life balance, more job satisfaction, and lower isolation from colleagues compared to workers who spent more or fewer days in the office. Employees in the intermediate hybrid condition received no different performance ratings compared to peers who spent more or fewer days in the office.

ABSTRACT We examine whether and how a widely established finding—employees respond negatively to managerial monitoring—generalizes to different performance-evaluation systems. We predict that relative performance evaluations (RPEs), a common evaluation feature in multiagent settings, attenuate employees’ negative responses to managerial monitoring. The results of our experiment support our theory. Consistent with prior literature, we find that without RPE, employees respond significantly more negatively to managerial monitoring compared to no monitoring. However, we find that the effect of managerial monitoring on employee responses is moderated in the presence of RPE—employees respond similarly regardless of whether their manager implements a monitoring control. We provide robust analyses to support our theory-derived mechanisms, demonstrating that our results are driven by employees’ fairness perceptions of managers’ monitoring decisions. Collectively, this study aids in the understanding of how and under what circumstances managerial monitoring may be more or less beneficial. Data Availability: Available upon request. JEL Classifications: C90; D91; J31; M40.

We propose a novel identification strategy to isolate exogenous immigration shocks across US counties, by interacting quasi-random variations in the composition of ancestry across counties with the contemporaneous inflow of migrants from different countries. We show a positive causal impact of immigration on local innovation and wages at the five-year horizon. The positive dynamic impact of immigration on innovation and wages dominates the short-run negative impact of increased labor supply. A structural estimation of a model of endogenous growth and migrations suggests the increased immigration to the United States since 1965 may have increased innovation and wages by 5 percent. (JEL J15, J22, J31, J61, O31, R11, R23)