Knowledge that Transforms

A large literature at the intersection of economics and finance offers prescriptions for regulating banks to increase financial stability.This literature abstracts from the discretion that accounting standards give banks over financial reporting, creating a gap between the information assumed to be available to regulators in models of optimal regulation and the information available to regulators in reality.We bridge insights from the economics, finance, and accounting literatures to synthesize knowledge about the design and implementation of bank regulation and identify areas where more work is needed.We present a simple framework for organizing the relevant ideas, namely the externalities that motivate bank regulation, the rationales for allowing accounting discretion, and the use of discretion to circumvent regulation.Our takeaway from reviewing work in these areas is that academic studies of bank regulation and accounting discretion require a more unified approach to design optimal policy for the real world.

If racial gaps in measures of human capital like educational attainment and standardized test scores were eliminated, what would happen to racial disparities in wages, employment, and other labor market outcomes?A credible answer to this question is foundational for understanding the nature and scope of racial inequality and discrimination in the United States.This article reviews and synthesizes a literature that studies this question by estimating the extent to which controlling for measures of human capital changes Black-white gaps in labor market outcomes, and discusses various conceptual and methodological issues related to interpreting this type of exercise.I show that while accurately interpreting this exercise and its many variants requires careful thinking, the results elucidate many important and subtle aspects of racial inequality in the United States.

The empirical economics literature on taxation in developing countries has centered on the importance of third-party information for enforcement. Yet, while surely a long-run objective, leveraging such information remains out of reach in many developing countries due to largely informal economies and low state capacity. This article examines an emerging complementary literature focused on strengthening the “sinews” of state capacity: tax administration. We argue that reforms to the organizational structure, personnel management, and task management of tax authorities have potential to raise tax capacity in developing countries. We also argue that efforts to improve the state’s legitimacy—popular acceptance of its right to tax—can increase capacity and may complement investments in tax administration. Our approach bridges a long-standing divide between how scholars in public finance and political economy approach tax capacity building in developing countries. (JEL D63, D73, H20, H50, K34, M50, O17)

This essay reviews seven books from the past dozen years by social scientists examining the economic impact of artificial intelligence (AI). These works offer valuable insights—AI as cheap prediction, architectural barriers to adoption, data as an economic asset, implementation challenges. However, they offer little guidance when it comes to the transformative scenarios considered plausible by many AI researchers. Economists have made great progress in explaining how to use AI within existing production functions, who benefits, and why; what remains needed is rigorous advice to policymakers concerned about rapid increases in labor churn, scientific development, labor–capital shifts, or existential risk. (JEL C45, C80, D83, O31, O36)

W. E. B. Du Bois is widely considered one of the most prominent American intellectuals of the twentieth century. While Du Bois has been praised for his contributions to sister disciplines, his contributions to economics have been underappreciated. Drawing upon published and unpublished sources documenting his academic training, his involvement in the economics profession, and his overall scholarship, this article shows that Du Bois made enduring contributions to economic science. We trace his intellectual formation as a student of the German Historical School of economics, analyzing his pioneering use of empirical methods to document the plight of Black Americans. Du Bois emphasized the role of power and institutions in structuring distributional outcomes and the importance of economic and social uplift. One implication is that by conducting intra- and intergroup analyses of racial, health, occupational, income, and wealth disparities, Du Bois anticipated the empirical and theoretical aims of stratification economics. (JEL B13, B25, B31, B55, I00, J15, Z13)

This paper describes a process for generating academic papers using large language models (LLMs) and demonstrates this process’s efficacy by producing hundreds of complete papers on stock return predictability, a topic well-suited for our illustration. After mining over 30,000 potential return predictors from accounting data, we generate template reports for 95 signals passing rigorous criteria from the Novy-Marx and Velikov (2024) Assaying Anomalies protocol. These templates detail signal performance predicting returns using a wide array of tests and benchmark performance against more than 200 documented anomalies. Finally, for each template we use state-of-the-art LLMs to generate multiple complete versions of academic papers with distinct theoretical justifications for the observed return predictability, incorporating citations to literature supporting their respective claims. This experiment illustrates the potential of artificial intelligence (AI) for enhancing financial research efficiency, but also serves as a cautionary tale, illustrating how it can be abused to industrialize hypothesizing after results are known (HARKing). ( JEL C12, C45, G12, G17)

Entrepreneurship is thought to be a key driver of economic growth. While there are myriad forms of entrepreneurship, ranging from self-employment to small and medium size enterprises to technology- and innovation-driven startups, recent research provides evidence that the relationship between entrepreneurship and economic growth is driven not by overall quantity of new firm entry, but rather by a small subset of high-growth startups that are primarily categorized as innovation-driven. This paper provides a survey of the growing literature on the economics of such innovation-driven entrepreneurship. We begin by distinguishing between the various forms of entrepreneurship, which are often confounded in both theory and empirical work. We lay out the current state of knowledge, and describe the challenges faced by researchers in the field, particularly around measurement, data and identification. We conclude with an overview of the major open questions and directions for future research in the area.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Difference-in-differences (DiD) is arguably the most popular quasi-experimental research design. Its canonical form, with two groups and two periods, is well understood. However, empirical practices can be ad hoc when researchers go beyond that simple case. This article provides an organizing framework for discussing different types of DiD designs and their associated DiD estimators. It discusses covariates, weights, handling multiple periods, and staggered treatments. The organizational framework, however, applies to other extensions of DiD methods as well. (JEL C23, H75, I12, I38)

Abstract Televised debates between presidential candidates are often regarded as the exemplar of persuasive communication. Yet, recent evidence from Le Pennec and Pons (2023) indicates that they may not sway voters as strongly as popular belief suggests. We revisit their findings through the lens of the persuasion rate and introduce a robust framework that does not require exogenous treatment, parallel trends, or credible instruments. Instead, we leverage plausible monotonicity assumptions to partially identify the persuasion rate and related parameters. Our results reaffirm that the sharp upper bounds on the persuasive effects of TV debates remain modest.

Abstract As manufacturing firms expand globally, business services such as advertising and legal support become essential for entering new markets. Exploiting exogenous demand shocks, we document that French manufacturers increasingly outsource market-access services as they enter more destinations. We develop a theory of market-access costs in which firms weigh the managerial strain of internal provision against adaptation costs of outsourcing—a mechanism that receives empirical sup-port. Further explorations reveal that outsourcing market-access services helps explain variation in access costs related to gravity and extended gravity, affects both sunk and fixed export costs, and substantially amplifies the variety gains from trade liberalization.