Knowledge that Transforms

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 Drawing upon published and unpublished sources documenting his academic training, his involvement in the economics profession, and his overall scholarship, this article shows that Du Bois made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)

Michael Luca of Johns Hopkins University reviews “Decisions about Decisions: Practical Reason in Ordinary Life” by Cass R. Sunstein. The Econlit abstract of this book begins: “Explores the psychological, practical, and emotional factors that inform decision-making processes.”

Elena Carletti of Bocconi University reviews “Unexpected Revolutionaries: How Central Banks Made and Unmade Economic Orthodoxy” by Manuela Moschella. The Econlit abstract of this book begins: “Explores the development of central banks from the heyday of monetary orthodoxy in the 1980s to the 2008 global financial crisis and the 2020 COVID-19 crisis, explaining why central banks responded to changed economic conditions by breaking with monetary orthodoxy and what consequences this evolutionary path entails for the role of central banks in domestic societies.”

Daiji Kawaguchi of University of Tokyo reviews “Building a New Economy: Japan's Digital and Green Transformation” by D. Hugh Whittaker. The Econlit abstract of this book begins: “Explores institutional and ideational change in Japan and whether or not these are coming together to form a new growth model, focusing on the changing nature of the Japanese state and state–market relations, corporate governance, management and employment, education and training, and innovation and entrepreneurship.”

The list below specifies doctoral degrees conferred by U.S. and Canadian universities during academic year July 2024 to June 2025. Lists of degree recipients and subject classifications are provided by the university. Note: Dissertations without classifications may be found under “Y Miscellaneous Categories.”