Knowledge that Transforms

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 Drawing upon published and unpublished sources documenting his academic training, his involvement in the economics profession, and his overall scholarship, this article shows that Du Bois made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

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).

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.

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.

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.

We document a series of stylized facts about how firms seek to protect the rents from innovation, using a large nationally representative survey of U.S. businesses over the period 2008-2015. Just 1.4 percent of firms obtain patents, but these patenting firms account for 87 percent of R&D investment. Firms consider utility patents less important than other forms of IP protection, like trade secrets, trademarks, and copyrights. Firm industry and size are strongly correlated with firms’ use of all types of intellectual property, but firm-age is not. Implications for innovation research and policy are discussed.

Court capture in developing countries is pervasive, yet its economic effects remain underexplored. We study a Chinese reform that transferred financial and personnel authority over local courts from local to provincial governments. Exploiting the staggered roll-out, we find a 7.3% decline in local defendants’ win rates against non-local plaintiffs, alongside improved judicial quality. The reform encouraged smaller non-local firms to litigate and attracted non-local investment, potentially raising GDP by 1.9%. Yet favoritism toward politically connected firms and inter-provincial protectionism remain, and centralization itself promotes less qualified judges— revealing both its promise and limits.

Counterfactuals in quantitative trade and spatial models are functions of the current state of the world and the model parameters. Common practice treats the current state of the world as perfectly observed, but there is good reason to believe that it is measured with error. This paper provides tools for quantifying uncertainty about counterfactuals when the current state of the world is measured with error. I recommend an empirical Bayes approach to uncertainty quantification, and show that it is both practical and theoretically justified.

This paper provides novel evidence on how dietary habits – a key health behavior – are transmitted across generations, exploiting unique grocery transaction data linked with administrative records. We document strong intergenerational persistence in dietary habits, exceeding that of income, and consider several channels that might explain this pattern. Specifically, we find that socioeconomic status and geography account for only a small share of the transmission. Combined with the absence of a dietary response following a parent’s unexpected lifestyle-related death, these findings underscore the importance of early-life influences and habit formation.