Work Product
Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence
Erik Brynjolfsson, Bharat Chandar & Ruyu Chen
Stanford Working Paper, August 2025
Abstract:
This paper examines changes in the labor market for occupations exposed to generative artificial intelligence using high-frequency administrative data from the largest payroll software provider in the United States. We present six facts that characterize these shifts. We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks. In contrast, employment for workers in less exposed fields and more experienced workers in the same occupations has remained stable or continued to grow. We also find that adjustments occur primarily through employment rather than compensation. Furthermore, employment declines are concentrated in occupations where AI is more likely to automate, rather than augment, human labor. Our results are robust to alternative explanations, such as excluding technology-related firms and excluding occupations amenable to remote work. These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market.
Minimum wage increases and vacancies
Marianna Kudlyak, Murat Tasci & Didem Tüzemen
Labour Economics, forthcoming
Abstract:
We use a unique data set and a novel identification strategy to estimate the effect of minimum wage increases on vacancy postings. Utilizing occupation-specific county-level vacancy data from the Conference Board’s Help Wanted Online for 2005-18, we find that state-level minimum wage increases lead to substantial declines in existing and new vacancy postings in occupations with a larger share of workers earning close to the effective minimum wage. We estimate that a 10 percent increase in the state-level effective minimum wage reduces vacancies in these occupations relative to the rest by 2.4 percent in the same quarter, and the cumulative effect is as large as 4.5 percent a year later. Focusing on vacancies rather than employment allows us to highlight changes in firms’ hiring intentions in response to minimum wage increases. Coupled with the earlier U.S. evidence showing reductions in separations following minimum wage hikes, our finding of declining vacancies contributes to the broader empirical literature suggesting negligible effects of minimum wage increases on net employment.
Job Transformation, Specialization, and the Labor Market Effects of AI
Lukas Freund & Lukas Mann
Boston College Working Paper, August 2025
Abstract:
Who will gain and who will lose as AI automates tasks? While much of the discourse focuses on job displacement, we show that job transformation -- a shift in the task content of jobs -- creates large and heterogeneous earnings effects. We develop a quantitative, task-based model where occupations bundle multiple tasks and workers possessing heterogeneous portfolios of task-specific skills select into occupations by comparative advantage. Automation shifts the relative importance of tasks within each occupation, inducing wage effects that we characterize analytically. To quantify these effects, we measure the task content of jobs using natural language processing, estimate the distribution of task-specific skills, and exploit mappings to prominent automation exposure measures to identify task-specific automation shocks. We apply the framework to analyze automation by large language models (LLMs). Within highly exposed occupations, like office and administrative roles, workers specialized in information-processing tasks leave and suffer wage losses. By contrast, those specialized in customer-facing and coordination tasks stay and experience wage gains as work rebalances toward their strengths. Our findings challenge the common assumption that automation exposure equates to wage losses.
What’s driving the decline in entrepreneurship?
Nicholas Kozeniauskas
Journal of Monetary Economics, September 2025
Abstract:
Why has there been a steady decline in entrepreneurship in the US in recent decades? To answer this question, I develop a general equilibrium occupation choice model and combine it with data on these choices. Skill-biased technical change can account for much of the decline in the relative entrepreneurship rate of more educated people, but cannot explain the decline in the aggregate level of entrepreneurship. The major factors in the decline in the share of people who are entrepreneurs, the firm entry rate, and the size of the entrepreneur sector are rising entry costs and outsized productivity gains by large non-entrepreneur firms.
The Labor Market Impacts of Fair Work Legislation
Anja Gruber
ILR Review, forthcoming
Abstract:
Fair Workweek (FWW) ordinances, which typically require employers to provide workers with advance notice of their schedules and extra pay for last-minute changes, have become an increasingly debated policy tool to address the unpredictability of low-wage work in the United States. In this article, the author studies the labor market impacts of the Oregon FWW law using data on treated workers from the Quarterly Workforce Indicators and American Community Survey, and a variety of empirical approaches that address the factors complicating such a labor market analysis. Taken together, the evidence points to limited effects on the average labor market outcomes of workers covered by the legislation. However, findings indicate increased employment and hours worked for men, and decreased employment and hours worked for women. Also, results show consistent evidence of decreased average monthly earnings for newly hired women at treated employers. Despite the ability of employers to bypass compensation requirements through voluntary standby lists, this study identifies compositional effects on the workforce resulting from FWW legislation.
Better Safe than Sorry? Toxic Waste Management after Union Elections
Magnus Schauf & Eline Schoonjans
Journal of Labor Economics, forthcoming
Abstract:
This paper studies the impact of union representation on toxic waste management at US facilities between 1991 and 2020. Using a regression discontinuity design, we find an increase in waste releases and air pollution and a decrease in waste treatment after union election wins. These effects persist after the bargaining of a first contract and are neither driven by changes in the production output nor financial constraints. Further, we document an increase in innovative waste prevention that partly offsets the reduction of waste treatment. Our findings suggest that safety and cost concerns of waste treatment dominate environmental and health concerns of waste releases.
Algorithmic Writing Assistance on Jobseekers’ Resumes Increases Hires
Emma Wiles, Zanele Munyikwa & John Horton
Management Science, forthcoming
Abstract:
There is a strong association between writing quality in resumes for new labor market entrants and whether they are ultimately hired. We show this relationship is, at least partially, causal: In a field experiment in an online labor market with nearly half a million jobseekers, treated jobseekers received nongenerative algorithmic writing assistance on their resumes. Treated jobseekers were hired 8% more often at 10% higher wages. Contrary to concerns that the assistance takes away a valuable signal, we find no evidence that employers were less satisfied. We find that the writing on treated jobseekers resumes had fewer errors and was easier to read. Our analysis suggests that writing is an imperfect signal of ability but better writing helps employers ascertain ability through clearer writing, suggesting digital platforms could benefit from incorporating nongenerative algorithmic writing assistance into text-based descriptions of labor services or products.