Labor Market Conflict and the Decline of the Rust Belt
Simeon Alder, David Lagakos & Lee Ohanian
Journal of Political Economy, forthcoming
No region of the United States fared worse over the postwar period than the "Rust Belt," the heavy manufacturing region bordering the Great Lakes. This paper hypothesizes that the decline of the Rust Belt was due in large part to the persistent labor market conflict that was prevalent throughout the region's main industries. We formalize this thesis in a multi-sector dynamic general equilibrium model in which labor market conflict leads to strikes and wage premia in equilibrium. These result in lower investment and productivity growth, which causes employment to move from the Rust Belt to the rest of the country. The model also features rising foreign competition as an alternative source of the Rust Belt's decline. Quantitatively, labor conflict accounts for around half of the decline in the Rust Belt's share of manufacturing employment. Consistent with the data, the model predicts that the Rust Belt's employment share stabilizes by the mid 1980s, once labor conflict subsides. Rising foreign competition plays a more modest role quantitatively, and its effects are concentrated in the 1980s and 1990s, after most of the Rust Belt's decline had already occurred.
Where Have All the "Creative Talents" Gone? Employment Dynamics of US Inventors
Ufuk Akcigit & Nathan Goldschlag
NBER Working Paper, March 2023
How are inventors allocated in the US economy and does that allocation affect innovative capacity? To answer these questions, we first build a model of creative destruction where an inventor with a new idea has the possibility to work for an entrant or incumbent firm. If the inventor works for the entrant the innovation is implemented and the entrant displaces the incumbent firm. Strategic considerations encourage the incumbent to hire the inventor, offering higher wages, and then not implement the inventor's idea. To test this prediction, we combine data on the employment history of over 760 thousand U.S. inventors with information on jobs from the Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau. Our results show that (i) inventors are increasingly concentrated in large incumbents, less likely to work for young firms, and less likely to become entrepreneurs, and (ii) when an inventor is hired by an incumbent, compared to a young firm, their earnings increases by 12.6 percent and their innovative output declines by 6 to 11 percent. We also show that these patterns are robust and not driven by life cycle effects or occupational composition effects.
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
Tyna Eloundou et al.
University of Pennsylvania Working Paper, March 2023
We investigate the potential implications of large language models (LLMs), such as Generative Pre-trained Transformers (GPTs), on the U.S. labor market, focusing on the increased capabilities arising from LLM-powered software compared to LLMs on their own. Using a new rubric, we assess occupations based on their alignment with LLM capabilities, integrating both human expertise and GPT-4 classifications. Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted. We do not make predictions about the development or adoption timeline of such LLMs. The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software. Significantly, these impacts are not restricted to industries with higher recent productivity growth. Our analysis suggests that, with access to an LLM, about 15% of all worker tasks in the US could be completed significantly faster at the same level of quality. When incorporating software and tooling built on top of LLMs, this share increases to between 47 and 56% of all tasks. This finding implies that LLM-powered software will have a substantial effect on scaling the economic impacts of the underlying models. We conclude that LLMs such as GPTs exhibit traits of general-purpose technologies, indicating that they could have considerable economic, social, and policy implications.
The Race Between Education, Technology, and the Minimum Wage
NBER Working Paper, March 2023
What is the impact of the minimum wage on the college wage premium? I show that job-ladder models imply that the effect should be small on impact -- raising only the wages of workers bound by the minimum wage -- and grow over time as workers slowly move up the job ladder. Guided by my theory, I present evidence that these dynamic effects are present and powerful. Estimated at the national level, I show that minimum wages -- together with supply and demand -- play a central role in shaping the evolution of the U.S. college premium. Estimated at the state level, I show that the elasticity of the college premium to the minimum wage is small on impact and grows dramatically over time. To verify my theory's mechanisms, I additionally document the dynamic impact of the minimum wage over the full wage distribution: on impact, wages rise only for the lowest percentiles (consistent with the literature) but over time this effect spills over up the wage distribution (consistent with my theory and my empirical results on the skill premium). On the basis of these theoretical and empirical results, I conclude that the minimum wage plays a central role in shaping the U.S. college premium and its variation across states.
Do higher minimum wages decrease union membership in minimum-wage-intensive industries?
Jeffrey Clemens & Michael Strain
Applied Economics Letters, forthcoming
Over the past decade, organized labour has played a significant role in advocating for minimum wage increases. In this paper, we investigate the effects of minimum wage increases on union membership among individuals in minimum wage intensive industries. We find no evidence of a change in union membership among high-skilled workers in these industries. Consistent with a 'free-riding' hypothesis, we find evidence that minimum wage increases predict declines in union membership among low-skilled workers in these industries. These workers are the minimum wage's most direct beneficiaries.
A Human Capital Theory of Who Escapes the Grasp of the Local Monopsonist
Matthew Kahn & Joseph Tracy
NBER Working Paper, March 2023
Over the last thirty years, there has been a rise in several empirical measures of local labor market monopsony power. The monopsonist has a profit incentive to offer lower wages to local workers. Mobile high skill workers can avoid the lower monopsony wages by moving to other more competitive local labor markets featuring a higher skill price vector. We develop a Roy Model of heterogeneous worker sorting across local labor markets that has several empirical implications. Monopsony markets are predicted to experience a "brain drain" over time. Using data over four decades we document this deskilling associated with local monopsony power. This means that observed cross-sectional wage gaps in monopsony markets partially reflects sorting on worker ability. The rise of work from home may act as a substitute for high-skill worker migration from monopsony markets.
Unionization at Volkswagen in Chattanooga: A Postmortem
Labor Studies Journal, forthcoming
Declining unionization rates in the private sector have long been a major object of research across the social sciences and among students of the labor movement. Nowhere is this issue felt more acutely than in core productive sectors of the American South, where employers have beaten back nearly every significant organizing effort. These problems are epitomized by the United Autoworkers Workers' 2014 defeat at the hands of German automaker Volkswagen in Chattanooga, Tennessee, where it failed to win an election despite management's ostensible neutrality. Though various competing explanations have been offered, I attribute the UAW's underwhelming performance principally to the union's own mistakes and shortcomings. Applying an analytical framework first proposed by Marshall Ganz, I argue that on three key measures of organizational performance-access to information, strategic capacity, and ongoing learning-the UAW fell short, ultimately sealing its fate. First, the UAW neglected to draw important lessons from its previous efforts to organize foreign-owned automakers, which often bore an uncanny resemblance to Volkswagen. Second, the UAW did not deploy its resources effectively, all but disregarding the widely held "best practices" and often displaying a more fundamental ineptitude. Finally, while successful unions adapt to changing conditions, the UAW suffered from path dependency, refusing to make necessary corrections when its pre-ordained strategy sent it veering off-course. These findings suggest, contra the dominant narrative, that the UAW bears some responsibility for its own organizing failures, with profound implications for the future of unions in the American South and beyond.
The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments
Erik Brynjolfsson et al.
NBER Working Paper, March 2023
We use data from the Annual Survey of Manufactures to study the characteristics and geography of investments in robots across U.S. manufacturing establishments. We find that robotics adoption and robot intensity (the number of robots per employee) is much more strongly related to establishment size than age. We find that establishments that report having robotics have higher capital expenditures, including higher information technology (IT) capital expenditures. Also, establishments are more likely to have robotics if other establishments in the same Core-Based Statistical Area (CBSA) and industry also report having robotics. The distribution of robots is highly skewed across establishments' locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presence of robot integrators and higher levels of union membership are positively correlated with being a Robot Hub.
How Do People Respond When They Know That Robots Will Take Their Jobs?
Christian Gunadi & Hanbyul Ryu
Oxford Bulletin of Economics and Statistics, forthcoming
In recent years, the USA observed a substantial increase in the adoption of robotic technology. The use of industrial robots in the US economy increased rapidly from about 1 robot per 1,000 workers in 2005 to 1.7 robots per 1,000 workers in 2017, a 70% increase. At the same time, there is a concern that the rapid adoption of robots will transform our society in a way that we have never seen before. In this article, we investigate whether individuals are responding to the increasing use of robots in their locality by altering their schooling decision. The results of the analysis suggest that a 10% increase in robot exposure is associated with an approximately 2.5% rise in college enrolment rate. In the long run, we find evidence that more intense exposure to robots during school ages is associated with an increase in the probability of an individual obtaining a college degree.
The Independent Contractor Workforce: New Evidence On Its Size and Composition and Ways to Improve Its Measurement in Household Surveys
Katharine Abraham et al.
NBER Working Paper, March 2023
Good data on the size and composition of the independent contractor workforce are elusive, with household survey and administrative tax data often disagreeing on levels and trends. We carried out a series of focus groups to learn how self-employed independent contractors speak about their work. Based on these findings, we designed and fielded a large-scale telephone survey to elicit more accurate and complete information on independent contractors, including those who may be coded incorrectly as employees in conventional household survey data and those who are independent contractors in a secondary work activity. We find that, upon probing, roughly one in 10 workers who initially reports working for an employer on one or more jobs (and thus is coded as an employee) is in fact an independent contractor on at least one of those jobs. Incorporating these miscoded workers into estimates of work arrangement on the main job nearly doubles the share who are independent contractors, to about 15 percent of all workers. Young workers, less-educated workers, workers of color, multiple-job holders, and those with low hours are more likely to be miscoded. Taking these workers into account substantively changes the demographic profile of the independent contractor workforce. Our research indicates that probing in household surveys to clarify a worker's employment arrangement and identify all low-hours work is critical for accurately measuring independent contractor work.
Small Businesses and the Minimum Wage
Jesse Wursten & Michael Reich
University of California Working Paper, March 2023
We provide the first causal analysis of the role of firm size on minimum wage effects in the U.S. Using a stacked event study estimator, we find that minimum wages increase pay in low wage industries, particularly so in small businesses. We do not detect any corresponding disemployment effects. For teens, wage increases are stronger in larger businesses and come with modest disemployment effects in smaller ones. These results point to strong monopsony power for large firms and backward bending teen labor supply curves.