Working on It
Evaluating the Great Micro Moderation
Sergio Salgado et al.
Stanford Working Paper, September 2023
Abstract:
This paper studies the trends in the income volatility of US workers from 1950 to 2019 using high-quality administrative data from the Social Security Administration and Census’ LEHD. Our results indicate that income volatility, which is a measure of labor income risk, has been stable or declining for most of this period, with the exception of the early 1970s. The decline has been especially pronounced since the early 1980s and has been pervasive across the population: it has been observed within most worker groups defined by gender, age, permanent earnings, and cohort, as well as by employer’s industry, age, and size. These findings contradict a common belief, based on survey data, that income volatility has significantly risen. We link the patterns of income volatility on the worker side to declining volatility on the firm employer side. We investigate several potential drivers of this trend to understand if declining volatility represents a broadly positive development -- declining income risk and uncertainty -- or a negative one -- declining business dynamism. Various factors appear to play a role, including reduced macro volatility, older and larger firms, older employees, and industry mix, but, none of these individually appears to be a dominant force.
Right-to-Work Laws and Discrimination Against Older Workers: Evidence from a Field Experiment
Vitor Melo & Liam Sigaud
George Mason University Working Paper, August 2023
Abstract:
Much research shows widespread hiring discrimination on the basis of various characteristics. Yet, little is known about how government policies may prevent or increase discrimination. This paper develops a framework for understanding how right-to-work laws affect age discrimination in the labor market. Our model predicts that by weakening unions’ ability to negotiate wages and benefits above competitive levels, these laws allow older workers to accept lower compensation, making them more attractive to employers. Using data from a resumé field experiment, we find that right-to-work laws are associated with an approximately 30% reduction in age discrimination against older women.
Entrepreneurship and the Gig Economy: Evidence from U.S. Tax Returns
Matthew Denes, Spyridon Lagaras & Margarita Tsoutsoura
Washington University in St. Louis Working Paper, October 2023
Abstract:
Platform intermediation of goods and services has considerably transformed the U.S. economy. We use administrative data on U.S. tax returns to study the effect of the gig economy on entrepreneurship. We find that gig workers are more likely to become entrepreneurs, particularly those who are lower income, younger, and benefit from flexibility. We track all newly created firms in the economy and show that the gig economy facilitates learning by potential entrepreneurs who experiment with starting riskier firms. Overall, our findings provide novel evidence about how on-the-job learning promotes entrepreneurial entry and shifts the type of firms started by entrepreneurs.
Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data
Leonid Kogan et al.
NBER Working Paper, November 2023
Abstract:
We develop measures of labor-saving and labor-augmenting technology exposure using textual analysis of patents and job tasks. Using US administrative data, we show that both measures negatively predict earnings growth of individual incumbent workers. While labor-saving technologies predict earnings declines and higher likelihood of job loss for all workers, labor-augmenting technologies primarily predict losses for older or highly-paid workers. However, we find positive effects of labor-augmenting technologies on occupation-level employment and wage bills. A model featuring labor-saving and labor-augmenting technologies with vintage-specific human capital quantitatively matches these patterns. We extend our analysis to predict the effect of AI on earnings.
Monopsony in spatial equilibrium
Matthew Kahn & Joseph Tracy
Regional Science and Urban Economics, forthcoming
Abstract:
An emerging labor economics literature examines the consequences of firms exercising market power in local labor markets. The extent of this market power is likely to vary across local labor markets. In choosing what local labor market to live and work in, workers tradeoff wages, house prices and local amenities. Building on the Rosen/Roback spatial equilibrium model, we investigate how the existence of local monopsony power affects the cross-sectional spatial distribution of house prices across cities. We find that house prices decline with increases in the employment concentration in the local market. For renters, this offsets roughly 70 percent of the estimated monopsony wage effect and shifts part of the costs of monopsony to homeowners. We find evidence that collective bargaining and minimum wages limit the extent of capitalization of monopsony power into house prices.
The housing boom and selection into entrepreneurship
João Galindo da Fonseca & Pierluca Pannella
Labour Economics, December 2023
Abstract:
Existing evidence shows that increases in property prices produce immediate positive effects on economic activity and, particularly, on business creation. In this paper, we ask the following question: how does a housing boom alter the selection of individuals that open a firm? The answer to this question is important to understand how robust and long-lasting is the positive effect of a housing shock. We find that the early 2000 US housing boom increased entry into entrepreneurship mostly for lower ability house-owners. We derive our results using IQ scores and an indirect measure of ability constructed from individuals’ wage history.
How it's Made: A General Theory of the Labor Implications of Technology Change
Laurence Ales et al.
Carnegie Mellon University Working Paper, October 2023
Abstract:
We develop a general theory relating technology change and skill demand. Performers (human or machine) face stochastic issues that must be solved in order to complete tasks. Firms choose how production tasks are divided into steps, the rate at which steps need to be completed, and the type of performer assigned to a step. Longer steps are more complex. Performers face a tradeoff between the complexity of their step and the rate at which they can perform. Human performers tend to have an advantage in complex steps while machine performers have an advantage in high rates. The cost of fragmenting tasks into steps and the cost of allocating performers to multiple steps are both central to the theory. We derive the optimal division of tasks, the level of automation, and the demand for workers of different skill levels. The theory predicts that technology change that reduces fragmentation costs and increases process complexity (such as interchangeable parts) increases the dispersion of skill demand; that automation is skill polarizing at lower production volumes and upskilling at higher volumes; and that technology change that raises the cost of fragmenting tasks (such as parts consolidation) reduces the dispersion of skill demand. We find counterparts to the theory across a range of contexts and time periods, including the Hand-Machine Labor Study covering mechanization and process improvement at the end of the 19th century and in contemporary automotive body assembly and optoelectronic semiconductor manufacturing.