Working it off
The Impact of Artificial Intelligence on the Labor Market
Michael Webb
Stanford Working Paper, November 2019
Abstract:
I develop a new method to predict the impacts of a technology on occupations. I use the overlap between the text of job task descriptions and the text of patents to construct a measure of the exposure of tasks to automation. I first apply the method to historical cases such as software and industrial robots. I establish that occupations I measure as highly exposed to previous automation technologies saw large declines in employment and wages over the relevant periods. I use the fitted parameters from the case studies to predict the impacts of artificial intelligence. I find that, in contrast to software and robots, AI is directed at high-skilled tasks. Under the assumption that the historical pattern of long-run substitution will continue, I estimate that AI will reduce 90:10 wage inequality, but will not affect the top 1%.
Testing the Automation Revolution Hypothesis
Keller Scholl & Robin Hanson
George Mason University Working Paper, December 2019
Abstract:
Recently, many have predicted an imminent automation revolution, and large resulting job losses. Others have created metrics to predict new patterns in job automation vulnerability. As context to such claims, we test basic theory, two vulnerability metrics, and 251 O*NET job features as predictors of 1505 expert reports regarding automation levels in 832 U.S. job types from 1999 to 2019. We find that pay, employment, and vulnerability metrics are predictive (R^2~0.15), but add little to the top 25 O*NET job features, which together predict far better (R^2~0.55). These best predictors seem understandable in terms of traditional kinds of automation, and have not changed over our time period. Instead, it seems that jobs have changed their features to become more suitable for automation. We thus find no evidence yet of a revolution in the patterns or quantity of automation. And since, over this period, automation increases have predicted neither changes in pay nor employment, this suggests that workers have little to fear if such a revolution does come.
Mergers and Acquisitions, Local Labor Market Concentration, and Worker Outcomes
David Arnold
Princeton Working Paper, December 2019
Abstract:
Thousands of establishments employing millions of workers change ownership each year, sometimes leading to large changes in local labor market concentration that potentially increase labor market power. Using matched employer-employee data from the U.S., this paper estimates the direct and indirect effects of mergers and acquisitions (M&As) and resulting local labor market concentration changes on worker outcomes. To measure local concentration, I derive an index of concentration that uses job-to-job mobility patterns to incorporate information on substitutability across industries. Causal effects are estimated using a matched differencein-differences design and cross-sectional variation in the predicted impacts of M&As on local concentration. In mergers that have negligible impacts on local labor market concentration, annual earnings for workers in M&A firms remain stable after the ownership change. In sharp contrast, earnings fall by over 2 percent for M&A workers in mergers that cause significant increases in local labor market concentration, with the largest effects in already concentrated markets. These patterns are similar in tradable industries, suggesting the effects are not driven by changes in product market power. Mergers generating the largest concentration changes generate negative spillovers on other firms in the same labor market, with an implied elasticity of earnings with respect to local concentration equal to -0.22. Viewed through the lens of a standard Cournot model, the results imply local concentration depresses wages by about 4-5 percent relative to a fully competitive benchmark.
Disability Insurance: Error Rates and Gender Differences
Hamish Low & Luigi Pistaferri
NBER Working Paper, November 2019
Abstract:
We show the extent of errors made in the award of disability insurance using matched survey-administrative data. False rejections (Type I errors) are widespread, and there are large gender differences in these type I error rates. Women with a severe, work-limiting, permanent impairment are 20 percentage points more likely to be rejected than men, controlling for the type of health condition, occupation, and a host of demographic characteristics. We investigate whether these gender differences in Type I errors are due to women being in better health than men, to women having lower pain thresholds, or to women applying more readily for disability insurance. None of these explanations are consistent with the data. We use evidence from disability vignettes to suggest that there are different acceptance thresholds for men and women. The differences by gender arise because women are more likely to be assessed as being able to find other work than observationally equivalent men. Despite this, after rejection, women with a self-reported work limitation do not return to work, compared to rejected women without a work limitation.
Financing Entrepreneurship through the Tax Code: Angel Investor Tax Credits
Sabrina Howell & Filippo Mezzanotti
NBER Working Paper, November 2019
Abstract:
A central issue in public finance is the tradeoff between maintaining tax revenues and using the tax code to incentivize particular economic activities. One important dimension of this tradeoff is whether incentive policies are used in practice as policymakers intend. This paper examines one particular tax program that many U.S. states use to stimulate entrepreneurship. Specifically, angel tax credits subsidize wealthy individuals’ investments in startups. This paper finds that these programs have no measurable effect on local entrepreneurial activity or beneficiary company outcomes, despite increasing some measures of angel activity. This appears to reflect the programs failing to screen out financially unconstrained firms and often being used for tax arbitrage. Over 90 percent of beneficiary companies fall into at least one of three categories: a corporate insider received a tax credit; the company previously raised external equity; or the company is not in a high-growth sector. Notably, at least 33 percent of beneficiary companies include an investor receiving a tax credit who is an executive at the company.
Skill Prices, Occupations, and Changes in the Wage Structure for Low Skilled Men
Christopher Taber & Nicolas Roys
NBER Working Paper, November 2019
Abstract:
This paper studies the effect of the change in occupational structure on wages for low skilled men. We develop a model of occupational choice in which workers have multi-dimensional skills that are exploited differently across different occupations. We allow for a rich specification of technological change which has heterogenous effects on different occupations and different parts of the skill distribution. We estimate the model combining four datasets: (1) O*NET, to measure skill intensity across occupations, (2) NLSY79, to identify life-cycle supply effects, (3) CPS (ORG), to estimate the evolution of skill prices and occupations over time, and (4) NLSY97 to see how the gain to specific skills has changed. We find that while changes in the occupational structure have affected wages of low skilled workers, the effect is not dramatic. First, the wages in traditional blue collar occupations have not fallen substantially relative to other occupations -- a fact that we cannot reconcile with a competitive model. Second, our decompositions show that changes in occupations explain only a small part of the patterns in wage levels over our time period. Price changes within occupation are far more important. Third, while we see an increase in the payoff to interpersonal skills, manual skills still remain the most important skill type for low educated males.
Do Targeted Business Tax Subsidies Achieve Expected Benefits?
Lisa De Simone, Rebecca Lester & Aneesh Raghunandan
Stanford Working Paper, November 2019
Abstract:
We examine the association between thousands of state and local firm-specific tax subsidies and business activity in the surrounding county, measured as the number of employees, aggregate wages, per capita employment, per capita wages, and number of business establishments. Using three different matched control groups, we find a positive association between subsidies and the employment measures. However, we show that local information - measured based on subsidy-specific disclosures, public awareness, and local press coverage - plays an important role in the effectiveness of subsidies. We also demonstrate that (i) receipt of multiple or subsequent subsidies in the same counties is critical for these employment outcomes and (ii) results are concentrated in the largest subsidy packages by dollar value. In addition, we observe mixed evidence for the relation between subsidies and business establishments and find little to no local effects for over 1,000 subsidies that cost approximately $99.8 million in aggregate. By providing a large-scale empirical analysis of the relation between firm-specific tax subsidies and aggregate economic activity at the county level, we extend a literature that generally focuses on the real effects of statutory tax policies that impact all firms in a jurisdiction. We also contribute to the accounting literature by examining the role of the local information environment in subsidy effectiveness.
Does a One-Size-Fits-All Minimum Wage Cause Financial Stress for Small Businesses?
Sudheer Chava, Alexander Oettl & Manpreet Singh
NBER Working Paper, December 2019
Abstract:
Do increases in federal minimum wage impact the financial health of small businesses? Using intertemporal variation in whether a state’s minimum wage is bound by the federal rate and credit-score data for approximately 15.2 million establishments for the period 1989-2013, we find that increases in the federal minimum wage worsen the financial health of small businesses in the affected states. Small, young, labor-intensive, minimum-wage sensitive establishments located in the states bound to the federal minimum wage and those located in competitive and low-income areas experience higher financial stress. Increases in the minimum wage also lead to lower bank credit, higher loan defaults, lower employment, a lower entry and a higher exit rate for small businesses. The results are robust to using nearest-neighbor matching and geographic regression discontinuity design. Our results document some potential costs of a one-size-fits-all nationwide minimum wage, and we highlight how it can have an adverse effect on the financial health of some small businesses.
The Minimum Wage and Seasonal Employment: Evidence from the U.S. Agricultural Sector
Amy Kandilov & Ivan Kandilov
Journal of Regional Science, forthcoming
Abstract:
Nearly 40 percent of agricultural workers in the United States earn an hourly wage that is within 10 percent of the prevailing state‐level minimum wage. We evaluate the impact of the minimum wage on farm employment using county‐level data from the U.S. Census of Agriculture. Following Meer and West (2016), we employ long‐differences specifications and find evidence of a dynamic, negative effect of the minimum wage on seasonal agricultural employment, but no effect on year‐round agricultural employment. We estimate a long‐run elasticity of total agricultural employment with respect to the minimum wage of about ‐0.40, which is both statistically and economically significant. Employers’ total expenditures on hired agricultural workers are not affected by the minimum wage. Finally, our analysis suggests that increases in minimum wages may lead to higher capital investment as well as consolidation of farming operations in the agricultural sector.