Toward understanding the impact of artificial intelligence on labor.

Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work. These barriers include the lack of high-quality data about the nature of work (e.g., the dynamic requirements of occupations), lack of empirically informed models of key microlevel processes (e.g., skill substitution and human-machine complementarity), and insufficient understanding of how cognitive technologies interact with broader economic dynamics and institutional mechanisms (e.g., urban migration and international trade policy). Overcoming these barriers requires improvements in the longitudinal and spatial resolution of data, as well as refinements to data on workplace skills. These improvements will enable multidisciplinary research to quantitatively monitor and predict the complex evolution of work in tandem with technological progress. Finally, given the fundamental uncertainty in predicting technological change, we recommend developing a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior.

An evaluation of the Paycheck Protection Program using administrative payroll microdata.

The Paycheck Protection Program (PPP), a principal element of the fiscal stimulus enacted by Congress in response to the COVID-19 economic shock, was intended to assist small businesses to maintain employment and wages during the crisis, as well as cover other expenses. We use high-frequency administrative payroll data from ADP-one of the world's largest payroll processing firms-to estimate the causal effect of the PPP on the evolution of employment at PPP-eligible firms relative to PPP-ineligible firms, where eligibility is determined by industry-specific firm-size cutoffs. Our estimates indicate that the PPP boosted employment at eligible firms by between 2 percent to 5 percent at its peak effect around mid-May 2020. The boost to employment waned thereafter and ranged from no effect to a 3 percent boost at the end of 2020. Our estimates imply that employers retained an additional 3.6 million jobs as of mid-May 2020, and 1.4 million jobs at the end of 2020, as a consequence of PPP. The estimated cost per year of employment retained was $ 169 , 000 to $ 258 , 000 , equal to 3.4 to 5.2 times median earnings.

Males at the Tails: How Socioeconomic Status Shapes the Gender Gap.

We document that the female advantage in childhood behavioural and academic outcomes is driven by gender gaps at the extremes of the outcome distribution. Using unconditional quantile regression, we show that family socioeconomic status particularly influences boys' relative to girls' outcomes at the lower tails of the outcome distribution, precisely where gender gaps are most pronounced. These relationships are not explained by school or neighbourhood factors, or parents' differential treatment of boys. The disproportionate effect of socioeconomic status on boys at the tails substantially contributes to the gender gap in high school dropout.

Skills, education, and the rise of earnings inequality among the "other 99 percent".

The singular focus of public debate on the "top 1 percent" of households overlooks the component of earnings inequality that is arguably most consequential for the "other 99 percent" of citizens: the dramatic growth in the wage premium associated with higher education and cognitive ability. This Review documents the central role of both the supply and demand for skills in shaping inequality, discusses why skill demands have persistently risen in industrialized countries, and considers the economic value of inequality alongside its potential social costs. I conclude by highlighting the constructive role for public policy in fostering skills formation and preserving economic mobility.