A few hundred thousand federal employees earn relatively low wages, and their numbers vary significantly across states.
From the abstract:
We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added (of an industry or economy) and may also reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production—due to automation and new tasks—can be inferred from industry-level data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.
From the summary:
This is the first report of a Keystone Research Center project on the “Future of Work.” The aim is to identify public policies that could help ensure that the application and diffusion of artificial intelligence (AI) over the next several decades fosters an economy in which Americans generally thrive. The project is motivated, in part, by concern that the opposite could occur: that AI will exacerbate the already high levels of income and wealth inequality in the United States. Our most important conclusion is that AI need not make our inequalities more severe. Creative public policies could lead to an AI economy “that works for the many, not just the few.”
The study design has been informed by the two principal authors’ experience at the one-time Office of Technology Assessment (OTA) of the US Congress. To guide the undertaking and provide feedback on its products, we recruited an advisory panel of nationally recognized academics and representatives of think tanks and the corporate, labor, and non-profit sectors. The project methodology combines interviews with technology experts, policy analysis, synthesis of research literature and, still to come, sectoral studies.
This first report contains three main parts. (1) Following an introduction, Sections II-IV contain an analysis of AI’s likely impacts through the lens of technology. Section II reviews past impacts of innovations including robotics and information technology on the economy and jobs. Section III looks at AI itself, how it does and does not go beyond previous technologies and substitute for human capacities and intelligence. Section IV explores the difficulties of predicting AI’s job impacts. (2) Section V, “The Plight of the American Worker,” considers the labor market context in which AI systems will spread and the roots of the economic inequality from which the nation suffers. (3) Section VI surveys policies that could influence inequality and the distribution of the benefits of productivity growth as AI spreads.
From the summary:
At first, technologists issued dystopian alarms about the power of automation and artificial intelligence (AI) to destroy jobs. Then came a correction, with a wave of reassurances. Now, the discourse appears to be arriving at a more complicated understanding, suggesting that automation will bring neither apocalypse nor utopia, but instead both benefits and stress alike. Such is the ambiguous and sometimes disembodied nature of the “future of work” discussion.
Hence the analysis presented here. Intended to bring often-inscrutable trends down to earth, the following report develops both backward and forward-looking analyses of the impacts of automation over the years 1980 to 2016 and 2016 to 2030 to assess past and upcoming trends as they affect both people and communities in the United States.
The report focuses on areas of potential occupational change rather than net employment losses or gains. Special attention is applied to digging beneath national top-line statistics to explore industry, geographical, and demographic variations. Finally, the report concludes by suggesting a comprehensive response framework for national and state-local policymakers.
Source: Gad Levanon, Frank Steemers, The Conference Board, December 2018
From the abstract:
The threat of labor shortages is more acute in blue-collar and low-pay services occupations than in more highly educated white-collar occupations, the exact opposite of the prevailing trends in recent decades. We expect that by the end of 2019, the labor market will be historically tight. Industries that employ large shares of blue-collar workers, such as agriculture, mining, utilities, construction, manufacturing, transportation, accommodation and food services, repair, maintenance, and personal care services, are strongly affected by rising wages and shrinking supply. While the labor white-collar market is also tight, wage growth for the 40 percent of workers in management, professional, and related occupations is slow to accelerate. Sales and office workers, most of whom do not have a bachelor’s degree, are in shorter supply than management and professional workers.
Blue Collar Worker Shortage Turns U.S. Labor Market on Its Head
Source: Rich Miller, Bloomberg, December 13, 2018
How can well-structured and effective workforce programs and policies result in better economic outcomes for individuals, businesses, and communities?
Explore contemporary research, best practices, and resources from more than 100 authors in the book Investing in America’s Workforce: Improving Outcomes for Workers and Employers.
The book is divided into three volumes: Investing in Workers, Investing in Work, and Investing in Systems for Employment Opportunity. Within each volume are discrete sections made up of chapters that identify specific workforce development programs and policies that provide positive returns to society, to employers, and to job seekers. Download the three volumes and individual chapters below.
Note: The policies and practices presented in the book are intended to spur innovative thinking that results in context-specific solutions. The perspectives are not intended as an endorsement from the Federal Reserve System or its partnering institutions.
VOLUME 1: INVESTING IN WORKERS
Front Matter and Table of Contents
Foreword: The Evolving U.S. Labor Market by Patrick T. Harker
Introduction: Investing in America’s Workforce by Stuart Andreason, Todd Greene, Heath Prince, and Carl E. Van Horn
– Building Employer Investment in Workforce Development
– Investing in Undervalued Human Capital
– Investing in Historically Black Colleges and Universities
– Investing in Workers with Different Abilities
– Investing in Workers of the Future
VOLUME 2: INVESTING IN WORK
Front Matter and Table of Contents
Introduction: Investing in Work by Prabal Chakrabarti and Jeffrey Fuhrer
– Investing in Opportunities to Create Good Jobs
– Investing in Work and Wealth
– Investing in Rural Work
– Investing in Human Capital to Support Local Economic Development
VOLUME 3: INVESTING IN SYSTEMS FOR EMPLOYMENT OPPORTUNITY
Front Matter and Table of Contents
Introduction: Investing in Systems for Employment Opportunity by Stuart Andreason and Alexander Ruder
– Financial Innovations in Workforce Development
– Government Investment in Workforce Development
– Investing in Technology
– Investing in Skills and Credentials
– Investing in Regional Workforce Development Systems
– Appendix: Investing in America’s Workforce
Labor force participation among U.S. men and women ages 25 to 54 has been declining for nearly 20 years, a stark contrast with rising participation in Canada over this period. Three-fourths of the difference between the two countries can be explained by the growing gap in labor force attachment of women. A key factor is the extensive parental leave policies in Canada. If the United States could reverse the trend in participation of prime-age women to match Canada, it would see 5 million additional prime-age workers join the labor force.
The decline in labor force participation of U.S. men and women ages 25 to 54 stands in stark contrast with other industrialized nations, where participation rates for prime-age workers have increased over time. In this Economic Letter, we show how labor force participation rates have diverged for men and women in the United States and Canada. We find that three-fourths of the difference in participation between the two countries can be explained by the growing gap in labor force attachment of women. We discuss how employment and social policies in Canada have made it easier for women to remain in the labor force while raising children. Our findings suggest that policy interventions to reduce the structural barriers that keep many women on the sidelines could bring millions of prime-age Americans into the labor force.
Source: Shannon Brobst, Regional Financial Review, May 2018
Eighteen U.S. states and 20 cities rang in 2018 with increases in their minimum wage, bringing back into the spotlight the debate about whether to raise the federal minimum, which has remained at $7.25 since 2009 (see Chart 1). The question of whether it should be increased receives many different answers from Republicans, Democrats, economists and non-professional observers. Some argue that increasing the cost of labor hurts the economy because it could lead to jobs cuts for low-paid workers. Raising the minimum wage increases businesses’ labor costs, and thus, the cost of producing a good or service. Higher production costs may cause employers to lay off workers in order to contain costs and remain profitable, and could cause marginally profitable small or struggling businesses to close. Others counter this argument stating that a higher minimum wage helps the economy by boosting incomes and does not materially affect employment. This paper examines the positive and negative effects of raising the minimum wage from $7.25 to $12 and $15 in Pennsylvania and discusses policy implications at the local and federal levels.
Source: Marios Michaelides, Peter Mueser, Journal of Policy Analysis and Management, Volume 37, Issue 3, Summer 2018
From the abstract:
We examine an experimental‐design reemployment program implemented in Nevada during the Great Recession that required Unemployment Insurance (UI) recipients to: (1) undergo an eligibility review to confirm they were qualified for benefits and actively searching for work and, if deemed eligible, (2) receive job‐counseling services. Our results show that the program expedited participant exit from UI, produced UI savings that exceeded program costs, and improved participant employment outcomes. Analyses of program effects on the UI exit likelihood show that the program’s effects are partly associated with increased participant exit up through the time when program activities were scheduled, reflecting voluntary exit of participants from UI to avoid program activities and disqualifications of participants who failed to meet eligibility requirements. In addition, the program induced substantial participant exit from UI in the period after participants fulfilled requirements and their interactions with the program had ended, suggesting that the job‐counseling services offered by the program may have helped participants to conduct more effective job searches. Our findings provide evidence that reemployment programs that combine an eligibility review with mandatory participation in job‐search services can be effective during recessions.
This article uses data from the Current Population Survey to examine the state of the U.S. labor market 10 years after the start of the Great Recession of 2007–09. By December 2017, unemployment rates had returned to prerecession lows for people of all ages, genders, major race and ethnicity groups, and levels of educational attainment. However, the long-term decline in labor force participation continued during this recovery, while long-term unemployment and involuntary part-time employment remained elevated.