This visualization, A Roadmap for Growing Good Jobs, intends to show that tailored data can help cities drive dynamic growth that also creates opportunity for the local workforce. The methods underlying our analysis are designed to accommodate a wide range of regional needs and goals. However, these insights and strategies are not meant to be prescriptive. Rather, they present a set of options to inform regional development based on different priorities and tailored to the strengths of each city. Local contexts and priorities are crucial to meaningful interpretations of the data. [Note: contains copyrighted material].
Advancing technologies are increasingly able to fully or partially automate job tasks. These technologies range from robotics to machine learning and other forms of artificial intelligence, and are being adopted across many sectors of the economy. Applications range from selecting job applicants for interviewing, picking orders in a warehouse, interpreting X-rays to diagnose disease, and automated customer service. These developments have raised concern that workers are being displaced by advancing automation technology. Indeed, over 18 recent studies predict job losses from new automation technologies, including some predictions of massive job losses (Winick 2018). A large literature on worker displacement suggests that the effects of such developments could be dire: individual workers subject to plant closings and mass layoffs experience reduced employment probabilities and wage reductions, leading to long-term earnings losses, as well as reductions in consumption and worse health outcomes. Concerns about these effects of automation have led some commentators to call for policies to directly combat mass unemployment, such as a Universal Basic Income.
But is this right? At a time when many firms are investing in automation, the unemployment rate is at historic lows. Low unemployment might seem hard to reconcile with apocalyptic predictions about mass unemployment. This paper reviews the evidence from recent studies and reports on a new paper we have written, “Automatic Reaction: What happens to workers at firms that automate” (Bessen et al. 2019). This paper is the first to take a look at what actually happens to those workers. We build on some of the findings in order to draw the implications for policy. [Note: contains copyrighted material].
The apprenticeship movement is reshaping skills, policies, and programs in the United States at a critical moment in our country’s history. This reader offers a chorus of voices emanating from different countries and populations, echoing commitment to bright, sustainable workforce futures through a well-crafted approach to this talent development model. The collected chapters and vignettes address questions for businesses of all sizes, community-based organizations, and schools looking for a way to build strong pipelines of skilled labor, stimulate economies in struggling regions, provide options for adults seeking career changes, and stimulate engagement for students filled with curiosity about the promise of work-based learning. We endeavored to shatter myths, remove barriers, and erase fears of attempting apprenticeship, particularly for small and medium-size businesses and parents who are naturally concerned about meaningful and gainful career choices for their children. This reader intends to show the possibilities modern apprenticeship affords contemporary societies and to inspire many to reframe the boundaries of traditional thinking. [Note: contains copyrighted material].
Long run labor market trends in the American economy pose significant challenges. Growth in real money wages has been slow, with the most rapid gains taking place among workers at the top of the earnings distribution. Labor force participation and employment rates have been falling. Reduced labor force participation and obsolescence of workers’ skills weigh down GDP growth, with predictable negative repercussions for living standards and federal revenue. These trends suggest a need for a major revamping of policies and programs that prepare people for careers and retrain people who must change careers. The authors focus on three major policy initiatives to maximize worker training to bolster productivity and wages: Improve access to in-demand training; strengthen connections between career and technical education and training and employer needs; and build a robust apprenticeship system that emphasizes learning by doing in a context that involves apprentice contributions to production, and culminates in a respected occupational credential. This new system goes beyond the “academic-only” approach commonly pursued in the US and should match individual interests, aptitudes, and skills to in-demand jobs and make new training investments that are cost effective and valued by employers. [Note: contains copyrighted material].
Three work-family supports—paid leave, workplace flexibility and control, and support for child care—are crucial to the ability of parents to effectively manage work and family. This research used national survey data to examine patterns in working parents’ access to these supports; variations in access by parental characteristics like socioeconomic advantage; and the need for these work-family supports among working parents.Three work-family supports—paid leave, workplace flexibility and control, and support for child care—are crucial to the ability of parents to effectively manage work and family. This research used national survey data to examine patterns in working parents’ access to these supports; variations in access by parental characteristics like socioeconomic advantage; and the need for these work-family supports among working parents. [Note: contains copyrighted material].
Since 2009, New York City has implemented the Jobs-Plus
program to increase employment and earnings public housing residents. The
program is modeled after a successful federal demonstration from the 1990s that
combines employment services, financial incentives, and community supports to
promote work. The Urban Institute evaluation of the program combined interviews
and focus groups with staff and participants with analysis of data on Jobs-Plus
participation, public housing residency, and quarterly earnings before and
after implementation. We concluded that the program provided personal,
culturally competent employment services and cultivate a network of employers
interested in hiring Jobs-Plus participants. Among participants, Jobs-Plus
increased employment by 12 percentage points and quarterly earnings by $497.
Our evaluation found mixed evidence that the program slightly improved
employment rates for residents of the targeted developments and found no
evidence that it improved earnings. We attribute this lack of impact primarily
to two factors. First, the Jobs-Plus providers might not have assisted a high
enough proportion of residents to change overall trends within the
developments. Second, our evaluation could not capture the program’s impact on
the many participants who lived in the targeted developments but were not
officially listed on the lease and were thus not included in our data. [Note: contains copyrighted material].
This is a qualitative study of low-wage workers in two
Minnesota communities who recently experienced either voluntary or involuntary
job separation. The study confronts a false dichotomy that people are either
working or on public assistance. The study analyzes workers’ experiences in
low-wage, unstable jobs, reasons for separating from jobs, and the roles public
assistance and other supports play in their lives. The study offers key
insights from workers themselves on how jobs and assistance programs may be
improved to help them achieve greater stability and economic security. [Note: contains copyrighted material].