We examine the determinants of the within-industry decline of the labor share, using industry-level annual data for 25 OECD countries, 20 business-sector industries and covering up to 28 years. We find that total factor productivity growth—which captures (albeit imprecisely) capital-augmenting or labor-replacing technical change—and capital deepening jointly account for as much as 80 % of the within-industry contraction of the labor share. We also find that another factor explaining the aggregate decline of the labor share is the increased international competition, with higher import penetration causing a contraction of the share of labour-intensive industries in total value added. However, the fraction of the drop of the labor share explained by international competition remains limited.

This paper links data on establishments and individuals to analyze the role of establishments in the increase in inequality that has become a central topic in economic analysis and policy debate. It decomposes changes in the variance of ln earnings among individuals into the part due to changes in earnings among establishments and the part due to changes in earnings within-establishments and finds that much of the 1970s-2010s increase in earnings inequality results from increased dispersion of the earnings among the establishments where individuals work. It also shows that the divergence of establishment earnings occurred within and across industries and was associated with increased variance of revenues per worker. Our results direct attention to the fundamental role of establishment-level pay setting and economic adjustments in earnings inequality.

This chapter considers means-tested employment and training programs in the United States. We focus in particular on large, means-tested federal programs, including the Job Training Partnership Act (JTPA), its successor the Workforce Investment Act (WIA), that program's recent replacement, the Workforce Innovation and Opportunity Act (WIOA), the long-running Job Corps program, and the Trade Adjustment Assistance (TAA) program. The first part of the chapter provides details on program history, organization, expenditures, eligibility rules, services, and participant characteristics. In the second part of the chapter, we discuss the applied econometric methods typically used to evaluate these programs, which in the United States means primarily social experiments and methods such as matching that rely on an assumption of "selection on observed variables." The third part of the chapter reviews the literature evaluating these programs, highlighting both methodological and substantive lessons learned as well as open questions. The fourth part of the chapter considers what lessons the evaluation literature provides on program operation, especially how to best allocate particular services to particular participants. The final section concludes with the big picture lessons from this literature and discussion of promising directions for future research.

Using a country-industry panel dataset (EUKLEMS) we uncover a robust empirical regularity, namely that high risk innovative sectors are relatively smaller in countries with strict employment protection legislation (EPL). To understand the mechanism, we develop a two-sector matching model where firms endogenously choose between a safe technology with known productivity and a risky technology with productivity subject to sizeable shocks. Strict EPL makes the risky technology relatively less attractive because it is more costly to shed workers upon receiving a low productivity draw. We calibrate the model using a variety of aggregate, industry and micro-level data sources. We then simulate the model to reflect both the observed differences across countries in EPL and the observed increase since the mid1990s in the variance of firm performance associated with the adoption of information and communication technology. The simulations produce a differential response to the arrival of risky technology between low- and high-EPL countries that coincides with the findings in the data. The described mechanism can explain a considerable portion of the slowdown in productivity in the EU relative to the US since 1995.

This report considers the current situation of the UK Education sector, the challenges it faces over the medium-term and its implications for skills. The intention is to provide a summary of the extent to which the performance challenges faced by the sector can be addressed through skill development and thereby bring about growth and contribute to the recovery of the UK economy.

This report presents a framework - Skills Toward Employment and Productivity (STEP), that provides a simple yet comprehensive way to look at skills development. It brings together research evidence and practical experience from a range of areas-from research on the determinants of early childhood development and learning outcomes, to policy experience with the reform of vocational and technical education systems and labor markets-and provides a set of powerful messages to policymakers, researchers, and practitioners. The report's emphasis on performance measurement and benchmarking, policy and program evaluation, and cross-sectoral approaches focusing on individuals throughout their lifecycle provides a solid platform for developing countries to start exploring reforms

Technological advances are generating fears of a jobless future. At the same time, major economies are seeing historically low unemployment rates and wage growth is puzzlingly low. Find out how technology is changing the nature of work, not eliminating it. This is the third report in Barclays' Impact Series, in which we analyse the wide-ranging impacts of technological advancement on how people work today, and possibly will work in the future.

Recent debates about the future of jobs have mainly focused on whether or not they are at risk of automation (Arntz et. Al., 2016; Frey and Osborne, 2017; McKinsey, 2017; PwC, 2017). Studies have generally minimised the potential effects of automation on job creation, and have tended to ignore other relevant trends, including globalisation, population ageing, urbanisation, and the rise of the green economy. In this study we use a novel and comprehensive method to map out how employment is likely to change, and the implications for skills. We show both what we can expect, and where we should be uncertain. We also show likely dynamics in different parts of the labour market - from sectors like food and health to manufacturing. We find that education, health care, and wider public sector occupations are likely to grow. We also explain why some low-skilled jobs, in fields like construction and agriculture, are less likely to suffer poor labour market outcomes than has been assumed in the past. More generally, we shine a light on the skills that are likely to be in greater demand, including interpersonal skills, higher-order cognitive skills, and systems skills. Unlike other recent studies, the method also makes it possible to predict with some confidence what kinds of new jobs may come into existence. The study challenges the false alarmism that contributes to a culture of risk aversion and holds back technology adoption, innovation, and growth; this matters particularly to countries like the US and the UK, which already face structural productivity problems (Atkinson and Wu, 2017; Shiller, 2017). Crucially, through the report, we point to the actions that educators, policymakers and individuals can take to better prepare themselves for the future.

This publication reports the findings from a combined quantitative and qualitative study of Australian working women, aged under 40. It draws together four separate data sources: a nationally representative online survey of (n=2,109) working women under 40; a smaller comparative survey of (n=502) working men under 40; additional boosted survey sample among (n=53) Aboriginal and Torres Strait Islander working women aged under 40; and the findings from five focus groups of (n=41) working women under 40. Quantitative fieldwork was conducted between September and October, while qualitative fieldwork was conducted in November 2017. At the time of being surveyed: over half of the women in the sample (55%) were working full-time or part-time for an employer, a fifth (19%) were working on a casual, freelance or short-term contract basis and 6% were self-employed. Half of the women (55%) were working in the private sector, 28% in the public sector and 6% for not-for-profit organisations. Over half (56%) were working in four industry sectors: retail trade, healthcare and social assistance, education and training, and accommodation and food services.