We present a meta-analysis of impact estimates from over 200 recent econometric evaluations of active labor market programs from around the world. We classify estimates by program type and participant group, and distinguish between three different post-program time horizons. Using meta-analytic models for the effect size of a given estimate (for studies that model the probability of employment) and for the sign and significance of the estimate (for all the studies in our sample) we conclude that: (1) average impacts are close to zero in the short run, but become more positive 2-3 years after completion of the program; (2) the time profile of impacts varies by type of program, with larger gains for programs that emphasize human capital accumulation; (3) there is systematic heterogeneity across participant groups, with larger impacts for females and participants who enter from long term unemployment; (4) active labor market programs are more likely to show positive impacts in a recession.

We summarize the estimates from over 200 recent studies of active labor market programs. We classify the estimates by type of program and participant group, and distinguish between three different post-program time horizons. Using regression models for the estimated program effect (for studies that model the probability of employment) and for the sign and significance of the estimated effect (for all the studies in our sample) we conclude that: (1) average impacts are close to zero in the short run, but become more positive 2-3 years after completion of the program; (2) the time profile of impacts varies by type of program, with larger average gains for programs that emphasize human capital accumulation; (3) there is systematic heterogeneity across participant groups, with larger impacts for females and participants who enter from long term unemployment; (4) active labor market programs are more likely to show positive impacts in a recession.

This paper presents a meta-analysis of recent microeconometric evaluations of active labor market policies. Our sample contains 199 separate "program estimates"--Estimates of the impact of a particular program on a specific subgroup of participants - drawn from 97 studies conducted between 1995 and 2007. For about one-half of the sample we have both a short-term program estimate (for a one-year post-program horizon) and a medium- or long-term estimate (for 2 or 3 year horizons). We categorize the estimated post-program impacts as significantly positive, insignificant, or significantly negative. By this criterion we find that job search assistance programs are more likely to yield positive impacts, whereas public sector employment programs are less likely. Classroom and on-the-job training programs yield relatively positive impacts in the medium term, although in the short-term these programs often have insignificant or negative impacts. We also find that the outcome variable used to measure program impact matters. In particular, studies based on registered unemployment are more likely to yield positive program impacts than those based on other outcomes (like employment or earnings). On the other hand, neither the publication status of a study nor the use of a randomized design is related to the sign or significance of the corresponding program estimate. Finally, we use a subset of studies that focus on post-program employment to compare meta-analytic models for the "effect size" of a program estimate with models for the sign and significance of the estimated program effect. We find that the two approaches lead to very similar conclusions about the determinants of program impact.

This paper provides a meta-analysis of microeconometric evaluation studies on the effectiveness of active labor market policies. The analysis is built upon a systematically assembled data set of causal impact estimates from 57 experimental and quasi-experimental studies, providing 654 estimates published between January 1990 and December 2017. We distinguish between the short and longer term impacts in our analysis; at 6, 12, 24, and 36 months after program start. After correcting for publication bias and country-specific macroeconomic characteristics, subsidized labor and public employment programs have negative short-term impacts, which gradually turn positive in the longer run. Schemes with enhanced services including job-search assistance and training programs do not have these negative short-term effects, and stay positive from 6 until 36 months after program start.

In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

Jobs provide higher earnings and better benefits as countries grow, but they are also a driver of development. Poverty falls as people work their way out of hardship and as jobs empowering women lead to greater investments in children. Efficiency increases as workers get better at what they do, as more productive jobs appear, and less productive ones disappear. Societies flourish as jobs bring together people from different ethnic and social backgrounds and provide alternatives to conflict. Jobs are thus more than a byproduct of economic growth. They are transformational —they are what we earn, what we do, and even who we are. High unemployment and unmet job expectations among youth are the most immediate concerns. But in many developing countries, where farming and self-employment are prevalent and safety nets are modest are best, unemployment rates can be low. In these countries, growth is seldom jobless. Most of their poor work long hours but simply cannot make ends meet. And the violation of basic rights is not uncommon. Therefore, the number of jobs is not all that matters: jobs with high development payoffs are needed. Confronted with these challenges, policy makers ask difficult questions. Should countries build their development strategies around growth, or should they focus on jobs? Can entrepreneurship be fostered, especially among the many microenterprises in developing countries, or are entrepreneurs born? Are greater investments in education and training a prerequisite for employability, or can skills be built through jobs? In times of major crises and structural shifts, should jobs, not just workers, be protected? And is there a risk that policies supporting job creation in one country will come at the expense of jobs in other countries? The World Development Report 2013: Jobs offers answers to these and other difficult questions by looking at jobs as drivers of development—not as derived labor demand—and by considering all types of jobs—not just formal wage employment. The Report provides a framework that cuts across sectors and shows that the best policy responses vary across countries, depending on their levels of development, endowments, demography, and institutions. Policy fundamentals matter in all cases, as they enable a vibrant private sector, the source of most jobs in the world. Labor policies can help as well, even if they are less critical than is often assumed. Development policies, from making smallholder farming viable to fostering functional cities to engaging in global markets, hold the key to success.