Active Labor Market Policy Evaluations – A Meta-analysis

This paper presents a meta-analysis of recent microeconometric evaluations of active labor market policies. Our sample consists of 199 program estimates drawn from 97 studies conducted between 1995 and 2007. In about one-half of these cases we have both a short-term impact estimate (for a one-year postprogram horizon) and a medium-term estimate (two-year horizon).We characterize the program estimates according to the type and duration of the program, the characteristics of the participants, and the evaluation methodology. Heterogeneity in all three dimensions affects the likelihood that an impact estimate is significantly positive, significantly negative, or statistically insignificant. Comparing program types, subsidized public sector employment programs have the least favorable impact estimates. Job search assistance programs have relatively favorable short-run impacts, whereas classroom and on-the-job training programs tend to show better outcomes in the mediumrun than the short-run. Programs for youths are less likely to yield positive impacts than untargeted programs, but there are no large or systematic differences by gender. Methodologically, we find that the outcome variable used to measure program effectiveness matters. Evaluations based on registered unemployment durations are more likely to show favorable short-term impacts. Controlling for the outcome measure, and the type of program and participants, we find that experimental and non-experimental studies have similar fractions of significant negative and significant positive impact estimates, suggesting that the research designs used in recent non-experimental evaluations are unbiased.Meta-analysis, active labor market policy, program evaluation

Active Labor Market Policy Evaluations: A Meta-Analysis

This paper presents a meta-analysis of recent microeconometric evaluations of active labor market policies. Our sample consists of 199 program estimates drawn from 97 studies conducted between 1995 and 2007. In about one-half of these cases we have both a short-term impact estimate (for a one-year post-program horizon) and a medium-term estimate (two-year horizon). We characterize the program estimates according to the type and duration of the program, the characteristics of the participants, and the evaluation methodology. Heterogeneity in all three dimensions affects the likelihood that an impact estimate is significantly positive, significantly negative, or statistically insignificant. Comparing program types, subsidized public sector employment programs have the least favorable impact estimates. Job search assistance programs have relatively favorable short-run impacts, whereas classroom and on-the-job training programs tend to show better outcomes in the medium-run than the short-run. Programs for youths are less likely to yield positive impacts than untargeted programs, but there are no large or systematic differences by gender. Methodologically, we find that the outcome variable used to measure program effectiveness matters. Evaluations based on registered unemployment durations are more likely to show favorable short-term impacts. Controlling for the outcome measure, and the type of program and participants, we find that experimental and non-experimental studies have similar fractions of significant negative and significant positive impact estimates, suggesting that the research designs used in recent non-experimental evaluations are unbiased.active labor market policy, program evaluation, meta-analysis

Active Labor Market Policy Evaluations: A Meta-analysis

This paper presents a meta-analysis of recent microeconometric evaluations of active labor market policies. Our sample consists of 199 program estimates drawn from 97 studies conducted between 1995 and 2007. In about one-half of these cases we have both a short-term impact estimate (for a one-year post-program horizon) and a medium-term estimate (two-year horizon). We characterize the program estimates according to the type and duration of the program, the characteristics of the participants, and the evaluation methodology. Heterogeneity in all three dimensions affects the likelihood that an impact estimate is significantly positive, significantly negative, or statistically insignificant. Comparing program types, subsidized public sector employment programs have the least favorable impact estimates. Job search assistance programs have relatively favorable short-run impacts, whereas classroom and on-the-job training programs tend to show better outcomes in the medium-run than the short-run. Programs for youths are less likely to yield positive impacts than untargeted programs, but there are no large or systematic differences by gender. Methodologically, we find that the outcome variable used to measure program effectiveness matters. Evaluations based on registered unemployment durations are more likely to show favorable short-term impacts. Controlling for the outcome measure, and the type of program and participants, we find that experimental and non-experimental studies have similar fractions of significant negative and significant positive impact estimates, suggesting that the research designs used in recent non-experimental evaluations are unbiased.

Spring waters as an indicator of nitrate and pesticide pollution of rural watercourses from nonpoint sources: results of repeated monitoring campaigns since the early 2000s in the low mountain landscape of Saarland, Germany

Background: Spring waters, which are fed mainly by near-surface groundwater, provide a comprehensive picture of emissions of nitrate and other pollutants caused by the type and intensity of land use in the topographic catchment area. One aim of this study was to develop a model for predicting the contribution of nonpoint-source inputs to the nitrate load of small- and medium-sized watercourses based on the type of agricultural use in the catchment areas. Methods: Fifty-five springs in the German Land Saarland and the adjacent Rhineland-Palatinate were monitored for pollutants during three monitoring periods of at least 12 months between 2000 and 2019. The catchment areas are representative of the natural regions in the study area and are outside the influence of settlements and other developments. In addition to nitrate and other physicochemical parameters, 25 agriculturally impacted springs were screened for pesticides and their metabolites. Results: Since the first measurements were taken in 2000, the vast majority of agriculturally impacted springs have consistently exhibited high nitrate concentrations of between 20 and 40 mg/L NO3−. Springs not influenced by agriculture contained an average of 3.6 mg/L nitrate. The extreme values observed in the early 2000s decreased to the limit value of 50 mg/L, but most of the springs with moderate levels exhibited an increase to approximately 30 mg/L. The number of pesticidal agents detected in the spring waters demonstrated a clear correlation with the watershed’s amount of arable land and the nitrate content detected. Moreover, we found a highly significant correlation between nitrate content and the share of cropland in the catchment area. From this, we derived a regression model that could be used to quantify the share of nitrate pollution attributable to nonpoint-source inputs for larger catchments in the region under investigation. Conclusion: Nitrate discharged from farmland has not decreased since the European Water Framework Directive (EU WFD) entered into force. At the historically extremely heavily polluted sites, measures have been implemented that have led to compliance with the limit value of the Nitrate Directive. However, below this limit, nitrate levels have increased significantly almost everywhere in the last two decades. We therefore recommend introducing stricter requirements for official water pollution control, such as the marine ecological target value

Polyakov loop distributions near deconfinement in SU(2) lattice gauge theory

Engels J, Fingberg J, Weber M. Polyakov loop distributions near deconfinement in SU(2) lattice gauge theory. Zeitschrift für Physik, C: Particles and Fields. 1988;41(3):513-519.The distribution function of the Polyakov loop is investigated on a 163×3 lattice in the neighbourhood of the deconfinement transition of SU(2) gauge theory. We find, that well above the transition the distribution is a Gaussian; when the coupling approaches the critical point it is modified due to phase flip attempts of the system. Corresponding distributions for the plaquettes remain, however, Gaussian. For one coupling close to the transition we study the distributions on 83, 123 and 183×4 lattices and show that strong finite size effects are present. Using the maximum values of the Gaussian parts of the distributions we construct a more physical (and therefore scaling) order parameter whose critical exponent is in excellent agreement with the universality hypothesis

Active Labor Market Policy Evaluations: A Meta-Analysis

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.