Search

We investigate the effectiveness of three different job-search and training programmes for German long-term unemployed persons. On the basis of an extensive administrative data set, we evaluated the effects of those programmes on various levels of aggregation using Causal Machine Learning. We found participants to benefit from the investigated programmes with placement services to be most effective. Effects are realised quickly and are long-lasting for any programme. While the effects are rather homogenous for men, we found differential effects for women in various characteristics. Women benefit in particular when local labour market conditions improve. Regarding the allocation mechanism of the unemployed to the different programmes, we found the observed allocation to be as effective as a random allocation. Therefore, we propose data-driven rules for the allocation of the unemployed to the respective labour market programmes that would improve the status-quo.

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a radius matching framework. Considering two popular methods, the results are ambiguous: We find that using LASSO based logit models to estimate the propensity score delivers more credible results than conventional methods in small and medium sized high dimensional datasets. However, the usage of Random Forests to estimate the propensity score may lead to a deterioration of the performance in situations with a low treatment share. The application reveals a positive effect of the training programme on days in employment for long-term unemployed. While the choice of the 'first stage' is highly relevant for settings with low number of observations and few treated, machine learning and conventional estimation becomes more similar in larger samples and higher treatment shares. Propensity Score Matching-Schätzer sind ein zentrales Tool, um Wirkungen aktiver Arbeitsmarktpolitik mit Individualdaten zu analysieren. Diese Studie untersucht, inwieweit Machine-Learning Algorithmen zur Schätzung des Propensity Score zu einer verbesserten Schätzung von durchschnittlichen Maßnahmeteilnahmeeffekten für die Teilnehmenden führt, wenn Radius-Matching verwendet wird. Es werden zwei gängige Methoden verwendet und die Analyse kommt zu keinem eindeutigen Ergebnis: Die Anwendung des LASSO auf der Basis von Logit-Modellen zur Schätzung des Propensity Score liefert überzeugendere Befunde als konventionelle Schätzmethoden, wenn kleine oder mittelgroße Datensätze verwendet werden. Wenn hingegen Random Forests zur Schätzung des Propensity Score verwendet werden, kann unter Verwendung von Stichproben mit einem geringen Anteil von Teilnehmenden das Gegenteil der Fall sein. Den Schätzergebnisse zufolge, führen die untersuchten Schulungsmaßnahmen dazu, dass die Tage in Beschäftigung nach Förderbeginn für die langzeitarbeitslosen Schulungsteilnehmenden höher ausfallen als ohne diese Förderung. Während bei Stichproben mit einer geringen Anzahl von Beobachtungen und einem kleinen Anteil von Maßnahmeteilnehmenden die Wahl des Schätzers für den Propensity Score für die Ergebnisse hoch relevant ist, sind die Resultate von Machine-Learning- und konventionellen Schätzungen bei einer hohen Anzahl von Beobachtungen und einem relativen hohen Anteil von Maßnahmeteilnehmenden ähnlicher.

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find substantial heterogeneity across programmes and unemployed. Simulations show that “black-box” rules that reassign unemployed to programmes that maximise estimated individual gains can considerably improve effectiveness: up to 20% more (less) time spent in (un)employment within a 30 months window. A shallow policy tree delivers a simple rule that realizes about 70% of this gain.

Uncovering the heterogeneity of causal effects of policies and business decisions at various levels of granularity provides substantial value to decision makers. This paper develops new estimation and inference procedures for multiple treatment models in a selection-on-observables frame-work by modifying the Causal Forest approach suggested by Wager and Athey (2018). The new estimators have desirable theoretical and computational properties for various aggregation levels of the causal effects. An Empirical Monte Carlo study shows that they may outperform previously suggested estimators. Inference tends to be accurate for effects relating to larger groups and conservative for effects relating to fine levels of granularity. An application to the evaluation of an active labour market programme shows the value of the new methods for applied research.

We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-experimental causal empirical models with Lasso-type estimators. The empirical analyses are based on rich administrative data from Swiss social security records. We find considerable heterogeneities only during the first six months after the start of training. Consistent with previous results of the literature, unemployed persons with fewer employment opportunities profit more from participating in these programmes. Furthermore, we also document heterogeneous employment effects by residence status. Finally, we show the potential of easy-to-implement programme participation rules for improving average employment effects of these active labour market programmes.

This paper evaluates the effect of a voucher award system for assignment into vocational training on the employment outcomes of unemployed voucher recipients in Germany, along with the causal mechanisms through which it operates. It assesses the direct effect of voucher assignment net of actual redemption, which may be driven by preference shaping/learning about (possibilities of) human capital investments or simply by costs of information gathering. Using a mediation analysis framework based on sequential conditional independence assumptions and semiparametric matching estimators, our results suggest that the negative short term and positive long term employment effects of voucher award are mainly driven by actual training participation. However, also the direct effect of just obtaining the voucher is negative in the short run. This points to potential efficiency losses of voucher award systems if individuals decide not to redeem, as employment chances are lower than under non-award in the short run and under redemption in the long run, making non-redemption the least attractive option.

We survey the literature on the link of labour market related outcomes to individ-ual physical activity and sports participation. The first part of the survey is devoted to the individual participation decision and is based on papers from various disciplines. The sec-ond part summarises parts of the epidemiological literature on health effects and the eco-nomic literature on the labour market effects as well as on the effects on well-being and so-cial capital. Somewhat surprisingly, at least for studies in empirical economics, all the papers seem to agree that individual leisure sports participation and physical activity has positive effects for adults.

Based on new, exceptionally informative and large German linked employer-employee administrative data, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programs for the unemployed. Such biases would lead to false policy conclusions about the cost-effectiveness of these expensive policies. Using newly developed Empirical Monte Carlo Study methods, we find that besides standard personal characteristics, information on individual health and firm characteristics of the last employer are particularly important for selection correction. Moreover, it is important to account for past performance on the labour market in a very detailed and flexible way. Information on job search behaviour, timing of unemployment and program start, as well as detailed regional characteristics are also relevant.

Based on a new, exceptionally informative and large German linked employer-employee administrative dataset, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programmes for the unemployed. Such biases would lead to false policy conclusions about the effectiveness of these expensive policies. Based on our preliminary findings, it seems that controlling for standard demographic variables removes already a substantial part of the potential selection bias.

In an evaluation of a job-training program, the influence of the program on the in-dividual wages is important, because it reflects the program effect on human capital. Esti-mating these effects is complicated because we observe wages only for employed individuals, and employment is itself an outcome of the program. Only usually implausible assumptions allow identifying these treatment effects. Therefore, we suggest weaker and more credible assumptions that bound various average and quantile effects. For these bounds, consistent, nonparametric estimators are proposed. In a reevaluation of a German training program, we find that a considerable improvement of the long-run potential wages of its participants.

Using exceptionally rich linked administrative and survey information on German welfare recipients we investigate the health effects of transitions from welfare to employment and of assignments to welfare-to-work programmes. Applying semi-parametric propensity score matching estimators we find that employment substantially increases (mental) health. The positive effects are mainly driven by males and individuals with bad initial health conditions and are largest for males with poor health. In contrast, the effects of welfare-to-work programmes, including subsidized jobs, are ambiguous and statistically insignificant for most outcomes. Robustness checks that include a semi-parametric instrumental variable approach do not provide reasons for concern.

"We estimate short, medium, and long-run individual labor market effects of training programs for unemployed by following program participation on a monthly basis over a ten-year period. Since analyzing the effectiveness of training over such a long period is impossible with experimental data, we use an administrative database compiled for evaluating German training programs. Based on matching estimation adapted to the various issues that arise in this particular context, we find a clear positive relation between the effectiveness of the programs and the unemployment rate over time." [authors abstract]

"We investigate the effects of the most important East German active labour market programmes on the labour market outcomes of their participants. The analysis is based on a large and informative individual database coming from administrative data sources. Using matching methods, we find that over a horizon of 2.5 years after programme start the programmes fail to increase the employment chances of their participants in the regular labour market. However, the programmes may have other effects for their participants that may be considered important in the especially difficult situation experienced in the East German labour market." (author's abstract)

We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators. Very informative administrative Swiss data with detailed regional information are combined with exogenous regional variation in programme participation probabilities, which generate an instrument within well-defined local labour markets. This allows pursuing instrumental variable as well as matching estimation strategies. A specific combination of those methods identifies a new type of effect heterogeneity. We find that ALMP increases individual employment probabilities by about 15% in the short term for unemployed that may be called 'marginal' participants. The effects seem to be considerably smaller for those unemployed not marginal to the participation decision.

"We analyse the effects of public sector sponsored training for the unemployed in the transition process in East Germany. For the microeconometric analysis, we use a new, large and informative administrative database that allows us to use matching methods to reduce potential selection bias, disaggregate programme types, and to observe interesting labour market outcomes over 8 years. We find that, generally, all training programmes under investigation increase long-term employment prospects and earnings. However, as an important exception, the longer training programmes are on average not helpful for their male participants. At least part of the explanation for this negative result is that caseworkers severely misjudged the structure of the future demand for skills." (author's abstract) Vor dem Hintergrund der Arbeitsmarktpolitik in Ostdeutschland nach der Wiedervereinigung wird die Wirksamkeit staatlich geförderter Fortbildungs- und Umschulungsmaßnahmen für Arbeitslose analysiert. Hierzu werden prozessproduzierte Daten aus drei Quellen herangezogen, um durch Matching-Verfahren die Fehler durch Selektionsbias zu vermindern, eine Disaggregation nach Maßnahmetypen vorzunehmen und Beschäftigungseffekte für die Teilnehmer zu identifizieren. Die Voraussetzungen der Maßnahmen und ihre Wirksamkeit werden beurteilt. Insgesamt zeigt sich, dass sich bei den Teilnehmern aller untersuchter Fortbildungs- und Umschulungsmaßnahmen langfristig die Beschäftigungsund Verdienstaussichten verbessern. Eine bedeutsame Ausnahme bilden jedoch Maßnahmen mit längerer Laufzeit, die in der Regel für männliche Teilnehmer wenig nützlich waren. Das wird zumindest teilweise darauf zurückgeführt, dass sich die Förderung der Weiterbildung arbeitsloser Männer in Richtung Bauwesen aufgrund der nachfolgenden Rezession in der Bauwirtschaft als Fehlentscheidung erwiesen hat. (IAB)

"Between 1991 and 1997 West Germany spent on average about 3.6 bn Euro per year on public sector sponsored training programmes for the unemployed. We base our empirical analysis on a new administrative data base that plausibly allows for selectivity correction by microeconometric matching methods. We identify the effects of different types of training programmes over a horizon of more than seven years. Using bias corrected weighted multiple neighbours matching we find that all programmes have negative effects in the short run and positive effects over a horizon of about four years. However, for substantive training programmes with duration of about two years gains in employment probabilities of more than 10% points appear to be sustainable, but come at the price of large negative lock-in effects." (author's abstract) Zwischen 1991 und 1997 wurden in Westdeutschland jährlich durchschnittlich 3,6 Milliarden Euro für die öffentliche Förderung von Weiterbildung ausgegeben. Basierend auf der Beschäftigtenstichprobe, der Leistungsempfängerdatei und der FuU-Teilnehmer-Datei des IAB werden die Beschäftigungseffekte verschiedener Formen der Weiterbildung über einen Zeithorizont von mehr als sieben Jahren ermittelt. Durch die Analyse mittels eines Bias-korrigierten gewichteten Multiple-Neighbour-Matchingverfahrens zeigt sich, dass sich alle Maßnahmen kurzfristig negativ auswirken, langfristig bei einem Zeithorizont von vier Jahren jedoch positiv. Bei langen Maßnahmen mit einer Laufzeit von etwa zwei Jahren ist schon ein Anstieg der Beschäftigungswahrscheinlichkeit von 10 Prozentpunkten nachhaltig, er wird jedoch durch negative Lock-in-Effekte erkauft. (IAB)

The effects of active labour market policies (ALMP) on individual employment chances and earnings are evaluated by nonparametric instrumental variables based on Swiss administrative data with detailed regional information. Using an exogenous variation in the participation probabilities across fairly autonomous regional units (cantons) generated by the federal government, we identify the effects of ALMP by comparing individuals living in the same local labour market but in different cantons. Taking account of small sample problems occurring in IV estimation, our results suggest that ALMP increases individual employment probabilities by about 15% in the short term for a weighted subpopulation of compliers.

The need for better targeting of active labour market programmes is evident from the many evaluation studies that find insignificant or even negative effects. A statistical system could contribute to a more precise targeting of labour market programmes to those individuals who are likely to benefit from them. Such a system could assist caseworkers in selecting adequate programmes on an individual basis. In this paper, international experiences with these systems are surveyed and a potential approach for Switzerland is developed. The simulated outcomes indicate that a statistical selection system could have contributed to a substantial re-employment increase.

We investigate the allocation of unemployed individuals to different subprograms within Swiss active labour market policy by the caseworkers at local employment offices in Switzerland in 1998. We are particularly interested in whether the caseworkers allocate the unemployed to services in ways that will maximize the program-induced changes in their employment probabilities. Our econometric analysis uses unusually informative data originating from administrative unemployment and social security records. For the estimation we apply matching estimators adapted to the case of multiple programmes. The number of observations in this database is sufficiently high to allow for this nonparametric analysis to be conducted in narrowly defined subgroups. Our results indicate that Swiss caseworkers do not do a very good job of allocating their unemployed clients to the subprograms so as to maximize their subsequent employment prospects. Our findings suggest one of three possible conclusions. First, caseworkers may be trying to solve the problem of allocating the unemployed to maximize their subsequent employment, but may lack the skills or knowledge to do this. Second, caseworkers may have a goal other than efficiency, such as allocating the most expensive services to the least well-off clients, that is not explicit in the law regulating active labour market policies. Third, the distortions of the local decision process could be due to federal authorities imposing strict minimum participation requirements for the various programs at the regional level.

Subsidised employment is an important tool of active labour market policies to improve the chances of the unemployed to find permanent employment. Using informative individual administrative data we investigate the effects of two different schemes of subsidised temporary employment implemented in Switzerland. One scheme operates as a non-profit employment programme (EP), whereas the other one is a subsidy for temporary jobs (TEMP) in firms operating in competitive markets. Using econometric matching methods we find that TEMP is considerably more successful in getting the unemployed back into work than EP. We also find that compared to nonparticipation both programmes are ineffective for unemployed who find job easily anyway as well as for those with short unemployment duration. For unemployed with potentially long unemployment duration and for actual long term unemployed, both programmes may have positive effects, but the effect of TEMP is much larger.

The paper presents an econometric evaluation of the effects of subsidised non-profit temporary employment agencies - a programme of the West German active labour market policy - on individual labour market outcomes. The empirical analysis is based on individual data from files for computer-assisted job brokering in Rhineland-Palatinate. Econometric estimates based on matching methods suggest that the programme generated a statistically significant additional reintegration success of about 13 per centage points. Furthermore within the first four month after leaving the programme, the estimated effect was about half a month additional employment for the participants.

In the second part of the 1990?s Switzerland conducted an ambitious active labour market policy (ALMP) encompassing a wide variety of programmes. We evaluate the effects of these programmes on the individual employment probability of potential participants. Our econometric analysis uses unusually informative data originating from administrative unemployment and social security records. We apply a matching estimator adapted for the case of multiple programmes. We find substantial positive effects for one particular programme that is a unique feature of the Swiss ALMP. It consists of a wage subsidy for temporary jobs in the regular labour market that would otherwise not be taken up by the unemployed. We also find large negative effects for traditional employment programmes operated in sheltered labour markets. For training courses the results are mixed.

In East Germany, active labour market policies (ALMPs) are used on a large scale to contain fast rising unemployment after unification. This paper evaluates the effects for participants in public employment programmes (PEPs), that are an important part of ALMPs. It focuses on individual unemployment probabilities. By concentrating on the state of Sachsen-Anhalt, the econometric analysis can use a new and large panel, the Arbeitsmarktmonitor Sachsen-Anhalt. We aim at nonparametric identification of the effects of PEPs by combining the use of comparison groups with differencing over time to correct for selection effects. Our results indicate that PEP participation reduces the unemployment risk of the participants.

Dieser Beitrag stellt ausgew ahlte Ergebnisse des vom Zentrum für Europäische Wirtschaftsforschung (ZEW) im Auftrag des IAB und des Ministeriums für Arbeit und Soziales Rheinland-Pfalz bearbeiteten Forschungsprojekts "Arbeitsplatzeffekte gemeinnütziger Arbeitnehmerüberlassungen in Rheinland-Pfalz" vor. Der ökonometrische Vergleich des Wiedereingliederungserfolgs zeigt Unterschiede zwischen Leiharbeitnehmern und Kontrollgruppe auf. In der kurzen Frist (bis zu 5 Monaten nach Ende des Aufenthalts in der Gesellschaft) weisen die Leiharbeitnehmer ein im Vergleich zur Kontrollgruppe um bis zu 13 Prozentpunkte besseres Wiedereingliederungsergebnis auf. Die Arbeit zeigt, dass die in der Evaluation von Programmen zur Wiedereingliederung spezifischer Arbeitsmarktgruppen noch vergleichsweise wenig verbreitete Matching- Methode in Verbindung mit der hohen Datenqualität, die durch die präzise Aufbereitung der Erwerbsgeschichte in der coArb zustande gekommen ist, eine geeignete Methode zur Abschätzung von Maßnahmeeffekten darstellt.