Sequential Matching Estimation of Dynamic Causal Models

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic casual effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation literature. A Monte Carlo study shows that the suggested estimators perform well in small and medium seize samples. Based on the application of the sequential matching estimators to an empirical problem - an evaluation study of the Swiss active labour market policies - some implementational issues are discussed and results are provided.Dynamic treatment effects, nonparametric identification, causal effects, sequential randomisation, programme evaluation, panel data

The Relation of Different Concepts of Causality in Econometrics

Granger and Sims non-causality (GSNC) are compared to non-causality based on concepts popular in the microeconometrics and programme evaluation literature (potential outcome non-causality, PONC). GSNC is defined as a set of restrictions on joint distributions of random variables with observable sample counterparts, whereas PONC combines restrictions on partially unobservable variables (potential outcomes) with different identifying assumptions that relate potential to observable outcomes. Based on a dynamic model of potential outcomes, we find that in general neither of the concepts implies each other without further assumptions. However, identifying assumptions of the sequential selection on observable type provide the link between those concepts, such that GSNC implies PONC, and vice versa.Granger causality, Sims causality, Rubin causality, potential outcome model, dynamic treatments

Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods

Recently, several studies have analysed active labour market policies by using a recently proposed matching estimator for multiple programmes. Since there is only very limited practical experience with this estimator, this paper checks its sensitivity with resprect to issues that are of practical importance in this kind of evaluation study. The estimator turns out to be fairly robust to several features that concern its implementation. Furthermore, the paper demonstrates that the matching approach per se is no panacea for solving all the problems of evaluation studies, but that its success depends critically on the information that is available in the data. Finally, a comparison with a bootstrap distribution provides some justification for using a simplified approximation of the distribution of the estimator that ignores its sequential nature.Balancing score; Matching; Multiple programmes, Programme evaluation, Sensitivity analysis, Treatment effects

A Note on the Relation of Weighting and Matching Estimators

This paper compares the inverse-probability-of-selection-weighting estimation principle with the matching principle and derives conditions for weighting and matching to identify the same and the true distribution, respectively. This comparison improves the understanding of the relation of these estimation principles and allows constructing new estimators.Matching, inverse-of-selection-probability weighting, treatment evaluation, unconfoundedness

Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach

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

Some Econometric Evidence on the Effectiveness of Active Labour Market Programmes in East Germany

In this paper we summarise our previous results on the effectiveness of different kinds of labour market training programmes as well as employment programmes in East Germany after unification. All the studies use the microeconometric evaluation approach and are based on different types of matching estimators. We find some positive earnings effect for on-the-job training and also some positive employment effects for employment programmes. No such effects appear for public sector sponsored (off-the-job) training programmes. Generally, the scope of such analysis is very much hampered by the insufficient quality and quantity of the data available for East Germany. Although in particular the results for public sector sponsored training programmes raise serious doubts about the effectiveness of these programmes, any definite policy conclusion from this and other studies about active labour market policy in East Germany would probably be premature.http://deepblue.lib.umich.edu/bitstream/2027.42/39702/3/wp318.pd

Are training programs more effective when unemployment is high?

"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." (Author's abstract, IAB-Doku) ((en))Qualifizierungsmaßnahme, arbeitsmarktpolitische Maßnahme, Beschäftigungseffekte - Determinanten, Arbeitslosenquote, Arbeitslose, berufliche Reintegration, Arbeitsmarktchancen, Teilnehmerstruktur, Trainingsmaßnahme, Einkommenseffekte, Arbeitsmarktentwicklung, Westdeutschland, Bundesrepublik Deutschland

Exploiting regional treatment intensity for the evaluation of labour market policies

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.Local average treatment effect, conditional local IV, active labour market policy, state borders, geographic variation, Switzerland, Fuller estimator

Some recent developments in microeconometrics: A survey

This paper summarizes some recent developments in rnicroeconometrics with respect to methods for estimation and inference in non-linear models based on cross-section and panel data. In particular we discuss recent progress in estimation with conditional moment restrictions, simulation methods, serniparametric methods, as well as specification tests. We use the binary cross-section and panel probit model to illustrate the application of some of the theoretical results. --