scholarly journals The use of propensity score-matching methods in evaluation of active labour market programs in Serbia

2007 ◽  
Vol 52 (172) ◽  
pp. 21-53
Author(s):  
Kosovka Ognjenovic
Keyword(s):  
Propensity Score ◽  
Labour Market ◽  
Propensity Score Matching ◽  
Treatment Effects ◽  
Matching Method ◽  
Estimation Process ◽  
Average Treatment ◽  
Active Labour ◽  
Average Treatment Effects ◽  
Active Labour Market Programmes

The aim of the paper is to evaluate impacts of active labour market measures in Serbia on the probability of the participants? employment. In the estimation process of average treatment effects, propensity score-matching method was applied. Its use has considerably reduced the bias in evaluation of the average treatment effects, induced by systematic differences between samples of those who participated in the active labour market programmes and those who did not. The estimated impacts of active labour market programmes on the probability of employment were found to be both positive and statistically significant. .

scholarly journals Effectiveness of Active Labour Market Programmes on the Job Quality of Welfare Recipients in Germany

2019 ◽  
Vol 48 (4) ◽  
pp. 807-838 ◽  
Author(s):  
KATHARINA DENGLER
Keyword(s):  
Propensity Score ◽  
Labour Market ◽  
Propensity Score Matching ◽  
Vocational Training ◽  
Job Quality ◽  
Welfare Recipients ◽  
High Quality ◽  
Active Labour ◽  
Active Labour Market Programmes

AbstractUsing rich administrative data on unemployed welfare recipients in Germany and propensity score matching, the author analyses the effects of participating in four major active labour market programmes (ALMPs) on various dimensions of job quality. In Germany, welfare recipients may suffer from poor job quality because they are forced to accept any reasonable job offer. However, few studies consider the effects of participation in ALMPs on job quality. The results imply that participation in a programme not only increases the probability of taking jobs but also increases the probability of holding a high-quality job for some dimension of job quality. In particular, further vocational training is very effective in terms of job quality for West German women. Thus, job centres should focus on the activation of unemployed welfare recipients.

scholarly journals Estimation of Average Treatment Effects Based on Propensity Scores

2002 ◽  
Vol 2 (4) ◽  
pp. 358-377 ◽  
Author(s):  
Sascha O. Becker ◽  
Andrea Ichino
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Labor Economics ◽  
Treatment Effects ◽  
Propensity Scores ◽  
Short Overview ◽  
Average Treatment ◽  
Matching Estimators ◽  
Average Treatment Effects ◽  
Supported Work

In this paper, we give a short overview of some propensity score matching estimators suggested in the evaluation literature, and we provide a set of Stata programs, which we illustrate using the National Supported Work (NSW) demonstration widely known in labor economics.

scholarly journals Estimation of Population Average Treatment Effects in the FIRST Trial: Application of a Propensity Score-Based Stratification Approach

2017 ◽  
Vol 53 (4) ◽  
pp. 2567-2590 ◽  
Author(s):  
Jeanette W. Chung ◽  
Karl Y. Bilimoria ◽  
Jonah J. Stulberg ◽  
Christopher M. Quinn ◽  
Larry V. Hedges
Keyword(s):  
Propensity Score ◽  
Treatment Effects ◽  
Average Treatment ◽  
Population Average ◽  
Average Treatment Effects

scholarly journals Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score

Econometrica ◽  
2003 ◽  
Vol 71 (4) ◽  
pp. 1161-1189 ◽  
Author(s):  
Keisuke Hirano ◽  
Guido W. Imbens ◽  
Geert Ridder
Keyword(s):  
Propensity Score ◽  
Treatment Effects ◽  
Efficient Estimation ◽  
Average Treatment ◽  
Average Treatment Effects

scholarly journals Estimating the average treatment effects of nutritional label use using subclassification with regression adjustment

2014 ◽  
Vol 26 (2) ◽  
pp. 839-864
Author(s):  
Michael J Lopez ◽  
Roee Gutman
Keyword(s):  
Propensity Score ◽  
Treatment Effects ◽  
Ordinal Scale ◽  
Limited Attention ◽  
Exposure Level ◽  
Average Treatment ◽  
Nutritional Label ◽  
Average Treatment Effects ◽  
Regression Adjustment ◽  
Label Use

Propensity score methods are common for estimating a binary treatment effect when treatment assignment is not randomized. When exposure is measured on an ordinal scale (i.e. low–medium–high), however, propensity score inference requires extensions which have received limited attention. Estimands of possible interest with an ordinal exposure are the average treatment effects between each pair of exposure levels. Using these estimands, it is possible to determine an optimal exposure level. Traditional methods, including dichotomization of the exposure or a series of binary propensity score comparisons across exposure pairs, are generally inadequate for identification of optimal levels. We combine subclassification with regression adjustment to estimate transitive, unbiased average causal effects across an ordered exposure, and apply our method on the 2005–2006 National Health and Nutrition Examination Survey to estimate the effects of nutritional label use on body mass index.

Estimation of average treatment effects based on parametric propensity score model

2010 ◽  
Vol 140 (3) ◽  
pp. 806-816 ◽  
Author(s):  
Lili Yao ◽  
Zhihua Sun ◽  
Qihua Wang
Keyword(s):  
Propensity Score ◽  
Treatment Effects ◽  
Propensity Score Model ◽  
Average Treatment ◽  
Average Treatment Effects ◽  
Score Model

scholarly journals Remittances from International Labour Migrants and the Standard of Living of the Left Behind Households in Sri Lanka

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
D. Siriwardhane ◽  
S. Amaratunge ◽  
I. De Silva
Keyword(s):  
Sri Lanka ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Survey Data ◽  
Thematic Analysis ◽  
Standard Of Living ◽  
Income Quintile ◽  
Matching Method ◽  
Left Behind ◽  
Average Treatment Effects

This study aims to examine the effect of remittances on the standard of living of the remittance receiving households in Sri Lanka. Survey data were analyzed using thematic analysis and stratified matching method in propensity score matching. It was found that, a large majority of labour migrants remit money to their households left behind. However, the volume of remittances varies with the demographic and socio-economic characteristics of the labour migrants and their households. Furthermore, it was found that remittance receiving households enjoy income from diversified sources. Average treatment effects estimated through stratified matching analysis reveal that remittance receivers enjoy a higher level of income and higher standard of living compared to their non-remittance receiving counterparts. Improvement of the income by the remittances varies with the income quintile of the households.KeywordsMigration, Propensity Score Matching, Remittances, Sri Lanka

scholarly journals Performance evaluation of propensity score methods for estimating average treatment effects with multi-level treatments

2018 ◽  
Vol 46 (5) ◽  
pp. 853-873 ◽  
Author(s):  
Hui Nian ◽  
Chang Yu ◽  
Juan Ding ◽  
Huiyun Wu ◽  
William D. Dupont ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Propensity Score ◽  
Treatment Effects ◽  
Propensity Score Methods ◽  
Average Treatment ◽  
Multi Level ◽  
Average Treatment Effects
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