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Reproducibility package for Labor Market Returns To Socio-Emotional Traits And The Impacts Of Training Programs: A Meta-Analysis

2026
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Reference ID
RR_WLD_2026_560
DOI
https://doi.org/10.60572/dz4x-dj42
Author(s)
Diego Angel-Urdinola, Maurice Kugler, Narae Lee, Angelo Gabrielle Fernandez Santos, Olzhas Zhorayev
Collections
World Bank Policy Research Working Papers
Metadata
JSON
Created on
Mar 04, 2026
Last modified
Mar 06, 2026
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159
Downloads
64
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Other Materials
README for the reproducibility package for Labor Market Returns To Socio-Emotional Traits And The Impacts Of Training Programs: A Meta-Analysis
Download [PDF, 3.77 MB]
Reproducibility verification for the reproducibility package for Labor Market Returns To Socio-Emotional Traits And The Impacts Of Training Programs: A Meta-Analysis
Download [PDF, 137.37 KB]
Reproducibility package for Labor Market Returns To Socio-Emotional Traits And The Impacts Of Training Programs: A Meta-Analysis
Download [ZIP, 5.48 MB]
Download https://reproducibility.worldbank.org//catalog/496/download/1421
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data_hash_report.csv
LICENSE.txt
README.pdf
00-Master-run-all.py
1.log
1.Pool-Estimates-RE-All.do
10.Descriptive-Stat-Training.do
10.log
11.Training-Impact.py
12.Training-Heterogeneity.py
13.Funnel-Plot-Training.do
13.log
14.Descriptive-Stat-Region.do
14.log
15.Wage-Returns-RE-Main.py
16.Wage-Returns-FE-All.py
17.Wage-Returns-RE-Big5.py
2.log
2.Pool-Estimates-Training.do
3.log
3.Pool-Estimates-RE-Main.do
4.log
4.Pool-Estimates-FE-All.do
5.log
5.Pool-Estimates-RE-Big5.do
6.Descriptive-Stat-Income.do
6.log
7.Wage-Returns-RE.py
8.Heterogeneity.py
9.Funnel-Plot.do
9.log
environment.txt
Paths.py
Setup.do
Setup.log
Figure1.WageReturns.png
Figure2.Heterogeneity.png
Figure3.FunnelPlot.png
Figure4.TrainingImpact.png
Figure5.TrainingHeterogeneity.png
Figure6.FunnelPlotTraining.png
FigureA7.WageReturnsREMain.png
FigureA8.WageReturnsFEAll.png
FigureA9.WageReturnsREBig5.png
Table2_DescriptiveStats_Income.xlsx
Table3_DescriptiveStats_Training.xlsx
TableA3_DescriptiveStats_Region.xlsx
reproducibility_report_RR_WLD_2026_560.pdf
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