| | Sample of men | Sample of women |
|---|
| | Difference in log wages | SE | t-stat | Difference in log wages | SE | t-stat |
|---|
| | (1) | (2) | (3) | (4) | (5) | (6) |
|---|
Panel A: Malaysia
| | | | | | |
ATT | 0.11*** | 0.04 | 2.95 | 0.05 | 0.04 | 1.30 |
Untreated | 2,394 | | | 2,035 | | |
Treated | 1,269 | | | 933 | | |
Observations | 3,663 | | | 2,968 | | |
Panel B: Thailand
| | | | | | |
ATT | 0.05 | 0.03 | 1.44 | 0.04* | 0.02 | 1.81 |
Untreated | 1,970 | | | 2,507 | | |
Treated | 2,182 | | | 2,759 | | |
Observations | 3,663 | | | 5,266 | | |
- Source: Authors’ calculations based on the Enterprise Surveys (World Bank).
- Note: * significant at 10%, ** significant at 5%, *** significant at 1%. The table uses propensity score matching to estimate equation (4) in the text. We estimate separate regressions by gender. Columns (1) and (4) report Average Treatment Effect on the Treated (ATT) which evaluates the wage impact of training for those actually participating in training. Columns (2) and (5) report standard errors. Columns (3) and (6) report the t-statistic. Treated individuals are those who have participated in training and the untreated individuals are the “control group” that is similar for all characteristics to the treated group except for the fact of receiving training. Panel A reports the estimates for the sample of workers in Malaysia, and Panel B reports the estimates for the sample of workers in Thailand.
