From: Impact of long working hours on health based on observations in China
 | OPROBIT | ERM | CMP |
---|---|---|---|
Long working hours | −0.0519* | − 0.0729* | − 0.0681** |
 | (0.090) | (0.050) | (0.047) |
Gender | 0.150*** | 0.151*** | 0.139*** |
 | (0.000) | (0.000) | (0.000) |
Age | −0.0275*** | −0.0274*** | − 0.0254*** |
 | (0.000) | (0.000) | (0.000) |
Income | 0.00772** | 0.00764** | 0.00718** |
 | (0.035) | (0.045) | (0.039) |
Level of education | −0.0182 | −0.0180 | −0.0163 |
 | (0.334) | (0.324) | (0.334) |
Marital status | 0.0519 | 0.0516 | 0.0481 |
 | (0.182) | (0.176) | (0.169) |
Smoking | −0.138** | −0.138** | −0.129** |
 | (0.043) | (0.039) | (0.035) |
Drinking | 0.133** | 0.132** | 0.123** |
 | (0.022) | (0.026) | (0.024) |
Exercise | 0.0264*** | 0.0263*** | 0.0246*** |
 | (0.000) | (0.000) | (0.000) |
Medical insurance | −0.0662 | −0.0297 | −0.0276 |
 | (0.168) | (0.607) | (0.606) |
Year | YES | YES | YES |
Province | YES | YES | YES |
sigma2_u | 0.168 | Â | Â |
_cons | (0.310) | Â | Â |
n | Â | 0.834*** | 0.834*** |
 |  | (0.000) | (0.000) |
_cons | Â | 0.106*** | Â |
 |  | (0.000) |  |
Log likelihood |  |  | −10,170.721 |
Wald | Â | 135.97*** | Â |
Observations | 6972 | 6972 | 6972 |