Qualification mismatch and impacts on earnings – OLS
| Full sample | Full sample | Male | Female | Urban | Rural | |
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Years of required education | 0.069*** (0.001) | 0.078*** (0.002) | 0.076*** (0.002) | 0.081*** (0.002) | 0.087*** (0.003) | 0.073*** (0.002) |
| Years of over-education | 0.048*** (0.003) | 0.063*** (0.003) | 0.058*** (0.004) | 0.068*** (0.004) | 0.079*** (0.005) | 0.053*** (0.004) |
| Years of under-education | −0.026*** (0.001) | −0.041*** (0.001) | −0.043*** (0.002) | −0.039*** (0.002) | −0.042*** (0.002) | −0.039*** (0.002) |
| Age cohorts | ||||||
| 15–25 | Ref | Ref | Ref | Ref | Ref | |
| 26–35 | 0.018 (0.011) | −0.003 (0.016) | 0.035** (0.016) | 0.027 (0.018) | 0.012 (0.015) | |
| 36–45 | 0.028 (0.019) | −0.004 (0.027) | 0.058** (0.027) | 0.020 (0.030) | 0.033 (0.025) | |
| 46–55 | 0.027 (0.027) | −0.027 (0.039) | 0.087** (0.038) | −0.023 (0.044) | 0.057* (0.035) | |
| 56–64 | −0.004 (0.037) | −0.018 (0.051) | 0.004 (0.055) | −0.107* (0.059) | 0.067 (0.047) | |
| Years of experience | 0.027*** (0.001) | 0.030*** (0.002) | 0.023*** (0.002) | 0.025*** (0.002) | 0.028*** (0.002) | |
| Years of experience-squared | −0.004*** (0.000) | −0.004*** (0.000) | −0.003*** (0.000) | −0.003*** (0.000) | −0.004*** (0.000) | |
| Gender | ||||||
| Male | Ref | Ref | Ref | |||
| Female | −0.104*** (0.005) | −0.133*** (0.008) | −0.084*** (0.007) | |||
| Marital status | ||||||
| Single | Ref | Ref | Ref | Ref | Ref | |
| Married | 0.053*** (0.007) | 0.088*** (0.011) | 0.031*** (0.009) | 0.025** (0.011) | 0.076*** (0.009) | |
| Region | ||||||
| Urban | Ref | Ref | Ref | |||
| Rural | −0.079*** (0.005) | −0.097*** (0.007) | −0.062*** (0.007) | |||
| Constant | 2.334*** (0.020) | 1.958*** (0.025) | 1.985*** (0.034) | 1.816*** (0.036) | 1.893*** (0.043) | 1.901*** (0.030) |
| Number of observations | 29,635 | 29,635 | 15,885 | 13,750 | 12,586 | 17,049 |
| R2 | 0.132 | 0.248 | 0.245 | 0.236 | 0.222 | 0.272 |
| Full sample | Full sample | Male | Female | Urban | Rural | |
|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | |
| Years of required education | 0.069*** (0.001) | 0.078*** (0.002) | 0.076*** (0.002) | 0.081*** (0.002) | 0.087*** (0.003) | 0.073*** (0.002) |
| Years of over-education | 0.048*** (0.003) | 0.063*** (0.003) | 0.058*** (0.004) | 0.068*** (0.004) | 0.079*** (0.005) | 0.053*** (0.004) |
| Years of under-education | −0.026*** (0.001) | −0.041*** (0.001) | −0.043*** (0.002) | −0.039*** (0.002) | −0.042*** (0.002) | −0.039*** (0.002) |
| 15–25 | Ref | Ref | Ref | Ref | Ref | |
| 26–35 | 0.018 (0.011) | −0.003 (0.016) | 0.035** (0.016) | 0.027 (0.018) | 0.012 (0.015) | |
| 36–45 | 0.028 (0.019) | −0.004 (0.027) | 0.058** (0.027) | 0.020 (0.030) | 0.033 (0.025) | |
| 46–55 | 0.027 (0.027) | −0.027 (0.039) | 0.087** (0.038) | −0.023 (0.044) | 0.057* (0.035) | |
| 56–64 | −0.004 (0.037) | −0.018 (0.051) | 0.004 (0.055) | −0.107* (0.059) | 0.067 (0.047) | |
| Years of experience | 0.027*** (0.001) | 0.030*** (0.002) | 0.023*** (0.002) | 0.025*** (0.002) | 0.028*** (0.002) | |
| Years of experience-squared | −0.004*** (0.000) | −0.004*** (0.000) | −0.003*** (0.000) | −0.003*** (0.000) | −0.004*** (0.000) | |
| Male | Ref | Ref | Ref | |||
| Female | −0.104*** (0.005) | −0.133*** (0.008) | −0.084*** (0.007) | |||
| Single | Ref | Ref | Ref | Ref | Ref | |
| Married | 0.053*** (0.007) | 0.088*** (0.011) | 0.031*** (0.009) | 0.025** (0.011) | 0.076*** (0.009) | |
| Urban | Ref | Ref | Ref | |||
| Rural | −0.079*** (0.005) | −0.097*** (0.007) | −0.062*** (0.007) | |||
| Constant | 2.334*** (0.020) | 1.958*** (0.025) | 1.985*** (0.034) | 1.816*** (0.036) | 1.893*** (0.043) | 1.901*** (0.030) |
| Number of observations | 29,635 | 29,635 | 15,885 | 13,750 | 12,586 | 17,049 |
| 0.132 | 0.248 | 0.245 | 0.236 | 0.222 | 0.272 | |
Notes: ORU Model. Dependent variable: natural logarithm of hourly wages. Sample of workers from 15 to 64 years old, working full-time in the formal sectors of the economy (excluding the military sector). We use age cohort dummies instead of age to avoid multicollinearity with years of experiences. Heteroskedasticity robust standard errors in parentheses. *,**,***Significant at 10, 5 and 1 percent levels, respectively
Source: Authors’ calculation