Estimation of returns to higher education by field of study controlled for occupational status in 2019 and 2021
| (MTE2019oc) | (MTE2021oc) | |
|---|---|---|
| ln(income) | ln(income) | |
| Field of study | ||
| 1. Teaching | 0.826*** | 0.729*** |
| (0.314) | (0.131) | |
| 2. Social science, law, art, and humanities | 0.615*** | 0.717*** |
| (0.232) | (0.129) | |
| 3. Business | 0.590 | 0.815*** |
| (0.363) | (0.119) | |
| 4. Computer related | 0.660** | 0.599*** |
| (0.260) | (0.107) | |
| 5. Science, agriculture, engineer, and architect | −0.294*** | −0.196*** |
| (0.073) | (0.059) | |
| 6. Healthcare | 0.705*** | 1.186*** |
| (0.174) | (0.081) | |
| 7. Other fields | 0.736*** | 0.636*** |
| (0.089) | (0.149) | |
| Occupation | ||
| 1. Employer | 0.001 | −0.016 |
| (0.117) | (0.091) | |
| 2. Own account workers | −2.722*** | −2.735*** |
| (Agri) | (0.048) | (0.048) |
| 3. Own account workers | −0.187*** | −0.306*** |
| (Non-agri) | (0.033) | (0.032) |
| Female | 0.274** | 0.277*** |
| (0.111) | (0.102) | |
| Age | 0.103*** | 0.112*** |
| (0.013) | (0.013) | |
| Age2 | −0.001*** | −0.001*** |
| (0.000) | (0.000) | |
| Urban | 0.480*** | 0.468*** |
| (0.041) | (0.040) | |
| IMR | −3.355*** | −3.440*** |
| (0.429) | (0.445) | |
| Constant | 7.562*** | 7.439*** |
| (0.268) | (0.253) | |
| Observations | 53,337 | 54,828 |
| (MTE2019oc) | (MTE2021oc) | |
|---|---|---|
| ln(income) | ln(income) | |
| 1. Teaching | 0.826*** | 0.729*** |
| (0.314) | (0.131) | |
| 2. Social science, law, art, and humanities | 0.615*** | 0.717*** |
| (0.232) | (0.129) | |
| 3. Business | 0.590 | 0.815*** |
| (0.363) | (0.119) | |
| 4. Computer related | 0.660** | 0.599*** |
| (0.260) | (0.107) | |
| 5. Science, agriculture, engineer, and architect | −0.294*** | −0.196*** |
| (0.073) | (0.059) | |
| 6. Healthcare | 0.705*** | 1.186*** |
| (0.174) | (0.081) | |
| 7. Other fields | 0.736*** | 0.636*** |
| (0.089) | (0.149) | |
| 1. Employer | 0.001 | −0.016 |
| (0.117) | (0.091) | |
| 2. Own account workers | −2.722*** | −2.735*** |
| (Agri) | (0.048) | (0.048) |
| 3. Own account workers | −0.187*** | −0.306*** |
| (Non-agri) | (0.033) | (0.032) |
| Female | 0.274** | 0.277*** |
| (0.111) | (0.102) | |
| Age | 0.103*** | 0.112*** |
| (0.013) | (0.013) | |
| Age2 | −0.001*** | −0.001*** |
| (0.000) | (0.000) | |
| Urban | 0.480*** | 0.468*** |
| (0.041) | (0.040) | |
| IMR | −3.355*** | −3.440*** |
| (0.429) | (0.445) | |
| Constant | 7.562*** | 7.439*** |
| (0.268) | (0.253) | |
| Observations | 53,337 | 54,828 |
Note(s): (1) Bootstrapped standard errors in parentheses (***p < 0.01, **p < 0.05, *p < 0.1)
(2) Explanatory variables used for the selection (into employment) equation in the HM models and the construction of the Inverse Mill’s Ration (IMR) for the MTE models include age, and dummy variables for married, urban, college, and vocational degree
(3) The MTE models were estimated using the mtreatreg command in Stata, developed by Deb (2009). Full estimation results are provided in Appendix A
Source(s): Authors’ estimations using the SES 2019 and SES 2021 datasets for a sample of individuals aged 25–60 years whose primary activity is not attending school (with population weighting)