The value of education in low skill economies: some evidence from Kenyan and Tanzanian Manufacturing
In depth
Robustness
Two robustness checks
- The first test refers to the sensitivity of the results to functional form.
- Our spline function is flexible, but linearity within each segment is imposed. This may be too restrictive.
- Our second robustness check refers to the sensitivity of the results to the inclusion of sector effects.
Predicted Earnings Based on Polynomial Specification: Kenya
Predicted Earnings Based on Polynomial Specification: Tanzania
Comparison with non-African Data
- Using data from Trostel et al (2002)
- 28 countries
- Multiple cross-sections of data
- Only one developing country the Philipines
- No Africa or Asia
- “ There is tenuous evidence that the ROR declines with educational level ”
- They do not draw graphs.
Robustness checks for sector
- Recall that our data contain individuals working in four manufacturing sub-sectors in the two countries: food, wood, textiles and metal.
- Such earnings regressions (with sector controls) indicate how education is rewarded within sectors. The pooling tests results are shown in Table A.1, panel B.
- The overall picture is similar to what we have seen above. For both countries the sector effects are jointly significant at the five per cent level or lower (tests not reported).
- While this suggests there are systematic wage differences across sectors, the estimated earnings profiles have not changed much as a result of including the sector controls. In particular, the graphs show quite clearly that the convexity of the earnings functions holds within, as well as between, sectors.