Educational Mismatches and Earnings: Extensions of Occupational Mobility Theory and Evidence of Human Capital Depreciation

Abstract

Using a human capital theory framework, this study examines the impact of educational mismatches on earnings and occupational mobility. Occupational mobility theory suggests that overeducated workers observe greater upward occupational mobility and undereducated workers observe lower upward occupational mobility. By extension, this leads to relatively high earnings growth for overeducated workers and relatively low earnings growth for undereducated workers. Moreover, overeducated workers are probably transient relative to their undereducated counterparts, so employers have few incentives to invest in their human capital. Accordingly, their experience will be rewarded at lower rates. These results may also occur if the unused human capital of overeducated workers depreciates with nonuse. The data verify these predictions. Insights on the link between experience and educational mismatches are also examined.

Key Words:

• Human capital
• overeducation
• occupational mobility

Notes

1. Allen and van der Velden (2001) find skill mismatches to be a better predictor of job satisfaction.

2. Other explanations are not ruled out by this research. One of particular note is assignment theory (Sattinger, 1993). Hartog (2000) and Allen and van der Velden (2001) explain the parallels between the findings in the overeducation literature and assignment theory.

3. These studies seek to examine the substitution/complementary relationship between experience and educational mismatches. These studies do not explain their findings in the context of occupational mobility and human capital depreciation as developed in this paper.

4. See Madrian and Lefgren (1999) for a description on matching individuals in the March CPS. As is recommended by Madrian and Lefgren, individuals whose age, race or gender coding implausibly change are believed to be improper matches and excluded. As is found in Madrian and Lefgren (1999), matching is successful in slightly more than seven out of 10 tries. Matching does not always occur due to non‐responses, mortality, recording errors, and migrations.

5. See Cohn et al. (2000), Ng (2001), and Groot (1996). In Oliveria et al. (2000), estimates of β_oe and β_ue vary based on the criterion used to calculate ED_REQ and are not consistent with the results found in this study.

6. Sicherman and Galor (1990, p. 183) hypothesize that if ‘the return to human capital (schooling) is lower while one is working in a specific occupation, the effect of schooling on the probability of being promoted from that occupation will be higher.’ Highly educated individuals with low pay will probably either be promoted intra‐firm or seek upward occupational mobility inter‐firm.

7. The results between the two models are not directly comparable. By including actual education in place of required education, overeducation impacts the model in two ways; the overeducation variable and the additional schooling necessary to become overeducated (Rubb, 2005).

8. Robst uses US data from the 1976, 1978, and 1985 Panel Study on Income Dynamics. Sicherman (1991) uses the 1976 and 1978 Panel Study on Income Dynamics. Both studies use dummy variables to indicate overeducation and undereducation, not the specification used in this paper that has the added benefit of capturing the extent of the educational mismatches. Sicherman and Büchel and Mertens control for actual education (not required education). In estimates similar to equation (4) (not shown for brevity) using the data set in this paper containing an individual’s actual schooling and not ED_REQ , the coefficients for ED_UN and ED_OV remain negative and positive, respectively. As indicated in note 7, the results are not directly comparable with those presented in this paper.