Abstract
It is generally found that overeducated (undereducated) workers earn less (more) than adequately educated workers with similar years of education. We investigate the importance of ability and measurement error bias for these outcomes by applying a fixed-effects instrumental variable approach on data for Flemish young workers. This approach results in substantially higher overeducation penalties and undereducation bonusses than a standard random effects approach. This suggests that the upward bias resulting from unobserved worker heterogeneity is more than compensated by the negative bias resulting from measurement error. Further, we also find some evidence on heterogeneous effects of mismatches accross job levels and years of experience.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
For the sampling, a multi-stage procedure was applied based on geographical areas. No stratification schemes were used.
For those who were without jobs at the time of the interview, information was gathered with respect to the end of their last job.
This results in a drop of 32 individuals. Consequently, the effect of years of education cannot be identified in the fixed-effects analysis. Yet, as this is a highly selective group of individuals, results on years of education would probably be unreliable.
A decomposition of our sample with respect to job levels and educational levels can be found in Appendix A.
As discussed in Verhaest and Omey (2006b), the ideal procedure would be to use as instrument an ISA measure that is based on the required level to do the job. Yet, such a measure is not available for the 1976 cohort. Moreover, for the 1978 cohort, it is only available for those with a first job that started before the age of 23. Finally, as shown in Appendix B, additional tests on the reliability and validity of the instruments did not reveal problems. F-test statistics on the contribution of the IV’s in the first stage equations are always strongly statistically significant. Further, the validity of the instrumental variables is never rejected on the basis of Sargan tests on overidentifying restrictions.
Using the midpoint of each interval might lead to inconsistent results (see Stewart 1983). We re-estimated the linear effects models with random effects on the basis of an interval random-effects regression. Yet, the estimation results were largely similar to the reported standard random effects estimates.
For instance, for someone with a HT degree (YEDUC i = 15) and working at the lowest job level (i.e. YREQ it = 6, and YOVER it = 9), we define the following values: YEDUCL i = 10, YEDUCH i = 5, YOVERL i = 4, and YOVERH i = 5. A similar decomposition is executed with respect to the ISA-measure, which serves as instrument.
Unreported IV fixed-effects estimates based on the decomposition of YUNDER it did not reveal statistically significant differences between the effect of YUNDERL it and that of YUNDERH it .
The age cohort nature of the data results in a strong connection between the year of observation and years of experience. Yet, in- or exclusion of these year dummies did not lead to fundamentally different conclusions.
Firm size, industry, region of employment, shift work and night work each include a dummy for observations with unknown category.
Rubb reported average ORU coefficients. The coefficient values that are comparable to our model were computed on the basis of \( YEDU{C_i} \equiv YRE{Q_{ij}} + YOVE{R_{ij}} - YUNDE{R_{ij}} \).
Additional tests did not reject the hypothesis that over- and undereducated workers at higher job levels are paid as their adequately educated colleagues who were employed at the same job level.
In the study of Robst (1994), the size of the bias was found to be even more substantial. The usage of an ISA measure as instrument for a JA measure, for instance, resulted in an increase of the estimated overeducation penalty from 4% to 11%.
The average level of experience in our sample at age 26 is 4.4 years.
References
Battu H, Belfield C, Sloane P (2000) How well can we measure graduate overeducation and its effects? Natl Inst Econ Rev 171:82–93
Bauer T (2002) Educational mismatch and wages: a panel analysis. Econ Educ Rev 21(3):221–229
Büchel F (1994) Overqualification at the beginning of a non academic working career: the efficiency of the German dual system under test. Konjuncturpolitik 40(3–4):342–368
Budría S (2011) Are educational mismatches responsible for the ‘inequality increasing effect’ of education? Soc Indic Res 102(3):409–437
CBS (2001) Standaard Beroepenclassificatie 1992—editie 2001. SDU, Den Haag
Chevalier A (2003) Measuring over-education. Economica 70(3):509–531
Chevalier A, Lindley J (2009) Overeducation and skills of UK graduates. J Roy Stat Soc A 172(2):307–337
Cohn E, Ng Y (2000) Incidence and wage effects of overschooling and underschooling in Hong Kong. Econ Educ Rev 19(2):159–168
Cohn E, Johnson E, Ng Y (2000) The incidence of overschooling and underschooling and its effects on earnings in the United States and Hong Kong. Res Labor Econ 19:29–61
de Grip A, Hosma H, Willems D, van Boxtel M (2008) Job-worker mismatch and cognitive decline. Oxf Econ Pap 60:237–252
Dolton P, Silles M (2008) The effects of over-education on earnings in the graduate labour market. Econ Educ Rev 27:125–139
Duncan G, Hoffman S (1981) The incidence and wage effects of overeducation. Econ Educ Rev 1(1):75–86
Frenette M (2004) The overqualified Canadian graduate: the role of the academic program in the incidence, persistence, and economic returns to overqualification. Econ Educ Rev 23(1):29–45
Groot W, Maassen van den Brink H (2000) Overeducation in the labor market: a meta-analysis. Econ Educ Rev 19(2):149–158
Hartog J (2000) Overeducation and earnings: where are we, where should we go? Econ Educ Rev 19(2):131–147
Korpi T, Tåhlin M (2009) Education mismatch, wages, and wage growth: overeducation in Sweden 1974–2000. Labour Econ 16(2):183–193
McGuinness S (2003) Graduate overeducation as a sheepskin effect: evidence from Northern Ireland. Appl Econ 35(5):597–608
McGuinness S, Bennett J (2006) Overeducation and the graduate labour market: a quantile regression approach. Econ Educ Rev 26(5):521–531
Mendes de Oliveira M, Santos MC, Kiker BF (2000) The role of human capital and technological change in overeducation. Econ Educ Rev 19(2):199–206
Robst J (1994) Measurement error and the returns to excess schooling. Appl Econ Lett 1:142–144
Rubb S (2003) Overeducation in the labor market: a comment and re-analysis of a meta-analysis. Econ Educ Rev 22(6):621–629
Sloane P (2003) Much ado about nothing? In: Büchel F, de Grip A, Mertens A (eds) Overeducation in Europe. Edwar Elgar, Cheltenham, pp 11–45
Sohn K (2010) The role of cognitive and noncognitive skills in overeducation. J Lab Res 31:124–145
SONAR (2003) Hoe maken Vlaamse jongeren de overgang van school naar werk?, basisrapportering cohorte 1978 (eerste golf), p 147
SONAR (2004) Hoe maken Vlaamse jongeren de overgang van school naar werk?, basisrapportering cohorte 1976 (tweede golf), p 116
Stewart M (1983) On least squares estimation when the dependent variable is grouped. Rev Econ Stud 50(163):737–753
van der Meer P (2006) The validity of two education requirement measures. Econ Educ Rev 25(2):211–219.
van der Velden R, van Smoorenburg M (1999) Overscholing en beloning: Het effect van verschillende meetmethoden. Tijdschrift voor Arbeidsvraagstukken 15(2):111–123
Verhaest D, Omey E (2006a) Measuring the incidence of over- and undereducation. Qual Quant 40:783–803
Verhaest D, Omey E (2006b) Discriminating between alternative measures of overeducation. Appl Econ 38(10):2113–2120
Verhaest D, Omey E (2006c) The impact of overeducation and its measurement. Soc Indic Res 77(3):419–448
Verhaest D, Omey E (2010) The determinants of overeducation: different measures, different outcomes? Int J Manpow 31(6):608–625
Author information
Authors and Affiliations
Corresponding author
Additional information
We thank Gerdie Everaert, Walter Van Trier and an anonymous referee for their valuable comments on a previous version of this paper.
Appendices
Appendix A
Appendix B
Appendix C
Rights and permissions
About this article
Cite this article
Verhaest, D., Omey, E. Overeducation, Undereducation and Earnings: Further Evidence on the Importance of Ability and Measurement Error Bias. J Labor Res 33, 76–90 (2012). https://doi.org/10.1007/s12122-011-9125-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12122-011-9125-6