samlet årgang - Økonomisk Institut - Københavns Universitet

THE EFFECT OF LABOUR MARKET CONDITIONS ON HIGHER EDUCATION COMPLETION 83
cantly affects mean differences in completion rates and time-to-degree across these
groups. Booth and Satchell (1996) analyse some of the same issues on British data on
one entering Ph.D. cohort in 1980. The most complete study in this area to date is by
Ehrenberg and Mavros (1995), who model the time to completion of higher education
using a discrete-time proportional hazard framework in which they analyse the effect
of changes in financial support, changes in student ability and changes in academic
labour market conditions on the time-to-degree completion and completion rates. Their
data is restricted to all entrants to PhD programs in 4 fields (Economics, English,
Mathematics and Physics) during the 1962 to 1986 period, in one single major U.S.
University, Cornell University. While their study incorporates drop-out behaviour by
modelling the competing risks of either degree completion or dropping out, they are
unable to control for unobserved ability that may arise due to unobserved heterogeneity.
In this paper, we consider the role of labour market conditions as well as student
background characteristics, student ability and program-specific factors on the time to
degree completion within the framework of a hazard model. Our focus is not just doctoral
students from a single institution or field, but all students that enter higher-education
programs in Denmark. In addition, unlike most of the previous studies mentioned
above, we correct for differences in individual unobserved ability that may affect the
time to degree completion. Unobserved ability differences among students can confound
the effect of education on labour market outcomes as high-ability individuals
tend to perform better in school and in the labour market. Wage studies of the effect of
schooling on earnings typically have addressed this problem by including separate
measures of ability in wage regressions, or by analysing how wages are affected when
a random event unrelated to ability affects their schooling, or even by analysing differences
in schooling among family members who have the same inherited characteristics,
such as twins, see Card (2001). The same problem can arise when estimating the
effect of observed characteristics on degree completion as omitted ability can bias the
returns to observed characteristics. That is, higher-ability students may be quicker to
complete their education because they experience lower psychic costs (i.e. have an
easier time learning etc.) and because their forgone earnings are likely higher. In a
recent paper, van Ours and Ridder (2003) analyze the supply of Ph.D.s in economics in
the Netherlands within a competing risks hazard model and find that students who are
more likely to take a long time to graduate are the ones most likely to drop out. Selection
is important, as good supervisors attract better students, and these students typically
also have a higher probability of staying on the program. Similarly, we propose a
correction for unobserved heterogeneity in higher education completion. In doing so,
we apply a proportional hazard modelling framework and an estimation technique of
fitting the model with grouped duration data developed by An (2000). This model