This study is concerned with a cost-benefit analysis of Higher Education in Greece. The main objective is the calculation of private and social rates of return for both males and females in five different subject groups, i.e. Economics, Law, Mathematics, Medical Sciences and Technical Sciences. The earnings data used come from the Public Sector, Public Power Corporation, Greek Banks, Institution of Social Security, National Health System and the Private Sector. The calculation of the rates of return is based on the differentials between the life-time earnings of a person who has a university degree in one of the subjects considered and a person who enters the job market just after finishing his/her secondary level education. Non-pecuniary returns have not been taken into account. The estimates of the rates of return show that males generally achieve higher returns than females. Moreover, for professions in which people can significantly extend their activities in the private sector, such as Doctors, the observed rates of return are relatively higher than for employees. The private rates of return vary from approximately 17.3% for male doctors to 7.4% for female engineers, whereas the social rates of return vary from 13.4% to 5.6% for the same professions. Thus, the social rates of return appear to be lower than the private rates of return, as has been found in most previous studies of this type. Furthermore, these results have been tested for their sensitivity to the assumptions made about the extent of activities in the private sector and the black economy. The tests carried out show that the results are rather sensitive to the assumptions, especially for occupations with extensive activities in the private sector. The implications of these results for the allocation of government spending on higher education in Greece are discussed.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:263753 |
Date | January 1992 |
Creators | Hadjidema, Stamatina |
Publisher | University of Leicester |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/2381/35490 |
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