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and

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Access to higher education and the value of a university degree

Governments sometimes promote reforms, normally with little thought as to what the actual outcomes will be, that increase access to education for a large share of the population. These reforms may lower the returns to education by altering returns to skills, education quality, and peer effects. In a new column at VoxEU.org examines Nicola Bianchi the case of a 1961 Italian reform that increased enrolment in university STEM majors among students who had previously been denied access. The reform ultimately failed to raise their incomes.

Bianchi writes,

In a recent working paper, I illustrate the effects of a 1961 Italian reform that led to a 216% increase in enrolment in university STEM (Science, Technology, Engineering, and Mathematics) programmes over a mere eight years (Bianchi 2014). I find that:

• The reform increased enrolment in university STEM majors among students that had been previously denied access, but ultimately failed to raise their incomes.
• The enrolment expansion lowered the value of a STEM education by crowding out university spending and generating negative peer effects.
• Due to lower returns to a university STEM degree, some students with the potential to succeed in STEM turned to other university programs.

He continues

Italian high schools offer different curricula. Until 1960, a student who graduated from a university-prep high school (licei) could enroll in university in any major. A student who graduated from a technical high school for industry-sector professionals (istituti industriali) could enroll in only a few majors and most often did not enroll in university at all. In 1961, the Italian government allowed graduates with a technical diploma to enroll in university STEM majors for the first time. Technical graduates embraced this opportunity to the extent that freshman enrolment in STEM programs had increased by 216% by 1968 [...]

To analyze the effects of this reform, I collected high school records, university transcripts, and income tax returns for the population of students that completed high school in Milan between 1958 and 1968. I chose Milan because it is Italy’s commercial capital and second largest city. It has the thickest market for university graduates and university-type jobs, and is believed to be the place where a university graduate can earn the highest returns.

The reforms resulted in higher university access but a lower value of education.

The reform was successful in increasing university access among students with a technical diploma. After 1961, many technical students enrolled in university and completed their degrees. However, I find little evidence that technical students gained positive returns to university STEM education. This is an important result for two reasons:

• STEM degrees were leading to high-paying occupations and
• the outside option of technical students was to enter the labour market with just a high school diploma.

To explain these findings, I lay out a simple framework in which enrolment expansions affect returns to education through three main channels:

• higher supply leads to lower wages,
• higher enrolment crowds university resources and decreases the quality of education,
• learning is lower in classes with students from different types of high school.

Thanks to the reforms you got crowding of university spending, peer effects, and changes in major choices.

Several findings suggest that the enrolment expansion following the policy implementation lowered the returns to a STEM degree. To analyze changes in the value of a university education, I focus on the students who were not directly affected by the reform – the graduates from university-prep high schools. Among these students, returns to STEM education declined after 1961 to the point of erasing the pre-reform income premium associated with a STEM degree.

This decline can be partially explained by a lower amount of skills acquired in STEM majors after 1961. I find that human capital (measured by absolute grades) decreased more in STEM courses in which resources became more crowded and in which the entry of technical students had greater disruptive potential. Overall, lower resources per student can explain 31% of the income decline, while the change in class composition can explain another 37.3%. The remaining share can be attributed to higher supply of workers with a university STEM education or possibly other minor channels of general equilibrium effects.

By decreasing the value of STEM education, the reform might have deprived STEM majors of talented students. After 1961, many more students with a university-prep diploma decided to enroll in university majors that were still not accessible to technical students. This effect was concentrated among the students with higher high school grades.

Policy conclusions?

There are instances in which students should invest more in education. For students who do not have the resources to pay for education, public intervention is needed to improve access, but should just ease the financial constraints of students under-investing in education. Public intervention, should not take the form of greatly expanded education provision by state-controlled universities. The inefficiencies in the public provision of education might be magnified by enrolment expansions and might limit the benefits for targeted students.

Ref.:

• Bianchi, N (2014), “The General Equilibrium Effects of Educational Expansion”, Working Paper.

Education and labour markets

Bill Kaye-Blake writes In praise of liberal arts:

One of the issues we examined was ‘mismatch’. With the NZ data, there wasn’t much we could do. There just isn’t enough information on what happens to students after they leave tertiary education. I know that the pay-off to a liberal arts education for me was a long time coming — it isn’t enough to follow people for two years or five years. To cite our conclusion:

Finally, mismatches between employment and field of study and/or qualification level are often cited as a possible driver of low returns. There is little evidence that observed mismatches are in fact mismatches at all. However, if persistent mismatching is going on due to policy or market failures, this could be having a significant impact on returns. Whether that is the case or not is an open question.

Mismatch actually refers to two separate things. One is qualification mismatch — people getting Bachelor’s degrees when employers really want trade qualifications. The second is subject-matter mismatch — university students studying French literature when employers want computer science grads.

But if there is a mismatch in either sense, isn't the real question, What are prices not adjusting? If there is an excess demand (supply) for a particular qualification/skill why are wages not increasing (decreasing)? Thus is the problem got more to do with labour markets, and their regulation, than it has to do with education as such?

Gender and human capital

It is common today for people to note that females are more numerous than males in most levels of education, and that they perform better in school. The obvious question this raises is Why? One possible answer is that there are simply biological differences between men and women that make men better at tasks that require force, while women are better at task for which reasoning is paramount. Over at the Economic Logic blog the Economic Logician comments on this idea:

Mark Pitt, Mark Rosenzweig and Nazmul Hassan build a model of investment in human capital that differentiates genders. Better nutrition improves strength and education improves skills. Individuals make these choices, as well as in which activities to work. Using panel data from rural Bangladesh, they find that model is a reasonable description of reality. That is particularly interesting, because rural Bangladesh does not strike me as an economy where brain would dominate brawn. Also of interest is that improvements in health do not increase education for men, it may even reduce it, while women education clearly benefits from them. Thus policies that focus on health improvements are likely to improve women's schooling more than men's, lead to more occupational differentiation across genders, and a larger gender wag gap.

An interesting result, should this turnout to be true, is that as the so-called "knowledge economy" expands more intelligence/education will be asked for from employees, replacing the need for force, and thus women will find more opportunities and better pay. This will result in a gender pay gap.