Pakistan Institute of Development Economics

Signaling Labor Markets and Universities
Publication Year : 2022
Author: Sonan Memon

The most elite and prestigious universities (for instance Harvard or LUMS in Pakistan) serve to act as signals in the labor market, which means that they solve an information revelation problem. Jobs in various sectors such as graduate schools, corporate sector, and others such as data science and management consultancy require different types of abilities. It is complex and costly to evaluate these abilities and elite universities partially address this problem by restricting the set of potential workers that can be hired. Social scientists refer to this as “social capital”, which is the social networking and recognition acquired through prestigious schools. I use the term social capital in the way that French sociologist Pierre Bourdieu defined it; that is “the aggregate of potential resources which are linked to possession of a durable network of institutionalized relationships or mutual acquaintance”.

With millions of potential applicants, the desired labor force cannot be selected efficiently if all of them are evaluated, given the costs of processing information. Hence, top recruiters restrict the pool of potential applicants to some elite universities. Even with the advent of artificial intelligence, selection of labor force must be done from a relatively small sample of people. Consequently, along with endowing people with pure intellectual capital which has its own independent returns in the labor market and intrinsic value, elite universities also serve as pure signals in the market, improving labor market outcomes for all students who study there.

Consequently, decomposition of the various returns of education from elite universities becomes a natural question to address. To what extent, if at all is the knowledge and skill set of students attributable to training at such universities relative to students’ intrinsic motivation and innate ability? In addition, if substantial knowledge acquisition and skills are generated within such universities, what proportion of this is due to a student’s interaction with and lectures delivered by professors versus interaction and competition from capable peers versus access to learning resources such as libraries?

For instance, if the main returns stem from the social capital of connections, which are not directly due to professors, it is optimal for the latter to do less teaching and allocate it to low-paid teaching assistants instead. Similarly, if individuals’ innate ability and motivation are the dominant determinants of success in the labor market, professors should invest less on teaching. However, this policy has adverse effects (economists call it negative externality) for some students who wish to pursue graduate school, especially a PhD. Meanwhile, if the dominant driver of returns to education is the quality of lectures, there is a tradeoff between investing in teaching and research activity for professors. Lastly, if purely academic interactions with peers and access to learning resources are the dominant drivers of outcomes, then the professors can invest more time on research and less on teaching, assuming little intrinsic motivation to teach.

Clearly, there is substantial heterogeneity across students in terms of their career goals and demand for education type. For instance, those pursuing a PhD in economics would want to be trained for academia and rigorous analysis of economic models by professors. Meanwhile, economics majors who want to work in the corporate/public sector would not demand such training. For the latter category, the labor market returns are likely to be less correlated with direct interaction with professors. Of course, in practice such students do not actually interact much with professors, which is an efficient allocation of time for both parties. Nevertheless, the process of going through rigorous coursework can facilitate learning for all students, as well as signal certain capacities in the job market. For instance, critical thinking, writing and the ability to consistently exert effort toward an end-goal can be learned through coursework; these skills are highly sought-after in the job market.

On the one hand, the proportion of students pursuing graduate school is low (despite increasing over time), which limits the extent to which coursework can be tailored in line with their preferences. However, the professors are normally not trained to offer specific training for non-academic jobs, leading to an intermediate solution. That is to say that the focus of teaching is on intuition and less formalism, while covering the core concepts, which aims to teach all students certain generalizable and core thinking tools. Furthermore, some specific, advanced courses are offered to be palatable for those with academic ambitions while other non-rigorous courses are offered, suitable for students with non-academic goals.

Given the variation of goals and abilities across students, should different students pay different fees for the same undergraduate degree or a specific course? For instance, should the teaching fees be higher for students who want to pursue a PhD and should students with higher innate ability pay lower fees? Similarly, should students pay higher course-specific fees for advanced and rigorous courses taught by professors as compared with less rigorous courses taught by teaching fellows?

Any answers to such controversial questions will create ethical quandaries and will have implications for access to education across various socio-economic strata. If all students are studying in the same classroom, then the idea of paying different fees will face backlash since it will be perceived as discriminatory. However, since advanced and rigorous courses are chosen by specific student types, one can justify different fees if students are informed about it before enrollment and variation in fees helps improve professors’ motivation to work harder. Even if different student types are enrolled in the same course, we already have some mechanisms which create variation in costs. For instance, merit scholarships for best students financially reward them for innate ability and hard work. We also have need based scholarships for students who satisfy the university’s entrance criteria but cannot afford the fees.

With the help of data driven, rigorous research that is publicly verifiable and accessible, elite private universities can address these questions and design more efficient and tailored pricing strategies for the various student types. This process will raise thorny ethical questions which must be debated, and a democratic solution must be arrived at. This will require inputs from and consent of students, professors, and university administration.

The author is a Research Fellow at the Pakistan Institute of Development Economics (PIDE), Islamabad.

Signaling Labor Markets and Universities
Publication Year : 2022
Author: Sonan Memon

The most elite and prestigious universities (for instance Harvard or LUMS in Pakistan) serve to act as signals in the labor market, which means that they solve an information revelation problem. Jobs in various sectors such as graduate schools, corporate sector, and others such as data science and management consultancy require different types of abilities. It is complex and costly to evaluate these abilities and elite universities partially address this problem by restricting the set of potential workers that can be hired. Social scientists refer to this as “social capital”, which is the social networking and recognition acquired through prestigious schools. I use the term social capital in the way that French sociologist Pierre Bourdieu defined it; that is “the aggregate of potential resources which are linked to possession of a durable network of institutionalized relationships or mutual acquaintance”.

With millions of potential applicants, the desired labor force cannot be selected efficiently if all of them are evaluated, given the costs of processing information. Hence, top recruiters restrict the pool of potential applicants to some elite universities. Even with the advent of artificial intelligence, selection of labor force must be done from a relatively small sample of people. Consequently, along with endowing people with pure intellectual capital which has its own independent returns in the labor market and intrinsic value, elite universities also serve as pure signals in the market, improving labor market outcomes for all students who study there.

Consequently, decomposition of the various returns of education from elite universities becomes a natural question to address. To what extent, if at all is the knowledge and skill set of students attributable to training at such universities relative to students’ intrinsic motivation and innate ability? In addition, if substantial knowledge acquisition and skills are generated within such universities, what proportion of this is due to a student’s interaction with and lectures delivered by professors versus interaction and competition from capable peers versus access to learning resources such as libraries?

For instance, if the main returns stem from the social capital of connections, which are not directly due to professors, it is optimal for the latter to do less teaching and allocate it to low-paid teaching assistants instead. Similarly, if individuals’ innate ability and motivation are the dominant determinants of success in the labor market, professors should invest less on teaching. However, this policy has adverse effects (economists call it negative externality) for some students who wish to pursue graduate school, especially a PhD. Meanwhile, if the dominant driver of returns to education is the quality of lectures, there is a tradeoff between investing in teaching and research activity for professors. Lastly, if purely academic interactions with peers and access to learning resources are the dominant drivers of outcomes, then the professors can invest more time on research and less on teaching, assuming little intrinsic motivation to teach.

Clearly, there is substantial heterogeneity across students in terms of their career goals and demand for education type. For instance, those pursuing a PhD in economics would want to be trained for academia and rigorous analysis of economic models by professors. Meanwhile, economics majors who want to work in the corporate/public sector would not demand such training. For the latter category, the labor market returns are likely to be less correlated with direct interaction with professors. Of course, in practice such students do not actually interact much with professors, which is an efficient allocation of time for both parties. Nevertheless, the process of going through rigorous coursework can facilitate learning for all students, as well as signal certain capacities in the job market. For instance, critical thinking, writing and the ability to consistently exert effort toward an end-goal can be learned through coursework; these skills are highly sought-after in the job market.

On the one hand, the proportion of students pursuing graduate school is low (despite increasing over time), which limits the extent to which coursework can be tailored in line with their preferences. However, the professors are normally not trained to offer specific training for non-academic jobs, leading to an intermediate solution. That is to say that the focus of teaching is on intuition and less formalism, while covering the core concepts, which aims to teach all students certain generalizable and core thinking tools. Furthermore, some specific, advanced courses are offered to be palatable for those with academic ambitions while other non-rigorous courses are offered, suitable for students with non-academic goals.

Given the variation of goals and abilities across students, should different students pay different fees for the same undergraduate degree or a specific course? For instance, should the teaching fees be higher for students who want to pursue a PhD and should students with higher innate ability pay lower fees? Similarly, should students pay higher course-specific fees for advanced and rigorous courses taught by professors as compared with less rigorous courses taught by teaching fellows?

Any answers to such controversial questions will create ethical quandaries and will have implications for access to education across various socio-economic strata. If all students are studying in the same classroom, then the idea of paying different fees will face backlash since it will be perceived as discriminatory. However, since advanced and rigorous courses are chosen by specific student types, one can justify different fees if students are informed about it before enrollment and variation in fees helps improve professors’ motivation to work harder. Even if different student types are enrolled in the same course, we already have some mechanisms which create variation in costs. For instance, merit scholarships for best students financially reward them for innate ability and hard work. We also have need based scholarships for students who satisfy the university’s entrance criteria but cannot afford the fees.

With the help of data driven, rigorous research that is publicly verifiable and accessible, elite private universities can address these questions and design more efficient and tailored pricing strategies for the various student types. This process will raise thorny ethical questions which must be debated, and a democratic solution must be arrived at. This will require inputs from and consent of students, professors, and university administration.

The author is a Research Fellow at the Pakistan Institute of Development Economics (PIDE), Islamabad.