Inequality in Educational Opportunity and Achievement: Evidence from Brazil

Inequality is ubiquitous. In some cases, it is believed to be the root cause of social division and economic stagnation. The general consensus is that education plays an important role in promoting socioeconomic mobility and levelling income inequality. In this sense, it is essential to inform economic policy in developing countries, in which inequality is generally more acute, about the dynamics of educational choice. Still, most of the existing empirical literature on higher education has focused on developed economies, partially due to data availability. Relying on relatively unexplored data from Brazil, my proposed research aims to shed new light to the education-inequality link.

These are the key questions I will address in my work: what circumstances drive university students to drop out before completing their degrees? If universities provide qualifications with high labour market returns, are these enjoyed by all individuals across the entire income distribution or only by some? Does state-sponsored financial aid work in the presence of possibly offsetting labour market forces?

Brazil offers an ideal environment for this analysis, as well as great opportunity in terms of still untapped microdata. One of the main data sources I plan to use is the Annual Census of Higher Education, which allows me to track the progression of each Brazilian student throughout their entire university career, linking individuals' socioeconomic characteristics to the exact date when they enrol and graduate or drop out of the university system.

To address the above issues, I plan to divide my work in three strands, which have never been done before for Brazil.

A. The importance of financial aid - In this first stage I will investigate the causal impact of financial aid on university performance (enrolment, drop-out and completion) using regression discontinuity design. Additionally, exploring other demographic characteristics - such as gender, race, age, field of study- can be used to understand if there are heterogeneous responses across different groups of students. This is interesting in itself and provides the background to develop part B and C.

B. The role of local labour market conditions - The objective of part B is to assess if and to what extent local labour markets favour the formation of highly educated workers, or if instead, they attract young people before they complete their university education. Here, I aim to identify the degree to which local markets are affected by proportional shifts to industry shares using a Bartik-type of instrumental variable or "multiple instrumentation" approaches.

C. A dynamic model of university careers - Finally, I will make use of discrete choice dynamic programming. The model should consist of a series of sequential binary choices: first choosing to enrol or not in college, and then choosing to continue in every subsequent period until completion of the degree, or withdraw, from the programme of study. This model and its estimates will allow me to address several counterfactual questions relevant to policy such as: how are university enrolment and completion rates affected by a change tuition fees? How do drop-out rates change if the local labour market is in a boom? Finally, I will pay special attention to the related work that from other social sciences, such as sociology, political science, and public policy, in order to better assess policy implications, establish possible complementarities in results and identify methodological improvements that might be needed for next research.