Markets network member Felicia Ionescu  is a Principal Economist in the Research Department at the Board of Governors of the Federal Reserve System. She joined the Federal Reserve Bank in July 2013, prior to which she was an Assistant Professor of Economics at Colgate University. Ionescu is a macroeconomist working on human capital investment and household finance. In previous work, she has analyzed the interactions between education opportunities, college financing, and repayment incentives under the Federal Student Loan Program. She has also studied the risk of investment in college and the provision of insurance against such risk. Her current research i) examines the interplay between federal student loans and other types of credit, such as private student loans and credit cards, and ii) compares the effect of college and stocks---two high return, high risk investments---on the well-being of different types of individuals.
Describe your area of study and how it relates to current policy discussions surrounding inequality.
As a macroeconomist, I am interested in studying the effects of human capital investments on individual as well as aggregate economic outcomes. At the individual-level, my work has emphasized the risks associated with college investment in particular. This has led me to use models in which human capital investment reflects as closely as possible the key features of the institutional environment in which college education occurs. Perhaps the most important among these features is the lumpy and risky nature of the investment itself. To draw conclusions about how human capital and the policy environment (that I’ll say more about in a minute) matter for aggregate outcomes, though, we need more. We need to know how different people make different decisions—and how many of each “type” of person there are! After all, human capital is an investment that unlike most financial-market investments, has returns that vary—possibly very substantially—across individuals. This means of course that any given policy will matter differently to different people.
For these reasons, the foundation of my work lies in representing—in an empirically consistent manner the “particulars” of a college education in America, and characterizing—again in an empirically consistent manner—the unobserved heterogeneity in ability, preparedness (as measured by accumulated human capital), and wealth that underlies differences in individual human capital investment decisions and outcomes. With this as a basis, I have studied the interaction of education opportunities and college financing policies as well as the risk of financial investment in college and the provision of insurance against such risk. All of my work in this area emphasizes that human capital investment decisions occur within a broader context, and I’ve therefore tried to account for rich representations of choices and risks that individuals face over their lifetime.
Accounting for heterogeneity turns out to be key for assessing individual economics outcomes and evaluating policies. For instance, I find that students’ ability and preparedness are central to their decision to invest in college, while their parents’ wealth is not. However, even though prospective students from low-income backgrounds do not appear to be credit constrained when enrolling in college, they may be less well positioned to complete college and collect the returns to their college investment. Consequently, subsidizing repayment, for instance in the form of partial dischargeability for student loans, rather than relaxing credit constraints at the time of college enrollment, could make college investment more attractive for people from low-income families and improve their economic outcomes. For them, the risk of incurring student debt without completing college seems to be substantial and flexibility in loan repayments helps reduce this risk. In fact, my work demonstrates that a mechanism to share the risk of taking a student loan and failing to complete college improves the well-being of students and this type of failure insurance is most valuable for students coming from low-income backgrounds, who typically are less prepared for college and therefore, have a high failure probability.
Of course, individuals do not make human capital investment in isolation but in the context of a rich set of choices, constraints, and sources of risk. My recent research studies possible interactions between the decision to invest in college and another high-return, high-risk investment: stocks. Both investments have the power to improve economic outcomes; however, absent public funding, both are seen as the preserve of the wealthy. College is heavily subsidized with the explicit aim of promoting equality of opportunity, while stock market investment is not. An important point, though, is that stock market returns are market-driven, while returns to college are affected by individual characteristics and endowments. Does the power of college to increase well-being exceed that of stocks, as large subsidies to the former suggest? My research suggests that the answer is not straightforward. College increases lifetime earnings and promotes upward mobility by quite a bit, but only for those whose preparedness and ability poise them for success. College may thus exacerbate, rather than alleviate, existing disparities. A diversified stock index fund, on the other hand, may improve economic outcomes for those whose initial endowments or characteristics make investment in human capital a relatively unattractive option. In current work we assess whether certain individuals would prefer receiving a stock index fund to the current per-capita college subsidy.
What areas in the study of inequality are most in need of new research?
While I am not an expert on inequality, it seems to me that inequality takes a multitude of forms and should be studied in settings that account for the interactions of a variety of factors rather than studying each factor in isolation. What I have in mind here is, for example, exploring the interactions of the roles of institutions versus families and peers for economic outcomes, or the effects of the interplay between education, labor, and credit markets for inequality. One area that I think too little is known about is black-white differentials. Many quantitative aggregate, or “macro” models of inequality have been developed over the past two decades. Few, to my knowledge, have been applied to understanding the extent to which, say, shocks, initial conditions, and policies matter for the lives of the two primary racial groups in the US. This seems to me maybe the most important quantitative kind of heterogeneity around—both because of the proportion of population it applies to, and because of the vast size of the disparities themselves.
What advice do you have for emerging scholars in your field?
Related to my answer to the previous question, I would suggest taking the time to make connections between a narrowly defined concept with other aspects relevant to the research question at hand. This is a bit tricky, as sometimes dots might not apparently connect. My advice is to find inspiration for your research in the data, in observed behavior. The complex patterns of interactions that we see in reality, if ignored, may lead to misleading conclusions. Similarly, once something sparks your interest, don’t let your current toolkit immediately limit your approach to answering it. Use the tools that can provide the most comprehensive answers. If, like me, you find understanding heterogeneity and its implications interesting, these will involve data tools, theory tools, and computational tools. Of course, there is a fixed cost of acquiring a new skill set or even of understanding new tools. This is why working with co-authors helps: so attend good conferences and meet people. I found this approach much more rewarding in terms of learning and the depth of results. Finally, embrace criticism!
 The views expressed here are those of the author and do not necessarily reflect the views of the Federal Reserve Board or the Federal Reserve System.