Sometimes, the best way to understand an idea is to meet the people who devote their time and energy to studying it.
The Institute’s mission to conduct and promote research that will advance economic opportunity and inclusive growth for all Americans means engaging with a diverse group of scholars who approach opportunity and inclusion from many angles. This series of short Q&As spotlights those individuals, what led them to economics, and how their research connects to opportunity and inclusion. Plus: the most useful ideas in economics, abandoned projects, podcasts, and economists to lunch with.
For this installment, Institute Writer Lisa Camner McKay sat down with Teegawende Zeida, assistant professor of economics at Brock University, to discuss how discrimination impacts entrepreneurship, tax policy in countries with high inequality, and the value of understanding GDP.
What made you decide to study economics? Have you always known you wanted to be an economist, or was there something along your path that led you to economics?
Good question. I didn’t know much about economics before my freshman year in university. I had only a general idea about what GDP and economic growth rates meant. After discussing with family and friends, I ended up taking economics classes at university. I found it fascinating that there is an interconnection between economics and other fields. For instance, being able to combine rigorous tools borrowed from mathematics, statistics, and other social sciences, like sociology and history, has been a powerful way of tackling real-world problems. This is how the journey started for me.
What do you think is one of the most useful or powerful ideas in economics?
I would say the notion of opportunity cost, because it’s the value of other alternatives that we give up when we choose one of them. It is surprising how we use this—we all use it in our day-to-day decision-making without even referring to it.
For instance, using this time to do this Q&A is costly for both of us. But at the margin, we value it more than other alternates. This connects to the simple idea in economics that is there is no free lunch—doing something means not doing something else.
And if you even take this notion to the policy dimension, policymakers face what we usually call trade-offs, for instance, equity versus efficiency. This is a standard question that economists ask, for example, Do we need more taxes on high-income earners for redistribution purposes, even though this may generate or induce a reduction in investment or business formation? So you have this trade-off going on. I think this is a really powerful economic notion or principle that everyone uses in our day-to-day decision-making.
What are you studying now?
My current projects are mainly focused on understanding group-based wealth and income inequality. The first project builds on the well-documented historical and persistent wealth gap between Blacks and Whites in the United States. My co-authors and I propose a channel that we call a “wealth destruction shock” that partially or totally destroys Black-owned wealth. And we conjecture that this type of risk can help to explain the lower wealth accumulated by Black households over time relative to their White counterparts.
A second project is related to the lower rate of return for Black entrepreneurs relative to White entrepreneurs. This is due to both financial discrimination—the credit supply available to Black entrepreneurs—and consumer discrimination, which is the demand side. Then we analyze the Kauffman Firm Survey data, and we find that consumer discrimination outweighs the financial discrimination, at least for startups.
These are my two main ongoing projects.
What do you plan to work on next?
I’m interested in the design of optimal tax policies in the presence of growing wealth and income inequality in developing countries. In the context of developed countries, such as the United States, this question has gained a lot of attention in recent economics literature. So exploring these types of questions—what is an optimal tax policy that takes into account income inequality as well as entrepreneurship—and extending the analysis to developing countries is the next step of my research. This is where I would like to take this type of question once I have finished with my current projects.
How does your research relate to economic opportunity and inclusion?
My research primarily focuses on understanding the interconnection between entrepreneurship, inequality, and taxation. And it tries to answer the following questions: What is the effect of entrepreneurship on wealth and income distributions? What is the role of taxation in this context? Is it optimal? And if it’s not optimal, does another tax design improve upon efficiency and equity? This type of analysis, I think, is included in the broader sense of what you can call opportunity and growth.
Is there an economist, living or deceased, that you would want to have lunch with, and why would you choose that person?
Since I work a lot with heterogenous agents models, if I had the opportunity, I would choose S. Rao Aiyagari. He was one of the pioneers of the heterogeneous agent model. In his 1994 paper, he proposed a framework where ex ante identical agents become exposed to idiosyncratic income fluctuations. Because they know their income might fluctuate, they save money as a precaution so they can smooth their consumption over time. Now this model is a major workhorse in modern macroeconomics to study inequality and wealth distribution. It’s rare to see someone discussing or analyzing inequality or wealth distributions without referencing this type of model.
Is there an important economic statistic that you think is surprising or that you think people should know?
I was saying at the beginning of the Q&A, I didn’t know much about GDP [when I started college]. So for me, the most important statistic someone should know is GDP, the gross domestic product. It’s the primary measure of the economy’s total production stemming from all sectors. And the rise and fall in this indicator predicts the nature of the business cycle, namely expansions or recessions. So if you take a wide audience and tell them there’s a recession, many people may not know what a recession is. But if people know the indicator economists use to monitor the change in the business cycle, then this can give people a better way of assessing the ongoing business cycle.
Is there a project you’ve decided to abandon along the way, and how come?
Not really, not yet. But some are on standby. Sometimes because you have a tight schedule, you cannot work on everything. So you say, "Oh, I will put this aside," and then you’ll come back.
Do you listen to podcasts, and if so, do you have a favorite one?
Yes, I do. I find it valuable to listen to EconoFact with Michael Klein because the analysis concerns timely economic issues and it’s also accessible to a wide audience. So I think it’s useful from time to time to see what topics are there.
Is there a good piece of advice that you’ve received or encountered along your journey?
Yeah, and I think this applies to all researchers in general, that you should be open to broad topics, in all fields, because this could help you encounter interesting insights that will eventually help you understand your own research better. Let’s say you are doing theoretical work. If you don’t take the time to just step back a little bit and also read papers about empirical work, you may not see all the contributions that you could be making. So going back and forth can help you understand what you are doing.
If you could do any career or job for a day, what would it be?
I would want to be a doctor so I could help people recover their health. When I was child, my dream job was to be a doctor one day.
Lisa Camner McKay is a writer/analyst with the Opportunity & Inclusive Growth Institute at the Minneapolis Fed. In this role, she creates content for diverse audiences in support of the Institute’s policy and research work.