The Methodology of Inequality: A Chat with Samuel Myers Jr.

Categories: Quantitative


Economist Samuel L. Myers Jr.

What we know and what we can prove are often quite separate, as any good researcher (or lawyer) will testify. Understanding that, Samuel L. Myers, Jr., has spent his career as both an academic and an advocate bridging that particular chasm, pioneering econometric methods to first study areas like law enforcement, housing, government aid and food availability and then to demonstrate to policymakers the inequalities that have dogged minorities and the poor.

Recognizing Myers’s contributions, the Urban Affairs Association (UAA) and SAGE Publishing will present him with the Marilyn J. Gittell Activist Scholar Award later this month at the UAA’s annual meeting. The award’s nominating committee unanimously selected Myers, who directs the Roy Wilkins Center for Human Relations and Social Justice at the University of Minnesota, based on how his  “trajectory and breadth of work brings to light the real material conditions of racial income inequality…. We appreciated especially his political economic analyses that reveal, challenge and inform the discursive battles shaping policy that produce racial income inequality.”

Myers, for his part, is modest about his contributions to both the field and to its methodology. “I do not consider myself an advocate in the traditional sense,” he says. “I see myself as someone empowering advocates and providing them with the tools and skills they need to be effective.”

MethodSpace asked Myers a few questions about his research methodology, starting with a description of his first major project:

My first big advocacy/research project in the Twin Cities with a broad and far-reaching impact was a report the Wilkins Center did on behalf of the Minneapolis Urban League concerning food prices. Local leaders were concerned about the pending relocation of a chain supermarket. Church members submitted their grocery receipts from this large chain to prove to the chain that the inner city was a viable market. At first, the Urban League asked me to analyze the grocery receipts to make the case on their behalf.  I responded that it was not obvious that collecting these receipts answered the question that the community members wanted answered:  what is best for the community? If prices were higher in the inner city than in the suburbs, was it in the best interest of the community to literally beg the food store to remain?  From there, our research team was able to design a study that asked and answered the question of whether the poor pay more. We found that the food quality was lower and the food prices higher in the neighborhoods where low-income African Americans lived versus in the suburbs. This report helped the Urban League change its strategy and also resulted in one of my most frequently cited publications in an academic journal.

So, what got me started was a community-initiated policy question that could be answered using the tools and skills of economics.

How does the methodology of looking at disparities differ from methods as applied to other research efforts?

Most of the econometric methodologies for looking at disparities use the same tools and techniques used in looking at inequality generally. The best tools are the ones that are not limited in their scope to the analysis of disparities. As a result, when one uses conventional tools with widespread acceptance within the broader research community and applies them to specific areas of disparities, one has the opportunity generalize and to use the disparities as an illustration that can be read and embraced across topics.

In particular, are there obstacles to getting good data for all communities?

Yes. But at the same time this is a generic research issue of selection bias, of non-response errors, and incomplete coverage.

Is big data helpful? How could it be better?

There are many problems with some of the data we often use to measure inequality and racial disparities. The big data often suffer from the problems described above. What is needed is more attention to the biases and the limits of these major data sets and the impacts on the policy decisions that result

What sort of innovation would you like to see in research methods to help your activities?

There are many things that are knowable but that are not measured or measurable. An example is peoples’ brains and things that are triggered in their brains when otherness is confronted. By otherness I mean things or people or events that deviate from our comfort zones: a young black male walking down the street holding a can in a brown paper bag. Maybe fMRI techniques can be used to uncover how these triggers can be changed through diversity training and education of, let’s say police officers, so that we can reduce the incidence of adverse events (e.g. police use of excess force against black males).

Of course, this type of innovation violates core principles of privacy. So, there is the need to develop less intrusive measures that yield the same results.


Interested in the advocacy side of Myers’ career? Click here for more Q&A.

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