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The 2019 Nobel Prize in Economics Should Make Us Think in Peace Studies

Tuesday, October 15, 2019

The following blog post was contributed by Kroc School Associate Professor Topher McDougal.

The 2019 Nobel Memorial Prize in Economic Sciences was no surprise. For those in the development economics space (or, in my case, in sporadically elliptical orbit around it), the award to Esther Duflo and Abhijit Banerjee of MIT and Michael Kremer of Harvard was not a question of if, but of when. (In 2010, Esther Duflo won the American Economic Association’s John Bates Clark Medal, often seen as a predictor of a future Nobel.)

Development economics is the branch of economics that deals with how countries go from being poor to being rich. It is broadly characterized by a belief that, for a number of distinct reasons, economies in the poorest countries may behave fundamentally differently from those in rich countries – most fundamentally by yielding negative returns on investment, leading to the so-called “poverty trap.” By the turn of the millennium, the field had long been dominated by big theoretical debates: Does development aid break cycles of poverty in poor countries? If so, which sectors should be spurred by bilateral and multilateral grants and lending? Or does development aid generate dependency? Is it a form of neo-Colonial exploitation?

Duflo, Banerjee, Kremer, and many others in, or inspired by, the Abdul Latif Jameel Poverty Action Lab (J-PAL) at MIT, took a more humble, small-scale approach: they decided simply to test as scientifically as possible every individual development intervention they could. They reasoned that, far from its original single-minded focus on promoting industrialization, the development industry had proliferated over the latter half of the 20th century into many different specialty interventions: water and sanitation delivery, public health campaigns, anti-corruption projects, job training programs, police training, transportation and energy infrastructure, government decentralization initiatives, poverty alleviation programs, etc. Certainly we couldn’t paint this complex panoply of distinct interventions with the same broad brush? So starting in the late 1990s and early 2000s, these pioneers implemented what are called randomized control trials (or RCTs) to split beneficiaries of individual projects into similar groups, some of which receive the treatment, some of which don’t. In this way, the “randomistas,” as they came to be known, could break down big, contentious, and intractable questions about development into bite-sized, empirically testable chunks.

As an economist with an MIT pedigree, I have been gratified at the recognition the randomista revolution has received. The approach that J-PAL has used is problem-informed and solution-oriented. It is unabashedly instrumental: it does not use scientific methods to generate knowledge for its own sake, but to solve real-world problems. In this sense, it fits in perfectly with the Kroc School’s mission to “face the world’s most pressing challenges.” In fact, in the Kroc School’s own Program Design, Monitoring and Evaluation course, students learn how to design RCTs and other so-called “quasi-experimental” evaluations. In recent years, I’ve even led efforts to apply some of these same techniques to conflict studies and peacebuilding initiatives. In collaboration with the Kroc School’s Institute for Peace and Justice (Kroc IPJ) and the International NGO Mercy Corps, I designed a quasi-experimental evaluation of the effects of education and civic engagement trainings on support for radical groups in Somalia. This evaluation was just featured in the NISSEM Global Briefs, a collection examining education provision in post-conflict and low-resources settings.

But the randomista approach also comes with its downsides. William Easterly, a development economist at NYU, has criticized it insofar as it may merely pick low-hanging fruit, tackling symptoms of – but leaving unchanged – larger structural problems. This critique was shared by the pioneering MIT development economist, Alice Amsden, who coincidentally sat on my PhD committee. Amsden, who passed away in 2012, believed that development had gone regrettably soft: the multiplication of “friendly” approaches like microfinance and solar electrification made us feel good, but ultimately failed to produce countries capable of lifting their millions and billions out of poverty. Historically, only “fierce” industrialization had ever accomplished that.

But another critique hits a bit closer to home for those of us interested in producing more peaceful societies. To the extent that we in the peacebuilding field tend to believe that the best solutions are designed, implemented, and refined locally and collaboratively by those who have a stake in their success, RCTs may appear rather useless. The problem here is one randomistas dub “selection bias”: local groups that innovate creative resolutions to their conflicts are fundamentally different to local groups who never did. Whether the difference lies in organization, local institutions and norms, trust, education, culture, or something else entirely, it makes randomized treatment a meaningless concept. “Treatment” is by definition a neutral, technocratic intervention that is “done to” the beneficiary community from without. We often seek to promote idiosyncratically authentic and innovative solutions from within.

We still have a lot to learn about the dynamics of peace and conflict. The Kroc IPJ’s newly-launched Impact:Peace initiative seeks to understand better the efficacy of different peacebuilding approaches, and thereby how we can best allocate our scarce financial resources. It may be a more complex undertaking even than the work of development economists, insofar as the conflicts they seek to solve are wickedly complex, multifaceted, and networked. Our diagnoses of conflict type, severity, incidence, and so on, should deeply inform our courses of treatment and our prognoses. And much as in modern medicine, our treatments may simply represent ways of supporting local healing processes. Whatever approach we adopt to strike a useful balance between scientific generalizability and local determination, we will owe a lot to Duflo, Banerjee, Kremer, and their colleagues.

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Contact:

Topher McDougal
tlm@sandiego.edu
(619) 260-7927

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