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  • 15th Oct 2019

Humble Empiricists win the Nobel Prize in Economics!

A huge congratulations to Abhijit Banerjee, Esther Duflo and Michael Kremer who have just won the 2019 Nobel Prize in Economics. 

All three were an inspiration for many of us at BIT. The book ‘Poor Economics’ by Dulfo and Banerjee; Kremer’s deworming study; and Duflo’s TED talk on ‘social experiments to fight poverty’, to cite only a few, motivated many of our team members to pursue careers in applied research.

Banerjee, Duflo and Kremer caused a revolution in development economics, and have closely inspired much of BIT’s international development work (for example BIT interventions that have doubled adherence to TB medication in Moldova, reduced headteacher absenteeism in Peru, and increased financial inclusion behaviours in Mexico).

Their impact has also extended far beyond international development and into the work organisations like BIT now do in higher-income countries. Their efforts to build applied research teams and institutions has structurally changed how social science research is now conducted. (And to reciprocate we are now supporting the creation of experimental units in developing economies including Bangladesh, Indonesia and Tanzania).

They have taught us the importance of being curious, humble about what we know, to question our priors based on evidence, and to use our research skills to find answers to practical problems. They have pushed us beyond simply learning “what works”, to think about what works best. Like Duflo, we now strive every day to become plumbers, improving the nuts and bolts of public policy.

The prize should, however, not be seen as revolution complete. Seeing the volume of applied RCTs currently published can make it seem that evidence-based policy is now the norm. It’s not. An overwhelming majority of policies still get rolled out without having undergone rigorous evaluation. 

So here is to hoping that this Nobel Prize inspires a new generation of plumbers – designing and testing interventions to improve life in messy real-world settings.

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