Speaker

Abhijit Banerjee

Abhijit Banerjee

Indian-American development economist and the Ford Foundation International Professor of Economics at MIT. In 2019 he was awarded the Nobel Prize in Economics jointly with Esther Duflo and Michael Kremer, for the experimental approach to alleviating global poverty. With Duflo he co-founded J-PAL — the Abdul Latif Jameel Poverty Action Lab — the network of researchers that has made the randomised controlled trial (RCT) a standard instrument of development economics. He is the co-author of Poor Economics (2011) and Good Economics for Hard Times (2019), both written with Duflo.

Banerjee trained at the University of Calcutta and Jawaharlal Nehru University before completing his PhD at Harvard, supervised by Eric Maskin and Andreu Mas-Colell. He began as a pure theorist — his early work in social learning and a 1999 paper with Aghion and Piketty foreshadowed later secular-stagnation arguments — before turning to field experiments. He now also teaches PhD behavioural economics, the influence of which runs through his current theoretical work.

Core positions

Economists, on Banerjee’s account, understand growth poorly and should say so. The one durable insight is that fast growth runs out as a country exhausts its best inputs; what governs the timing and size of growth episodes — why some countries surge and stall — remains genuinely unexplained. He is correspondingly sceptical of confident development recipes extrapolated from small, idiosyncratic successes such as Singapore or Dubai, and of large institutional fixes like charter cities, which he regards as politically unstable rather than merely hard.

His methodological position is that the RCT is a theorist’s tool. Its value is not unbiased estimation — which he calls a red herring — but the ability to redesign the treatment in the field to chase the hypothesis in your head, interrogating a question the way good theory trains you to. The complement to this is his case for portable insights in economics education: teach the lens that lets you spot where a market’s assumptions fail, not the edifice of theorems for its own sake.

In the field, his graduation work with Duflo, Karlan, and others shows that cash transfers to the very poor pay off far better when paired with training and coaching. The mechanism, he argues, is confidence and process: the poorest have never succeeded at anything, and converting a daunting goal into concrete procedural steps — alongside the signal that someone believes in them — is itself the intervention.

In the wiki