Sendhil Mullainathan is a Professor of Economics at Harvard University. He was hired with tenure by Harvard in 2004 after having spent six years at MIT, first as a junior faculty member and then as a full Professor. He is a recipient of a MacArthur Foundation "genius grant" and conducts research on development economics, behavioral economics, and corporate finance. He is a co-founder of the MIT Poverty Action Lab and most recently of the think-tank Ideas42. Mullainathan received his B.A. in Computer Science, Mathematics, and Economics from Cornell University in 1993 and his Ph.D. in Economics from Harvard in 1998. Although he was born in a small farming village in India, Mullainathan moved to the Los Angeles area at age seven.
In a recent article published in the American Economic Review, he and co-author Marianne Bertrand tested for the existence of race-based hiring in the Boston and Chicago labor markets by sending out identical résumés to employers, half with traditionally African American names and the other half with traditionally Caucasian names. They observe a 53 percent difference in call-back rates between the two samples.
Another paper with co-authors (Marianne Bertrand, Dean Karlan, Eldar Shafir and Jon Zinman) shows small psychological factors can have large effects even in big decisions. They send out letters offering a loan to clients of a bank in South Africa. These letters are randomly varied to include or not huge psychologically important changes, such as including a female photo or not. They find that these small changes can have the same impact on take-up of the loan as dropping the interest rate by 2 to 5 percentage points. These large effects raise serious questions about what really drives decisions and whether the economic model is a good approximation.
A December 2007 paper in the Quarterly Journal of Economics, jointly written with Marianne Bertrand, Simeon Djankov and Rema Hanna, studies corruption in obtaining driving licenses in Delhi, India. On the average, individuals pay about twice the official amount to obtain a licence and very few take the legally required driving test, resulting in many unqualified yet licenced drivers. The magnitude of distortions in the allocation of licenses increases with citizens’ willingness to pay for licenses. These results support the view that corruption does not merely reflect transfers from citizens to bureaucrats but that it distorts allocation. The paper also shows that partial anti-corruption measures have only a limited impact because players in this system adapt to the new environment. Specifically, a ban on agents at one regional transport office is associated with a high percentage of unqualified drivers overcoming the residency requirement and obtaining licences at other license offices.
