Sendhil Mullainathan

Sendhil Mullainathan (Template:Pronunciation) (born c. 1973) is an American professor of economics and professor of electrical engineering and computer science at the Massachusetts Institute of Technology.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>

Early life and career

Born in a small farming village in Tamil Nadu, India, Mullainathan moved to the Los Angeles area in 1980.<ref>Template:Cite news</ref><ref name=":0">{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> His father studied and later worked in aerospace engineering.<ref name=":0" /> As security clearance laws in the US aerospace industry were tightened in the 1980s, his father lost his job.<ref name=":0" /> His parents subsequently operated a video store.<ref name=":0" />

He received his B.A. in computer science, mathematics, and economics from Cornell University in 1993 and he completed his Ph.D. in economics from Harvard University 1993–1998.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>

Mullainathan was a professor of Computation and Behavioral Science at the University of Chicago Booth School of Business from 2018–2024. He is the author of Scarcity: Why Having Too Little Means So Much<ref>Template:Cite book</ref> (with Eldar Shafir). He was hired with tenure by Harvard in 2004 after having spent six years at MIT.

Mullainathan is a recipient of a MacArthur Foundation "genius grant" and conducts research on development economics, behavioral economics, and corporate finance. He is co-founder of Ideas 42, a non-profit organization that uses behavioral science to help solve social problems, and J-PAL, the MIT Poverty Action Lab and has made extensive academic contributions through the National Bureau of Economic Research and has also worked in government at the Consumer Financial Protection Bureau (CFPB). In May 2018, he moved from Harvard to the University of Chicago Booth School of Business, becoming the George C. Tiao Faculty Fellow.<ref>Template:Cite news</ref> In November 2018, he received the Infosys Prize (in Social Sciences category), one of the highest monetary awards in India that recognize excellence in science and research, for his contributions to the field of economics, especially behavioral economics.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> In 2024, he moved back to MIT as a professor on joint appointment between the Department of Economics and the School of Engineering.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>

Research contributions

Template:Development economics sidebar He has made substantial contributions to the field of behavioral economics as well as innovative additions to the literature on development topics, such as discrimination, corruption, and corporate governance. According to IDEAS/RePEc, he ranked 185th in September 2018 in terms of research among 54 233 registered economists (i.e, among the top 0.4%).<ref>Top 10% Authors. Retrieved November 5th, 2018.</ref>

Mullainathan's research topics have included cigarette taxes,<ref>Template:Cite journal</ref> corruption in obtaining driving licenses in Delhi,<ref>Template:Cite journal</ref> executive compensation,<ref>Template:Cite journal</ref><ref>Template:Cite journal</ref><ref>Template:Cite journal</ref> and the impact of poverty on cognitive function.<ref>Template:Cite journal</ref>

His influential 2004 paper "Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination" used a simple technique to measure labor market discrimination by switching the names at the top of resumes.<ref>Template:Cite journal</ref> Controlling for other factors, Mullainathan and his co-authors found that applications with white sounding names attained 50% more callbacks.

His most-cited<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> paper is a statistical methodology article, coauthored with Marianne Bertrand and Esther Duflo, which shows that a statistical procedure that is commonly used in the empirical economics literature frequently drastically overstates the statistical significance of the results. The article, "How Much Should We Trust Differences-In-Differences Estimates?"<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> shows that when a trend is occurring, a statistical test of whether there has been a "before and after" change regarding some event, such as the passage of a law, is likely to find that there has been a significant change due to the passage of the law even when the law had no effect on the trend.

Selected bibliography

Books

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Journal articles

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• Mullainathan, Sendil, Bertrand, Marianne, Duflo, Esther (February 2004) "How Much Should We Trust Differences-In-Differences Estimates?" Quarterly Journal of Economics 119 (1): 249–275. {{#invoke:CS1 identifiers|main|_template=doi}}
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Papers

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External links

• Harvard Faculty Web Page
• Scarcity: Why Having Too Little Means So Much
• The Mistake Busy People Make (Time)
• The Mental Strain of Making Do With Less (The New York Times)
• When a Co-Pay Gets in the Way of Health (The New York Times)
• Poverty Impedes Cognitive Function
• List of Working Papers Online
• TEDIndia Talk