Sendhil Mullainathan

166 papers receiving 36.3k citations

Sendhil Mullainathan's Hit Papers

An algorithmic approach to reducing unexplained pain disparities in underserved populations 2021 · 165 citations
1650+5+10Years since publication10002.0k3.0k

Peers

Sendhil Mullainathan
Comparison fields: 5 of 212
  • Health Informatics 1.4k
  • General Decision Sciences 1.7k
  • Accounting 9.6k
  • Safety Research 4.0k
  • Economics and Econometrics 12.5k
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Countries citing papers authored by Sendhil Mullainathan

Since Specialization
Citations

This map shows the geographic impact of Sendhil Mullainathan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sendhil Mullainathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sendhil Mullainathan more than expected).

Fields of papers citing papers by Sendhil Mullainathan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sendhil Mullainathan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sendhil Mullainathan. The network helps show where Sendhil Mullainathan may publish in the future.

Co-authors

The 25 scholars most cited alongside Sendhil Mullainathan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sendhil Mullainathan Line = papers co-authored together Sendhil Mullainathan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 175 papers — load more, or switch the sort, to bring in the rest.

#Work
1
How Much Should We Trust Differences-In-Differences Estimates?
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20047614
2
Dissecting racial bias in an algorithm used to manage the health of populations
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20193133
3
Enjoying the Quiet Life? Corporate Governance and Managerial Preferences
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20032867
4
Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination
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20042842
5
Poverty Impedes Cognitive Function
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20131690
6
Ferreting out Tunneling: An Application to Indian Business Groups
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20021220
7
Are CEOs Rewarded for Luck? The Ones Without Principals Are
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20011174
8
Machine Learning: An Applied Econometric Approach
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20171100
9
Scarcity: Why Having Too Little Means So Much
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20131046
10
Do People Mean What They Say? Implications for Subjective Survey Data
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20011027
11
Some Consequences of Having Too Little
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2012920
12
The Market for News
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2005843
13
Behavior and Energy Policy
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2010619
14 2000479
15 2003429
16
Getting to the Top of Mind: How Reminders Increase Saving
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2016375
17
Human Decisions and Machine Predictions
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2017365
18 2010361
19 2005355
20
Prediction Policy Problems
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2015345

About Sendhil Mullainathan

Sendhil Mullainathan is a scholar working on Economics and Econometrics, Sociology and Political Science, Accounting, General Decision Sciences and Safety Research, having authored 175 papers that have together received 38.7k indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (25 papers), Financial Literacy, Pension, Retirement Analysis (21 papers), Corporate Finance and Governance (13 papers), Housing Market and Economics (12 papers), Experimental Behavioral Economics Studies (12 papers), Ethics and Social Impacts of AI (10 papers), Explainable Artificial Intelligence (XAI) (10 papers) and Media Influence and Politics (9 papers). The work is most often cited by research in Health Informatics (1.4k citations), General Decision Sciences (1.7k citations), Accounting (9.6k citations), Safety Research (4.0k citations) and Economics and Econometrics (12.5k citations). Sendhil Mullainathan has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Marianne Bertrand, Esther Duflo, Eldar Shafir, Ziad Obermeyer, Brian W. Powers, Christine Vogeli, Jann Spiess, Andrei Shleifer, Anuj Shah and Jon Kleinberg. Their work appears in journals such as The Quarterly Journal of Economics, American Economic Review, Science, Proceedings of the National Academy of Sciences and The Journal of Economic Perspectives.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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