← back to explore
Abhijit Banerjee
Researchers / independent engineers · Science/Research · milestone at age 26 ·
T1 Global iconMilestone (age 26)
Completed PhD in economics from Harvard at age 26 under Eric Maskin, having studied at the University of Calcutta and JNU before making early contributions to development economics.
Born in Mumbai to economists, Banerjee studied at Calcutta and JNU before completing his Harvard PhD at 26, later co-founding the Abdul Latif Jameel Poverty Action Lab (J-PAL) and pioneering randomized controlled trials in development economics.
Starting point
Born in Mumbai, India to two economist parents; his father was a professor of economics and his mother was also an economics academic; grew up in a household deeply immersed in economic thinking.
Current position (2025)
Ford Foundation International Professor of Economics at MIT; co-founder of the Abdul Latif Jameel Poverty Action Lab (J-PAL); Nobel Laureate in Economics (2019).
How this path compounded
01 Starting advantages
10/24 starting-position score
Strongest documented signals: Parent / family domain, Elite institution pipeline, Dedicated mentor / coach.
Describes the starting position, not what the person later made of it.
Cohort percentile: 91
02 Built or converted leverage
17/25 multiplying-capacity score
Strongest observed levers:Scarce skill depth, Elite ecosystem network, Concentration intensity.
Measures what was present, not whether it was inherited, earned, self-built, external, or mixed.
Cohort percentile: 98
03 Compounding trajectory
7 documented steps
The timeline below shows the sequence of work and transitions around the selected early milestone. It is evidence of a path, not proof that every step was necessary.
Milestone at age 26
04 Observed career standing
T1 · Global icon
Legendary or globally iconic career standing. The tier summarizes documented career recognition through the data cutoff—not Abhijit Banerjee's worth or future potential.
Question four · where did the leverage come from?
Abhijit Banerjee's leverage provenance
Each non-zero lever gets a best-supported origin, evidence signals, and confidence. Unresolved is the honest default when the biography cannot distinguish self-built, advantage-enabled, earned, external, or mixed.
Scarce skill depth3/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Parent / family domain (2/2)Dedicated mentor / coach (2/2)Elite institution pipeline (2/2)
Elite ecosystem network3/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Inherited audience / network (1/2)Parent / family domain (2/2)Elite institution pipeline (2/2)Frontier geography (1/2)
Concentration intensity3/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Family financial platform (1/2)Dedicated mentor / coach (2/2)
Domain proximity2/2
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Direct domain exposure (1/2)Parent / family domain (2/2)Frontier geography (1/2)Elite institution pipeline (2/2)
Prior reps2/3
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Parent / family domain (2/2)Dedicated mentor / coach (2/2)Elite institution pipeline (2/2)
Structural wave / timing2/3
Externalmedium confidence
A structural wave is external to the person, even when their position improved access to it.
Frontier geography (1/2)
Complementary team1/2
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Elite institution pipeline (2/2)
Capital safety1/2
Advantage-enabledmedium confidence
One or more documented starting advantages plausibly enabled this lever.
Family financial platform (1/2)Elite institution pipeline (2/2)
This is a bounded inference from the current annotations—not a claim about private effort, merit, or the percentage of Abhijit Banerjee's outcome attributable to any origin.
Luck is not a leftover score.Structural luck, Encounter luck, Event luck, Outcome variance can change every arrow in the path. This successful-only dataset cannot observe the near-identical paths that did not break through, so luck stays visible and unscored.
Within Researchers / independent engineers, Abhijit Banerjee's starting-advantage total is at the 91th percentile. Separately, their built or converted leverage total is at the 98th percentile. Other T1 profiles average 8.9 / 24 starting advantage and 13.6 / 25 leverage. Similar scores appear in other tiers, so these figures describe positioning—not a cause.
Trajectory
- 1981 · age 20
Graduated from University of Calcutta
Completed his BSc in economics at the University of Calcutta, Presidency College.
- 1983 · age 22
Graduated from JNU with MA in economics
Completed his MA in economics at Jawaharlal Nehru University in Delhi.
- 1988 · age 26
Completed PhD at Harvard University
Earned his doctorate in economics from Harvard under Eric Maskin, with a thesis on informational economics.
- 1988 · age 26
Joined Princeton as assistant professor
Began his faculty career at Princeton University as an assistant professor of economics.
- 1993 · age 32
Joined MIT as professor
Moved to MIT as a professor of economics, where he would establish his development economics research program.
- 2003 · age 42
Co-founded J-PAL at MIT
Co-founded the Abdul Latif Jameel Poverty Action Lab with Esther Duflo and Sendhil Mullainathan, pioneering the use of randomized controlled trials in development economics.
- 2019 · age 58
Awarded Nobel Prize in Economics
Shared the Nobel Memorial Prize in Economic Sciences with Esther Duflo and Michael Kremer for their experimental approach to alleviating global poverty.
Primary leverage engine
Technical depth
Scarce technical / intellectual depth
Secondary engine
Elite academic network
Built/converted leverage
17 / 25
evidence: Medium
Built or converted leverage
Multiplying capacity documented later in the path. Measures what was present, not whether it was inherited, earned, self-built, external, or mixed.
Started serious reps before 20
0/1
Elite ecosystem network
3/3
Structural wave / timing
2/3
Concentration intensity
3/3
Starting-advantage scores (0–2 each)
Access or conditions documented near the beginning of the path. Zero means "no clear evidence in reviewed sources," not "advantage was absent."
Family financial platform
1/2
Parent / family domain
2/2
Inherited audience / network
1/2
Elite institution pipeline
2/2
Dedicated mentor / coach
2/2
Exceptional peer / cofounder
0/2
Direct domain exposure
1/2
Prodigy / innate ability
0/2
Adversity / constraint catalyst
0/2
Family context
Born in Mumbai, India; both his parents were economists. His father was a professor of economics and his mother was also an economics academic.
Parent / family domain
Both parents were economists, providing direct domain mentorship and deep intellectual environment in economics from childhood.
Archetype & tags
Family-domain apprenticeshipeconomist parentsCalcutta/JNU/Harvard pipelineMaskin mentorshipdevelopment economicsRCTsNobel Prize
Evidence summary
Banerjee was born in Mumbai to two economist parents, providing direct domain exposure from childhood. He studied at the University of Calcutta and Jawaharlal Nehru University before completing his Harvard PhD at 26 under Eric Maskin. His parents' economics expertise and the Harvard economics ecosystem were key advantages. He later co-founded J-PAL and pioneered the use of randomized controlled trials in development economics.
advantage confidence: Medium · source count: 3 · audit: not_independently_audited · status: subagent_researched_beta
Sources
Related — same primary engine