Overview

Researchers have compiled a multi-decade database of the super-rich. Building off the Forbes World's Billionaires lists from 1996-2014, scholars at Peterson Institute for International Economics have added a couple dozen more variables about each billionaire - including whether they were self-made or inherited their wealth. (Roughly half of European billionaires and one-third of U.S. billionaires got a significant financial boost from family, the authors estimate.)

http://www.iie.com/publications/interstitial.cfm?ResearchID=2917

Explore Structure




Index Type Example Value
0 dict { }
... ... ...
Key Type Example Value Comment
"category" str "New Sectors"
[Preview ]
A category representing where their money came from.
"from emerging" bool True Whether the money came from emerging markets.
"industry" str "Technology-Computer"
[Preview ]
The specific industry this billionaire profitted from.
"was political" bool False Whether the money came from politics.
"inherited" str "not inherited"
[Preview ]
The way that this money was inherited (or not inherited). Inheritance can come from a spouse, the father, or from multiple generations within a family (either 3, 4, or 5+).
"was founder" bool True Whether the billionaire was the founder of their company.
Value Count
"Financial" 800
"Non-Traded Sectors" 597
"Traded Sectors" 564
"New Sectors" 319
"Resource Related" 245
"0" 85
"Trucking" 1
"energy" 1
"Finance" 1
"" 1
Value Count
"Consumer" 471
"Retail, Restaurant" 281
"Real Estate" 280
"Money Management" 249
"Media" 219
"Technology-Computer" 208
"Diversified financial" 167
"Energy" 132
"Technology-Medical" 111
"Non-consumer industrial" 107
"Constrution" 97
"Mining and metals" 90
"Other" 83
"Hedge funds" 67
"Private equity/leveraged buyout" 25
"0" 16
"Venture Capital" 8
"services" 1
"banking" 1
"" 1
Value Count
"not inherited" 1688
"father" 558
"3rd generation" 210
"4th generation" 68
"spouse/widow" 59
"5th generation or longer" 31
Key Type Example Value Comment
"gender" str "male"
[Preview ]
A string representing their gender.
"age" int 40 The current age of the billionaire. Ages that are represented as -1 stand for ages that were not available in the data that was collected.
Value Count
"male" 2328
"female" 249
"" 34
"married couple" 3
Key Type Example Value Comment
"gdp" float 8.1e+12 The "Gross Domestic Product" of the country where the billionaire has citizenship. This is one of the primary indicators used to gauge the health of a country's economy. It represents the total dollar value of all goods and services produced over a specific time period; you can think of it as the size of the economy.
"region" str "North America"
[Preview ]
The region of the world where this billionaire lives.
"citizenship" str "United States"
[Preview ]
The name of the country that this billionaire has citizenship with.
"country code" str "USA"
[Preview ]
the 3-letter country code of the country where this billionaire has citizenship.
Value Count
"North America" 992
"Europe" 698
"East Asia" 535
"Latin America" 182
"Middle East/North Africa" 117
"South Asia" 69
"Sub-Saharan Africa" 20
"0" 1
Value Count
"United States" 903
"Germany" 160
"China" 153
"Russia" 119
"Japan" 96
"Brazil" 81
"Hong Kong" 77
"France" 72
"United Kingdom" 65
"India" 63
"Italy" 58
"Canada" 53
"Switzerland" 51
"Mexico" 44
"Taiwan" 40
"Spain" 37
"South Korea" 36
"Australia" 33
"Turkey" 32
"Indonesia" 31
"Malaysia" 28
"Sweden" 27
"Israel" 26
"Singapore" 26
"Thailand" 23
"Philippines" 22
"Saudi Arabia" 22
"Chile" 19
"South Africa" 12
"Argentina" 12
"Netherlands" 12
"Greece" 11
"Norway" 11
"Austria" 10
"Denmark" 10
"Peru" 9
"Lebanon" 9
"Egypt" 9
"Ukraine" 9
"Colombia" 8
"Ireland" 8
"Venezuela" 7
"Kuwait" 7
"Czech Republic" 6
"United Arab Emirates" 5
"Portugal" 5
"Poland" 5
"Kazakhstan" 5
"Finland" 4
"Morocco" 4
"Belgium" 4
"Nigeria" 4
"Cyprus" 4
"New Zealand" 3
"Monaco" 3
"Liechtenstein" 2
"Macau" 2
"Oman" 2
"Uganda" 1
"Romania" 1
"Angola" 1
"Guernsey" 1
"Vietnam" 1
"Tanzania" 1
"Georgia" 1
"St. Kitts and Nevis" 1
"Algeria" 1
"Bahrain" 1
"Ecuador" 1
"Swaziland" 1
"Bermuda" 1
"Lithuania" 1
"Nepal" 1
Value Count
"USA" 903
"DEU" 160
"CHN" 153
"RUS" 119
"JPN" 96
"BRA" 81
"HKG" 77
"FRA" 72
"GBR" 65
"IND" 63
"ITA" 58
"CAN" 53
"CHE" 51
"MEX" 44
"Taiwan" 40
"ESP" 37
"KOR" 36
"AUS" 33
"TUR" 32
"IDN" 31
"MYS" 28
"SWE" 27
"SGP" 26
"ISR" 26
"THA" 23
"PHL" 22
"SAU" 22
"CHL" 19
"ARG" 12
"ZAF" 12
"NLD" 12
"GRC" 11
"NOR" 11
"AUT" 10
"UKR" 9
"LBN" 9
"PER" 9
"IRL" 8
"COL" 8
"EGY" 8
"VEN" 7
"KWT" 7
"CZE" 6
"DEN" 6
"KAZ" 5
"ARE" 5
"FIN" 5
"POL" 5
"PRT" 5
"DNK" 4
"MAR" 4
"BEL" 4
"CYP" 4
"NGA" 4
"MCO" 3
"NZL" 3
"MAC" 2
"OMN" 2
"LIE" 2
"VNM" 1
"BHR" 1
"UGA" 1
"NPL" 1
"KNA" 1
"LTU" 1
"ROU" 1
"GEO" 1
"BMU" 1
"TZA" 1
"ECU" 1
"GGY" 1
"DZA" 1
"SWZ" 1
"AGO" 1
Key Type Example Value Comment
"founded" int 1975 The year that the company was founded.
"sector" str " Software"
[Preview ]
The sector of the business, or what segment of the economy they fit into.
"type" str "new"
[Preview ]
The type of business for this company.
"name" str "Microsoft"
[Preview ]
The name of the company.
"relationship" str "founder"
[Preview ]
The billionaires relationship to the company.
Value Count
"real estate" 177
"retail" 120
"media" 117
"construction" 96
"banking" 93
"pharmaceuticals" 76
"oil" 74
"software" 67
"hedge funds" 50
"technology" 36
"groceries" 31
"shipping" 30
"private equity" 26
"mining" 25
"electronics" 25
"hotels" 25
"insurance" 23
"" 23
"investment banking" 22
"steel" 21
"fashion" 19
"publishing" 17
"beer" 16
"venture capitalist" 16
"luxury goods" 16
"cars" 16
"soup" 16
"apparel" 15
"cement" 15
"entertainment" 15
"beverages" 14
"consumer goods" 14
"financial services" 14
"automobiles" 14
"candy" 13
"telecommunications" 13
"chemicals" 13
"petrochemicals" 13
"coal" 13
"casinos" 13
"cosmetics" 12
"textiles" 12
"e-commerce" 11
"asset management" 11
"internet" 11
"clothing " 11
"hospitals" 10
"restaurant" 10
"cleaning supplies" 10
"advertising" 10
"natural gas" 10
"medical supplies" 9
"food" 9
"oil and gas" 9
"clothing" 9
"toys" 9
"energy" 8
"furniture" 8
"metals, paper, cement" 8
"internet company" 8
"coffee" 8
"paper" 8
" Finance" 8
"cell phones" 8
"makeup" 8
"investment" 8
"food processing/commodities" 8
"education" 7
"metals" 7
"investments" 7
"medical devices" 7
"agriculture" 7
"finance" 7
"telecom" 7
"food packaging" 7
"manufacturing" 6
"timber" 6
"fertilizers" 6
"jeans" 6
"copper" 6
"liquor" 6
"aluminum" 6
"diamonds" 6
"leveraged buyouts" 6
"diversified investments" 6
"Banking" 6
"semiconductors" 6
"internet companies" 5
"supermarkets" 5
" technology" 5
"travel company" 5
"timber and paper" 5
"shopping centers" 5
"gas" 5
"energy, retail, manufacturing" 5
"beverages and food" 5
"restaurants" 5
" retail" 5
"home improvement retail" 5
"cheese" 5
... ...
Value Count
"new" 2264
"aquired" 196
"privatization" 42
"" 36
" new" 34
"subsidiary" 9
"state owned enterprise" 7
"acquired" 5
"new " 4
"merger" 3
"new/aquired" 3
"franchise" 2
"new, privitization" 2
" acquired" 2
"joint venture" 1
"neew" 1
"new division" 1
"franchise rights" 1
"privatized" 1
Value Count
"" 38
"Walmart" 18
"Campbell Soup" 16
"Hyatt" 15
"SAP AG" 12
"Microsoft" 11
"Sid Richardson Gasoline Co" 11
"Mars, Incorperated" 10
"The Gap" 10
"Oetker-Gruppe" 10
"S. C. Johnson & Son" 9
"Berkshire Hathaway" 9
"Ziff Davis Inc" 9
"Koch industries" 8
"Cargill" 8
"Votorantim Group" 8
"Standard Oil" 8
"Est?Lauder" 8
"Tetra Pak" 7
"Alfa Group" 7
"Cox Enterprises" 7
"Samsung" 7
"Maxingvest AG" 7
"Home Depot" 6
"SAS institute" 6
"Advance Publications" 6
"Metro AG" 6
"Carnival Corporation" 6
"Levi Strauss & co" 6
"Fidelity Investments" 6
"Loews Corporation" 6
"Construcciones y Contratas" 6
"Stryker Corporation" 6
"Holcim" 6
"Benckiser" 6
"Bechtel Corporation" 6
"Saudi Oger" 6
"McCaw Cellular" 6
"Sociedade de Turismo e Divers?es de Macau" 6
"Benetton Group" 6
"Tingyi" 5
"CMPC" 5
"Seagrams" 5
"BMW" 5
"Bloomberg" 5
"Dogus Holding" 5
"Globo Organizations" 5
"Kharafi Group" 5
"Orascom" 5
"Koc Holding" 5
"Amway" 5
"Glencore Xstrata" 5
"Banco Safra (now Saftra Group)" 5
"Hermes" 4
"Mori Building" 4
"Reliance" 4
"EMS-Chemie" 4
" H&M" 4
"Gazprom" 4
"Unibanco" 4
"Banamex" 4
"Boston Scientific" 4
"Electronic Data Systems" 4
"Blackstone Group" 4
"Enterprise Products" 4
"Google" 4
"Check Point" 4
"Al Rajhi bank" 4
"Infosys" 4
"Yahoo!" 4
"Tana Exploration Company" 4
"Ebay" 4
"George Weston Limited" 4
"Li & Fung Group" 4
"Carlson Inc" 4
"Sun Hung Kai Properties" 4
"Ferrovial" 4
"Chanel" 4
"Danaher" 4
"Kone Corporation" 4
"Marriot" 4
"Broadcom Corporation" 4
"Facebook" 4
"Franklin Resources" 4
"Kohlberg Kravis Roberts" 4
"Zodiac Maritime Agencies" 4
"Sun Microsystems" 4
"ArcelorMittal" 3
"Al-Ghurair Group" 3
"Benesse Corporation" 3
"LG Group" 3
"Allianz, Merk Finck & Co" 3
"Ferrero spa" 3
"Limited Brands" 3
"Equity Group Investments" 3
"Techint" 3
"Ito-Yokado" 3
"Grupo Modelo" 3
"Gerling Konzern" 3
"Usaha Tegas Sdn Bhd" 3
... ...
Value Count
"founder" 1214
"relation" 945
"owner" 94
"chairman" 76
"" 46
"investor" 36
"Chairman and Chief Executive Officer" 30
"CEO" 16
"president" 13
"ceo" 9
"former CEO" 8
"Chairman" 8
"founder and chairman" 7
"Relation" 6
"founder/chairman" 5
"investor " 5
"relation and chairman" 5
"founder and CEO" 4
"partner" 4
"founder/CEO" 4
"Vice Chairman" 3
"former chairman and CEO" 3
"executive chairman" 3
"employee" 3
"founder/relation" 3
"head of Microsoft's application software group" 2
"chariman" 2
"co-chairman" 2
"founder CEO owner" 2
"leadership" 2
"president and ceo" 2
"founder/vice chairman" 2
"founder, chairman" 2
"founder, chairman, ceo" 2
"vice-chairman" 2
"general director" 2
"Chief Executive" 2
"investor and CEO" 2
"relative" 2
"Global Head of Real Estate" 1
"founder, chairwoman, ceo" 1
"founder and executive vice chairman" 1
"deputy chairman" 1
"lawer" 1
"Chairman, CEO" 1
"Exectuitve Director" 1
"head of high-yield bond trading dept" 1
"inventor" 1
"Honorary President for Life" 1
"Vice President of Infrastructure Software" 1
"chairwomen" 1
"shareholder" 1
"director" 1
"founder/president" 1
"chairman of management committee" 1
"investor/founder" 1
"co-director of zinc, copper and lead" 1
"owner and former CEO" 1
"Chairman/founder" 1
"inherited" 1
"Chairman/shareholder" 1
"Head of Board of Directors" 1
"supervisory board or directors" 1
"owner and vice chair" 1
"relation and ceo" 1
"founder and executive chairman" 1
"COO" 1
"chairman and ceo" 1
"founder and chairwoman" 1
"lawyer" 1
"vice chairman" 1
"founder and ceo" 1
"Vice President" 1
"chairman of the board" 1
"relation/vice chairman" 1
Key Type Example Value Comment
"worth in billions" float 18.5 The number of billion of dollars that this billionaire is worth.
"how" dict { }
"type" str "founder non-finance"
[Preview ]
The type of billionaire that they are.
Value Count
"inherited" 953
"founder non-finance" 713
"self-made finance" 500
"privatized and resources" 236
"executive" 190
"" 22
Key Type Example Value Comment
"name" str "Bill Gates"
[Preview ]
The name of the billionaire.
"demographics" dict { }
"rank" int 1 The rank of this billionaire compared to the rest of the billionaires reported on. A lower rank means they make more money.
"location" dict { }
"year" int 1996 The year that data about this billionaire was collected.
"company" dict { }
"wealth" dict { }
Value Count
"Henry Sy" 3
"Masayoshi Son" 3
"Takemitsu Takizaki" 3
"Wee Cho Yaw" 3
"Saleh Kamel" 3
"Alberto Bailleres Gonzalez" 3
"Stanley Hubbard" 3
"Lee Shau Kee" 3
"Eliodoro Matte" 3
"Steven Spielberg" 3
"Hasso Plattner" 3
"Anne Cox Chambers" 3
"Larry Ellison" 3
"Rolf Gerling" 3
"Kwek Leng Beng" 3
"Richard Branson" 3
"Lorenzo Mendoza" 3
"Robert Bass" 3
"Robert Kuok" 3
"Klaus Tschira" 3
"Nicky Oppenheimer" 3
"Kumar Birla" 3
"Stephan Schmidheiny" 3
"Shoji Uehara" 3
"Donald Bren" 3
"Gordon Moore" 3
"Ted Turner" 3
"Curt Engelhorn" 3
"Dirk Ziff" 3
"Micky Arison" 3
"Ingvar Kamprad" 3
"Fayez Sarofim" 3
"Alain Wertheimer" 3
"Gordon Getty" 3
"Richard Rainwater" 3
"Ralph Lauren" 3
"George Soros" 3
"Sid Bass" 3
"Michael Dell" 3
"Michele Ferrero" 3
"Mary Alice Dorrance Malone" 3
"John Mars" 3
"John Sall" 3
"Soichiro Fukutake" 3
"Li Ka-shing" 3
"Dennis Washington" 3
"Carlos Slim Helu" 3
"Johanna Quandt" 3
"Craig McCaw" 3
"Jacques Servier" 3
"Charles Bronfman" 3
"Jeronimo Arango" 3
"Henry Hillman" 3
"David Koch" 3
"Serge Dassault" 3
"Dietmar Hopp" 3
"Antonio Ermirio de Moraes" 3
"Gerald Cavendish Grosvenor" 3
"Michael Bloomberg" 3
"Gregorio Perez Companc" 3
"Lakshmi Mittal" 3
"Ryoichi Jinnai" 3
"Ronald Lauder" 3
"Sam Zell" 3
"Kirk Kerkorian" 3
"Donald Hall" 3
"Jack Taylor" 3
"David Duffield" 3
"Riley Bechtel" 3
"Quek Leng Chan" 3
"Robert Ziff" 3
"James Jannard" 3
"Martha Ingram" 3
"Warren Buffett" 3
"Bill Gates" 3
"Jon Huntsman" 3
"Sumner Redstone" 3
"Paul Allen" 3
"Kunio Busujima" 3
"Luciano Benetton" 3
"Silvio Berlusconi" 3
"Akira Mori" 3
"Charles Koch" 3
"Mustafa Rahmi Koc" 3
"Maria Asuncion Aramburuzabala" 3
"Lee Kun-Hee" 3
"Alice Walton" 3
"Galen Weston" 3
"Julio Bozano" 3
"Charlotte Colket Weber" 3
"Reinhold Wuerth" 3
"Richard DeVos" 3
"Gustavo Cisneros" 3
"August von Finck" 3
"Thomas Schmidheiny" 3
"Doris Fisher" 3
"Abigail Johnson" 3
"Liliane Bettencourt" 3
"Leonard Lauder" 3
"Michael Otto" 3
... ...

Downloads

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Usage

This library has 1 function you can use.
import billionaires
list_of_billionaire = billionaires.get_billionaires()

Documentation

 billionaires.get_billionaires()

Returns information about all the billionaires.