Evolution of Total Population , 1550-2000
Evolution of Global Extreme Poverty Cost of Basic Needs, 1820-2018
Evolution of Global Hunger, 1820-2018
Evolution of Global Extreme Poverty Dollar a Day, 1820-2018
Evolution of Cattle per Capita, 1600-2010
Evolution of Cropland per Capita, 1500-2010
Raking and performance of all available indicators for the entire period covered by the data (download all indicators)
Period | Best performing | Worst performing | Best ranking | Worst ranking |
---|---|---|---|---|
1820-1869 19 | Total Cattle | Global Hunger | Global Extreme Poverty Cost of Basic Needs |
Cropland per Capita |
1870-1919 19 | Total Cattle | Sheep per Capita | Global Extreme Poverty Cost of Basic Needs |
Cropland per Capita |
1920-1959 27 | Total Cattle | Composite Measure of Wellbeing |
Biodiversity - naturalness |
Cropland per Capita |
1960-2010 43 | Total Num. of Pigs | Total CO2 Emissions | Total CO2 Emissions | Total Population |
Overall 47 | N/A | N/A | Biodiversity - naturalness |
Cropland per Capita |
Click on the CPV badge next to an indicator below to download the corresponding indicator only for Cape Verde. The badge is only shown when data for Cape Verde are available. You can also download all available indicators for Cape Verde by clicking here
Clicking on the indicator's title takes you to the indicator's page as usual.
Cattle per CapitaCPV 1600 [42] 2010
Cropland per CapitaCPV 1500 [34] 2010
Goats per CapitaCPV 1600 [42] 2010
Pasture per CapitaCPV 1500 [34] 2010
Pigs per CapitaCPV 1600 [42] 2010
Sheep per CapitaCPV 1600 [42] 2010
Total CattleCPV 1500 [43] 2010
Total CroplandCPV 1600 [33] 2010
Total Number of GoatsCPV 1600 [42] 2010
Total Number of PigsCPV 1600 [42] 2010
Total Number of SheepCPV 1600 [42] 2010
Total PastureCPV 1600 [33] 2010
DemographyComposite Measure
of WellbeingCPV 1820 [19] 2000
Female life Expectancy at BirthCPV 1960 [5] 2000
Global Extreme Poverty (CBN)CPV 1820 [199] 2018
Global Extreme Poverty (DAD)CPV 1820 [199] 2018
Global HungerCPV 1820 [199] 2018
Life Expectancy at Birth (Total)CPV 1950 [60] 2009
Male life Expectancy at BirthCPV 1960 [5] 2000
Total PopulationCPV 1550 [14] 2000
Total Urban PopulationCPV 1600 [9] 2000
Urbanization RatioCPV 1800 [3] 2000
EnvironmentBiodiversity - naturalnessCPV 1500 [34] 2010
CO2 Emissions per CapitaCPV 1950 [7] 2010
Total CO2 EmissionsCPV 1950 [59] 2008
FinanceExchange Rates to UK PoundCPV 1952 [62] 2013
Exchange Rates to US DollarCPV 1952 [62] 2013
Gender Equality of NumeracyCPV 1910 [6] 1960
Gender Equality Years
of Education
Historical Gender Equality Index
Human CapitalEducational Inequality Gini
Coefficient
Numeracy (Total)CPV 1910 [6] 1960
InstitutionsArmed Conflicts (Internal)CPV 1500 [501] 2000
Armed Conflicts (International)CPV 1500 [501] 2000
Competitiveness of Executive
Recruitment (XRCOMP)CPV 1975 [38] 2012
Competitiveness of Participations
(PARCOMP)CPV 1975 [38] 2012
Executive Constraints
(XCONST)CPV 1975 [38] 2012
Homicide RatesCPV 1980 [4] 2008
Openness of Executive
Recruitment (XROPEN)CPV 1975 [38] 2012
Political CompetitionCPV 1975 [26] 2000
Political ParticipationCPV 1975 [26] 2000
Polity2 IndexCPV 1975 [38] 2012
Regulation of Chief Executive
Recruitment (XRREG)CPV 1975 [38] 2012
Anguilla[No Data]
Antigua and Barbuda1500 (5)-2013 (21)
Aruba[No Data]
Bonaire, Sint Eustatius and Saba[No Data]
British Virgin Islands[No Data]
Cayman Islands[No Data]
Curaçao[No Data]
Dominican Republic1500 (6)-2018 (39)
Guadeloupe[No Data]
Martinique[No Data]
Montserrat[No Data]
Puerto Rico[No Data]
Saint Kitts and Nevis1500 (5)-2010 (14)
Saint Martin (French part)[No Data]
Saint Vincent and the Grenadines1500 (5)-2010 (20)
Saint-Barthélemy[No Data]
Sint Maarten (Dutch part)[No Data]
Trinidad and Tobago1500 (5)-2018 (35)
Turks and Caicos Islands[No Data]
United States Virgin Islands[No Data] Central America
Bolivia (Plurinational State of)1500 (8)-2018 (42)
Falkland Islands (Malvinas)[No Data]
French Guiana[No Data]
Venezuela (Bolivarian Republic of)1500 (8)-2018 (40)
Northern AmericaBermuda[No Data]
Greenland[No Data]
Saint Pierre and Miquelon[No Data]
Turkmenistan1500 (16)-2016 (27)
Eastern AsiaChina, Hong Kong Special Administrative Region[No Data]
China, Macao Special Administrative Region[No Data]
Åland Islands[No Data]
Channel Islands[No Data]
Faeroe Islands[No Data]
Guernsey[No Data]
Isle of Man[No Data]
Jersey[No Data]
Sark[No Data]
Svalbard and Jan Mayen Islands[No Data]
United Kingdom of Great Britain and Northern Ireland1500 (20)-2018 (56)
Guam[No Data]
Marshall Islands1500 (4)-2010 (5)
Micronesia (Federated States of)1500 (2)-2013 (6)
Northern Mariana Islands[No Data]
American Samoa[No Data]
French Polynesia[No Data]
Niue[No Data]
Pitcairn[No Data]
Tokelau[No Data]
Wallis and Futuna Islands[No Data]
Åland Islands[No Data]
Channel Islands[No Data]
Faeroe Islands[No Data]
Gibraltar[No Data]
Greenland[No Data]
Guernsey[No Data]
Holy See[No Data]
Isle of Man[No Data]
Jersey[No Data]
Netherlands1500 (22)-2018 (43)
Sark[No Data]
Svalbard and Jan Mayen Islands[No Data]
Switzerland1500 (19)-2018 (44)
United Kingdom of Great Britain and Northern Ireland1500 (20)-2018 (56)
Anguilla[No Data]
Antigua and Barbuda1500 (5)-2013 (21)
Aruba[No Data]
Bermuda[No Data]
Bolivia (Plurinational State of)1500 (8)-2018 (42)
Bonaire, Sint Eustatius and Saba[No Data]
British Virgin Islands[No Data]
Cayman Islands[No Data]
Curaçao[No Data]
Dominican Republic1500 (6)-2018 (39)
Falkland Islands (Malvinas)[No Data]
French Guiana[No Data]
Guadeloupe[No Data]
Martinique[No Data]
Montserrat[No Data]
Puerto Rico[No Data]
Saint Kitts and Nevis1500 (5)-2010 (14)
Saint Martin (French part)[No Data]
Saint Pierre and Miquelon[No Data]
Saint Vincent and the Grenadines1500 (5)-2010 (20)
Saint-Barthélemy[No Data]
Sint Maarten (Dutch part)[No Data]
Trinidad and Tobago1500 (5)-2018 (35)
Turks and Caicos Islands[No Data]
United States Virgin Islands[No Data]
Afghanistan1500 (16)-2016 (28)
American Samoa[No Data]
Brunei Darussalam1500 (12)-2013 (19)
French Polynesia[No Data]
Guam[No Data]
Marshall Islands1500 (4)-2010 (5)
Micronesia (Federated States of)1500 (2)-2013 (6)
New Caledonia[No Data]
Niue[No Data]
Norfolk Island[No Data]
Northern Mariana Islands[No Data]
Philippines1500 (17)-2018 (46)
Pitcairn[No Data]
Solomon Islands1500 (11)-2018 (25)
Tokelau[No Data]
Wallis and Futuna Islands[No Data]
China, Hong Kong Special Administrative Region[No Data]
China, Macao Special Administrative Region[No Data]
Guinea-Bissau1500 (16)-2018 (31)
Mayotte[No Data]
Réunion[No Data]
Saint Helena[No Data]
Sao Tome and Principe1500 (14)-2016 (20)
Sierra Leone1500 (15)-2018 (36)
South Africa1500 (14)-2018 (49)
In 2010, the Netherlands Organisation for Scientific Research (NWO) awarded a subsidy to the Clio Infra project, of which Jan Luiten van Zanden was the main applicant and which is hosted by the International Institute of Social History (IISH). Clio Infra has set up a number of interconnected databases containing worldwide data on social, economic, and institutional indicators for the past five centuries, with special attention to the past 200 years. These indicators allow research into long-term development of worldwide economic growth and inequality.
Global inequality is one of the key problems of the contemporary world. Some countries have (recently) become wealthy, other countries have remained poor. New theoretical developments in economics - such as new institutional economics, new economic geography, and new growth theory - and the rise of global economic and social history require such processes to be studied on a worldwide scale. Clio Infra provides datasets for the most important indicators. Economic and social historians from around the world have been working together in thematic collaboratories, in order to collect and share their knowledge concerning the relevant indicators of economic performance and its causes. The collected data have been standardized, harmonized, and stored for future use. New indicators to study inequality have been developed. The datasets are accessible through the Clio Infra portal which also offers possibilities for visualization of the data. Clio Infra offers the opportunity to greatly enhance our understanding of the origins, causes and character of the process of global inequality.
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