Abstract
Author(s)
Production date
Variable(s)
Keywords
Time period
Geographical coverage
Methodologies used for data collection and processing
Period of collection
Data collectors
Data quality
General references
The wage and price series shown in this chapter are taken from three sources: (A) a variety of studies on historical real wages that appeared in academic journals and books; (B) the British Colonial Blue Books (circa 1840-1912); and (C) the October Enquiries of the International Labour Organisation (1924-2008). These data were then converted into subsistence ratios, which indicate how many times the daily wage of a male unskilled construction labourer can buy the daily subsistence basket. This methodology has the advantage of providing an absolute yardstick to compare welfare across countries and time periods and, hence, is conceptually close (but not identical) to purchasing power parities. Finally, in order to fill gaps in the data, interpolations were made (D) on the basis of real wages indices from the (older) literature.
* To start, for much of the 19th century data we draw on economic histories. Much European data came from Allen's pioneering study (2001) on European wages and prices from the late Middle Ages to the First World War. Data for Istanbul came from the study by Ozmucur and Pamuk (2002), which was based on over 6 000 account books from the soup kitchens of pious foundations and the Topkapı Palace. In addition, we took data for Japan from Bassino and Ma (2005), for several Southeast Asian countries from Van der Eng and Bassino (2013), for India from Allen (2007), for China from Allen et al. (2011), for Argentina, Bolivia, Chile, Colombia, Mexico and Peru from Arroyo Abad et al. (2012), for the United States from Allen et al. (2012), and for Indonesia from De Zwart and Van Zanden (2012). These studies each draw on a variety of sources that are too extensive to discuss here.
* The Colonial Blue Books (1840-1912) contain data that were collected by the colonial administrators in the various colonies of the British Empire and sent each year to the Colonial Office in London, in response to questionnaires sent out by the latter. Frankema and Van Waijenburg (2012) worked with these data for nine British African colonies, with the earliest observation dating from 1870. We extended their series, where possible, to 1850, and added estimates for South Africa (De Zwart, 2011). In addition, we added data from several non-African colonies, especially in Oceania, Latin America and the Caribbean. Data from the Blue Books are not ideal, since price data do not always reflect retail prices (but prices for produce) and wages are not always representative for the majority of the population, but these are currently the only figures available for many of Europe's former colonial possessions.
* Since 1924, the International Labour Organisation (ILO) has conducted an annual survey, called the October Inquiry, to obtain data on wages and prices worldwide. Every year the ILO has sent two questionnaires (one relating to wages and hours of work, the other to retail prices) to national statistical agencies, which were to complete the questionnaires with the information already available to them (and thus not to conduct specific surveys in order to supply the data). Hence, while the price data are roughly consistent, the wage information returned for the various countries could differ significantly; while some reported average wages per hour from an establishment survey, others reported legislated minimum or maximum wage rates for certain occupations, and others returned minimum wage rates based on collective agreements, etc. (see Freeman and Oostendorp, 2001). These wage data thus require some form of standardisation before they can be used. Since 1983, this work has been performed by Freeman and Oostendorp (2001), Harsch and Kleinert (2011), and Oostendorp (2012). In addition, the number of countries included expanded from 15 in 1924 to over 50 in the 1950s, after which the number of countries has fluctuated (after 1983 it contains data on over 130 countries!).
* Real wage series for various countries in the 19th and 20th centuries are also available from other (older) literature (e.g. Mitchell, 2007; Williamson 1998; Scholliers and Zamagni, 1995) as well as from some more recent literature on wages and prices (e.g. Van Leeuwen, 2004; 2007). In addition, in a few cases we included special reports, such as on the period 1950-1970 in China for which little data is available (e.g. Survey on cities and counties in Guangxi, 1985; Yulin City Gazetteer, 1993). The lack of standardisation in the methodology makes direct comparisons on the basis of these data impossible. However, in order to deal with gaps in the data, those real wage series are used for interpolation in a few cases.
Cattle per Capita 1500 [7456] 2010
Cropland per Capita 1500 [6226] 2010
Goats per Capita 1500 [7037] 2010
Pasture per Capita 1500 [5963] 2010
Pigs per Capita 1500 [6841] 2010
Sheep per Capita 1500 [6835] 2010
Total Cropland 1500 [6191] 2010
Total Number of Goats 1500 [7037] 2010
Total Number of Pigs 1500 [6841] 2010
Total Number of Sheep 1500 [6835] 2010
Total Pasture 1500 [5928] 2010
DemographyComposite Measure
of Wellbeing 1820 [3667] 2000
Female life Expectancy at Birth 1750 [1058] 2000
Global Extreme Poverty (CBN) 1820 [26069] 2018
Global Extreme Poverty (DAD) 1820 [26069] 2018
Global Hunger 1820 [27263] 2018
Infant Mortality 1810 [641] 2000
Life Expectancy at Birth (Total) 1543 [12863] 2012
Male life Expectancy at Birth 1750 [1058] 2000
Total Population 1500 [3221] 2000
Total Urban Population 1500 [1722] 2000
Urbanization Ratio 1500 [1051] 2000
EnvironmentBiodiversity - naturalness 1500 [6120] 2010
CO2 Emissions per Capita 1750 [1724] 2010
SO2 Emissions per Capita 1850 [2079] 2000
Total CO2 Emissions 1750 [16446] 2008
Total SO2 Emissions 1850 [2079] 2000
FinanceExchange Rates to UK Pound 1500 [15572] 2013
Exchange Rates to US Dollar 1500 [11765] 2013
Gold Standard 1800 [14359] 2010
Long-Term Government
Bond Yield 1727 [2849] 2011
Total Gross Central Government
Debt as a Percentage of GDP 1692 [7134] 2010
Gender Equality of Numeracy 1810 [1064] 1960
Gender Equality Years
of Education 1950 [140] 2000
Gender-equal Inheritance 1920 [78] 2000
Historical Gender Equality Index 1950 [6222] 2003
Share of Women in Parliament 1960 [1589] 2010
Human CapitalAverage Years of Education 1820 [1677] 2010
Book Titles per Capita 1500 [8191] 2009
Educational Inequality Gini
Coefficient 1850 [12631] 2010
Numeracy (Total) 1500 [1384] 1970
Universities Founded 1502 [1424] 2013
InstitutionsArmed Conflicts (Internal) 1500 [95198] 2000
Armed Conflicts (International) 1500 [95198] 2000
Competitiveness of Executive
Recruitment (XRCOMP) 1800 [14792] 2012
Competitiveness of Participations
(PARCOMP) 1800 [14792] 2012
Executive Constraints
(XCONST) 1800 [14792] 2012
Homicide Rates 1800 [6618] 2010
Latent Democracy Variable 1850 [7842] 2000
Openness of Executive
Recruitment (XROPEN) 1800 [14792] 2012
Political Competition 1810 [12762] 2000
Political Participation 1810 [12883] 2000
Polity2 Index 1800 [14593] 2012
Regulation of Chief Executive
Recruitment (XRREG) 1800 [14792] 2012
Number of Days Lost in
Labour Disputes 1927 [4531] 2013
Number of Labour Disputes 1927 [4808] 2013
Number of Workers Involved
in Labour Disputes 1927 [4651] 2013
Working week
in manufacturing 1800 [3974] 2008
GDP per Capita 1500 [17675] 2016
Social Spending 1820 [290] 2016
Prices and WagesIncome Inequality 1820 [866] 2000
Labourers Real Wage 1820 [5053] 2008
Wealth Decadal Ginis 1820 [225] 2010
Wealth Top10 percent share 1820 [225] 2010
Wealth Yearly Ginis 1820 [749] 2015
ProductionAluminium Production 1850 [11736] 2012
Bauxite Production 1880 [6384] 2012
Copper Production 1700 [19472] 2012
Gold Production 1681 [35855] 2012
Iron Ore Production 1820 [12738] 2012
Lead Production 1705 [12934] 2012
Manganese Production 1835 [8722] 2012
Nickel Production 1850 [5214] 2012
Silver Production 1681 [26892] 2012
Tin Production 1700 [13772] 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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