Abstract

Following Sen (1992), the ratio of girls to boys is used to assess discrimination against women in the area of health. There should be a fixed rate of male to female births in humans (about 5 % more boys than girls). In some countries and regions, however, there are much more boys then girls, which is often blamed on sex-selective abortion, infanticide, and neglect in health and nutrition. We focus on the age category 0–5 for two reasons. The first is that the three-fifth of missing women go missing in the birth–childhood period. Secondly, the phenomenon of missing girls at birth reflects discrimination in the household, resulting from the combination of strong preferences for sons combined with declining fertility and the spread of technologies allowing parents to know the sex of the child before birth. Missing girls/women at later stages of the life cycle reflect not only discriminatory practices against women, but also issues of general development, such as lack of healthcare, or infrastructure in terms of water and sanitation (World Bank, 2011)

Author(s)

Sarah Carmichael, Selin Dilli and Auke Rijpma, Utrecht University

Production date

20 August 2014

Variable(s)

Sex ratio

Keywords

Gender equality, demograpy

Time period

1900–2009

Geographical coverage

Worldwide, selected countries

Methodologies used for data collection and processing

Population distribution by gender from published census material were used to reconstruct the ratio of girls to boys aged 0–5 in each country. Decadal averages for each country were taken

Period of collection

See references

Data collectors

Auke Rijpma


Good after 1950 (based on official UN WPP 2013 statistics), before 1950 official government census data from Mitchell (2007) were used, but misreporting might be an issue in the original censuses for countries outside Europe and its offshoots

General references

United Nations, Department of Economic and Social Affairs, Population

Division (2013), World Population Prospects: The 2012 Revision, Key

Findings and Advance Tables,

http://esa.un.org/wpp/Excel-Data/population.htm.

Mitchell, B. R. (2007), International Historical Statistics, 6th ed.

Palgrave Macmillan, Basingstoke, Hampshire, [etc.].

Caribbean

Anguilla[No Data]

Antigua and Barbuda1500 (5)-2013 (21)

Aruba[No Data]

Bahamas1500 (5)-2013 (23)

Barbados1500 (5)-2013 (27)

Bonaire, Sint Eustatius and Saba[No Data]

British Virgin Islands[No Data]

Cayman Islands[No Data]

Cuba1500 (8)-2012 (34)

Curaçao[No Data]

Dominica1500 (5)-2013 (20)

Dominican Republic1500 (6)-2013 (40)

Grenada1500 (5)-2013 (21)

Guadeloupe[No Data]

Haiti1500 (6)-2013 (36)

Jamaica1500 (6)-2013 (38)

Martinique[No Data]

Montserrat[No Data]

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.