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UNESCO defined theGender Parity Index (GPI) as asocioeconomic index usually designed to measure the relative access toeducation of males and females. It is used by international organizations particularly in measuring the progress ofdeveloping countries. For example, someUNESCO documents consider gender parity inliteracy.[1]
UNESCO describes attempts to eliminate gender disparities in primary and secondary education and emphasize on the plight of girls in unequal access in third world countries.[2]
GPI is often used in order to identify nations and regions that are in need ofeconomic development andequality.[3]
TheWorld Economic Forum'sGlobal Gender Gap Report 2022 allows users to look at and compare country GPI data, calculate their own country's gender parity and explore global patterns.[3]
World GPI has consistently increased toward parity since 1980.[4]
The Institute for Statistics ofUNESCO also uses a more general definition of GPI: for any development indicator one can define the GPIrelative to this indicator by dividing its value for females by its value for males.[2]
In its simplest form, GPI is calculated as the quotient of the number of females by the number of males enrolled in a given stage of education (primary,secondary, etc.).
A GPI value that is less than one is an indication that gender parity favor males while a GPI value greater than one designates that gender parity is in favor of females.[5] The closer a GPI is to one, the closer a country is to achieving equality of access between males and females.[6] A nation is said to have achieved gender parity when its GPI value falls within the range of 0.97 and 1.03.[7]
The utilization of Gender Parity Index (GPI) by economists enables comprehensive monitoring and assessment of a nation's economic progress from a gender equality perspective.[3] It is believed by many economists that gender inequality results in economic consequences such as increased unemployment, decreased output, and vast income inequality.[8] As such, the monitoring of GPI by international organizations, such asUNESCO and theWorld Bank, serves the purpose of discerning the economic development deficiencies in nations and regions that are caused by gender inequality.
There is a present link between low-income countries a low GPI, particularly insecondary education andtertiary education.[9] For example, many low-income, sub-Saharan countries have large gaps between male and female access to education.[9]
Household income level is also a determining factor in secondary and tertiary GPI.[9] Inunderdeveloped countries such asCameroon,Guinea,Pakistan, andYemen, gender parity existed among the top 20% of earners; yet low GPI levels were present among the bottom 20% of earners.[9] As such, policymakers and other stakeholders utilize GPI in order to target regions in which economic development is a primary cause of gender disparity.
In theeducation space, GPI is used to measure gender equality in education access.[2] Governments and international organizations such asUNESCO and theUnited Nations monitor the gender gap in education access, using GPI to identify sectors where intervention is needed to address gender disparities.[2]
A low GPI at theprimary education level is an indication of economic, cultural, or other structural barriers that prevent women from receiving education, and a low GPI at thetertiary education level is an indication of structural barriers preventing women from breaking into specialized, advanced career fields.[9]
GPI is also used to measure literacy equality, particularly byUNESCO.[2] Gender disparities, specifically inprimary education, have a drastic effect on literacy rates. For example, a low primary GPI is an indication that women in a particular nation or region are restricted from acquiring basic literacy skills.[10]
| Year | World GPI |
| 1970 | 0.8 |
| 1971 | 0.8 |
| 1972 | 0.8 |
| 1973 | 0.8 |
| 1974 | 0.8 |
| 1975 | 0.82 |
| 1976 | 0.84 |
| 1978 | 0.85 |
| 1979 | 0.84 |
| 1980 | 0.85 |
| 1981 | 0.85 |
| 1982 | 0.85 |
| 1983 | 0.84 |
| 1984 | 0.85 |
| 1985 | 0.85 |
| 1986 | 0.87 |
| 1987 | 0.87 |
| 1988 | 0.87 |
| 1989 | 0.88 |
| 1990 | 0.88 |
| 1991 | 0.89 |
| 1992 | 0.9 |
| 1993 | 0.9 |
| 1994 | 0.91 |
| 1995 | 0.91 |
| 1996 | 0.91 |
| 1997 | 0.92 |
| 1998 | 0.92 |
| 1999 | 0.92 |
| 2000 | 0.92 |
| 2001 | 0.93 |
| 2002 | 0.93 |
| 2003 | 0.95 |
| 2004 | 0.95 |
| 2005 | 0.95 |
| 2006 | 0.96 |
| 2007 | 0.96 |
| 2008 | 0.97 |
| 2009 | 0.97 |
| 2010 | 0.97 |
| 2011 | 0.98 |
| 2012 | 0.98 |
| 2013 | 1 |
| 2014 | 1 |
| 2015 | 1 |
| 2016 | 1.01 |
| 2017 | 1 |
| 2018 | 0.98 |
| 2019 | 0.98 |
| 2020 | 0.98 |
| Country | Most recent year of calculation | Most recent value |
| Afghanistan | 2017 | 0.42 |
| Albania | 2021 | 1.02 |
| Algeria | 2020 | 0.97 |
| Andorra | 1983 | 0.96 |
| Angola | 2018 | 0.94 |
| Antigua and Barbuda | 2019 | 0.98 |
| Argentina | 2020 | 1.01 |
| Armenia | 2021 | 1.01 |
| Austria | 2020 | 0.99 |
| Azerbaijan | 2021 | 1.01 |
| Bahrain | 2019 | 0.99 |
| Bangladesh | 2021 | 1.02 |
| Barbados | 2021 | 0.97 |
| Belarus | 2021 | 1 |
| Belgium | 2020 | 1.01 |
| Belize | 2021 | 0.96 |
| Benin | 2021 | 0.93 |
| Bhutan | 2021 | 1.04 |
| Bolivia | 2020 | 1 |
| Bosnia and Herzegovina | N/A | No Data |
| Botswana | 2021 | 0.98 |
| Brazil | 2020 | 0.95 |
| Brunei | 2020 | 1 |
| Bulgaria | 2020 | 0.99 |
| Burkina Faso | 2021 | 1.02 |
| Burundi | 2020 | 1.01 |
| Cabo Verde | 2019 | 0.94 |
| Cambodia | 2021 | 0.98 |
| Cameroon | 2019 | 0.9 |
| Canada | 2020 | 0.97 |
| Central African Republic | 2017 | 0.77 |
| Chad | 2021 | 0.8 |
| Channel Islands | N/A | No Data |
| Chile | 2020 | 0.97 |
| China | 2021 | 1.01 |
| Colombia | 2020 | 0.97 |
| Comoros | 2018 | 1 |
| Congo | 2018 | 0.97 |
| Costa Rica | 2021 | 0.99 |
| Côte d'Ivoire | 2021 | 0.95 |
| Croatia | 2020 | 1 |
| Cuba | 2021 | 0.98 |
| Cyprus | 2020 | 0.99 |
| Czech Republic | 2020 | 1 |
| Denmark | 2020 | 1 |
| Djibouti | 2021 | 0.92 |
| Dominica | 2021 | 0.95 |
| Dominican Republic | 2021 | 0.97 |
| DR Congo | 2020 | 0.95 |
| Ecuador | 2021 | 1.02 |
| Egypt | 2019 | 1.01 |
| El Salvador | 2014 | 0.96 |
| Equatorial Guinea | 2015 | 0.99 |
| Eritrea | 2019 | 0.86 |
| Estonia | 2020 | 1 |
| Eswatini | 2019 | 0.92 |
| Ethiopia | 2021 | 0.91 |
| Fiji | 2021 | 0.96 |
| Finland | 2020 | 1 |
| France | 2020 | 0.94 |
| French Guiana | No Data | No Data |
| Gabon | 2019 | 0.97 |
| Gambia | 2021 | 1.13 |
| Georgia | 2021 | 1.01 |
| Germany | 2020 | 1.03 |
| Ghana | 2020 | 1.02 |
| Gibraltar | 2021 | 1.12 |
| Greece | 2020 | 1.01 |
| Grenada | 2018 | 0.98 |
| Guatemala | 2021 | 0.98 |
| Guinea | 2020 | 0.85 |
| Guinea-Bissau | 2020 | 0.73 |
| Guyana | 2019 | 0.99 |
| Haiti | 1998 | 0.97 |
| Holy See | No Data | No Data |
| Honduras | 2012 | 1 |
| Hong Kong | 2021 | 1.08 |
| Hungary | 2020 | 0.98 |
| Iceland | 2020 | 1.01 |
| India | 2021 | 1.04 |
| Indonesia | 2018 | 0.99 |
| Iran | 2020 | 1.06 |
| Iraq | 2007 | 0.84 |
| Ireland | 2020 | 1.01 |
| Isle of Man | No Data | No Data |
| Israel | 2020 | |
| Italy | 2020 | 1.01 |
| Jamaica | 2007 | 1 |
| Japan | 2019 | 1.02 |
| Jordan | 2021 | 0.99 |
| Kazakhstan | 2020 | 1 |
| Kenya | 2020 | 1 |
| Kuwait | 2019 | 1.25 |
| Kyrgyzstan | 2021 | 1 |
| Laos | 2021 | 0.97 |
| Latvia | 2020 | 1 |
| Lebanon | 1985 | 0.91 |
| Lesotho | 2019 | 0.95 |
| Liberia | 2020 | 1 |
| Libya | 2006 | 0.96 |
| Liechtenstein | 2020 | 0.97 |
| Lithuania | 2020 | 1 |
| Luxembourg | 2020 | 0.99 |
| Macao | 2021 | 0.98 |
| Madagascar | 2019 | 1.02 |
| Malawi | 2019 | 1.03 |
| Malaysia | 2019 | 1.03 |
| Maldives | 2019 | 1.01 |
| Mali | 2020 | 0.91 |
| Malta | 2020 | 1 |
| Mauritania | 2020 | 1.07 |
| Mauritius | 2021 | 1.02 |
| Mayotte | No data | No data |
| Mexico | 2020 | 1.02 |
| Moldova | 2021 | 0.99 |
| Monaco | No Data | No Data |
| Mongolia | 2021 | 0.98 |
| Montenegro | 2021 | 1 |
| Morocco | 2021 | 0.97 |
| Mozambique | 2020 | 0.94 |
| Myanmar | 2018 | 0.96 |
| Namibia | 2021 | 0.97 |
| Nepal | 2021 | 0.97 |
| Netherlands | 2020 | 1 |
| Nicaragua | 2020 | 0.99 |
| Niger | 2021 | 0.91 |
| Nigeria | 2019 | 1.01 |
| North Korea | 2019 | 1.01 |
| North Macedonia | 2020 | 1 |
| Norway | 2020 | 1 |
| Oman | 2021 | 1 |
| Pakistan | 2019 | 0.88 |
| Panama | 2021 | 0.99 |
| Paraguay | 2015 | 0.97 |
| Peru | 2021 | 0.97 |
| Philippines | 2021 | 0.98 |
| Poland | 2020 | 0.96 |
| Portugal | 2020 | 0.99 |
| Qatar | 2021 | 1.02 |
| Réunion | No Data | No Data |
| Romania | 2020 | 0.99 |
| Russia | 2019 | 0.99 |
| Rwanda | 2021 | 0.99 |
| Saint Helena | No Data | No Data |
| Saint Kitts and Nevis | 2020 | 1 |
| Taiwan | 2021 | 0.90 |