The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2024, the country offering most gender equal conditions was Iceland with a score of 0.94. Overall, the Nordic countries make up four of the five most gender equal countries in the world. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the least gender equal country Sudan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country has worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly nine million people are estimated to be at acute risk of famine. The Middle East and North Africa has the largest gender gap Looking at the different world regions, the Middle East and North Africa has the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

The Gender Equality Index benchmarks national gender gaps on economic, political, education, and health-based criteria among the countries of the European Union. A score of 0 indicates that there is no gender equality, while 100 points indicate that gender equality is achieved. In the 2023 index, the leading country was Sweden with a score of 82.2 points. The Netherlands and Denmark were the second and third most gender equal countries. Considering the other side of the spectrum, Romania only scored 56.1 points, way below the EU average of 70.2. Other countries at the bottom of the ranking were Hungary and Czechia. Equality in health Not only does the index measure gender equality on national levels, it also breaks down gender equality into different dimensions. With an index score of 88 points, health was the most equal dimension among men and women within the EU, followed by money and work. To the contrary, power was considered the most unequal dimension, along with knowledge and time management. The Global Gender Gap Index From a global perspective, Iceland is considered the most gender equal country. Dominating this list are the Nordic countries: Norway, Finland, New Zealand, and Sweden rank in the top-5. As of 2023, it was estimated that Europe had closed 76.3 percent of its gender gap, making it the most successful region in the world, before North- and Latin America. Nevertheless, experts predict that gender parity will not be achieved in the region for another 67 years.

This fascinating compilation of the recent data on gender differences in education presents a wealth of data, analysed from a multitude of angles in a clear and lively way. In particular it looks at underperformance among boys, lack of self confidence among girls and family, school and societal influences before addressing policies to help boys and girls reach their full potential.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Abstract

This retrospective report explores global progress and lessons learned over the past 10 years in promoting gender equality. This report takes stock of global progress and considers the impact of evidence-backed solutions to close the most persistent gender gaps. It examines the evolution of World Bank Group’s engagement on gender and highlights promising approaches. Reflections and findings will enable the WBG and its partners to develop a deeper understanding of what works, provide opportunities to strengthen and expand efforts in critical areas, and will inform the new WBG Gender Strategy, to be launched in 2024.

Citation

“World Bank. 2023. Gender Equality in Development: A Ten-Year Retrospective. © Washington, DC: World Bank. http://hdl.handle.net/10986/39939 License: CC BY-NC 3.0 IGO.”

URI

https://openknowledge.worldbank.org/handle/10986/39939

The COVID-19 pandemic has impacts beyond people’s health that affect different aspects of day-to-day life. All people will be impacted in some way and must adapt to the pandemic, however men and women – or different groups of men and women – will not all be affected in the same ways. This is due to women and men play different roles and have different responsibilities in their homes and communities.

Women and girls are disproportionately impacted by crises. Women and girls are likely to: face even higher rates of domestic violence and sexual abuse; are more vulnerable to economic hardship as income generation activities women perform are disrupted; have increased unpaid in the household due to the closure of schools and have reduced access to essential health services. It is important to keep track of how all the different segments of the population are being affected by the COVID-19 pandemic and how mitigation measures are affecting people’s lives. This set of indicators has been developed to assist with that purpose.

COVID-19 response strategies that are gender responsive and socially inclusive to address the needs of women, youth, people with disabilities and other segments of the population who are more vulnerable.

The list of indicators is not mandatory nor exhaustive but, hopefully, helpful for people needing to track COVID-19 responses and impacts. The indicators cover seven areas: 1. Health impacts of the COVID-19 pandemic. 2. Participation of women, youth, and people with disability in decision making. 3. Sexual and reproductive health. 4. Domestic violence. 5. Economic security. 6. Food security. 7. Unpaid care work.

Achieve gender equality and empower all women and girls : The region has made progress in achieving gender equality and empowering women and girls, particularly in education and health and to a lesser extent women’s participation in formal employment and national policy making. This is attributed to growing awareness of the need to address gender inequalities; While almost all countries in the Pacific have adopted specific gender policies and strategies, the resources for integrating and implementing these priorities are limited. Budgets for national women’s offices are less than one percent of national appropriations; Gender inequality is highlighted by the high prevalence rates of violence against women (more than 60 percent in Melanesia, and more than 40 percent in Polynesia and Micronesia). Sexual and reproductive health and rights issues also remain substantial challenges to be addressed under Goal 5. Fertility rates, especially teenage fertility, remain high in some.

Find more Pacific data on PDH.stat.

Download of Gender statistics CSV file from World Bank, as of September 25th 2019.

According to a recent survey, 55 percent of the male respondents believed that their respective countries have gone far enough in terms of giving women equal rights with men. This statement was only supported by 42 percent of the female respondents. However, female respondents found to a greater extent than male respondents that workplaces treat men and women equally.

The OECD Gender Data Portal, www.oecd.org/gender/data, includes 40+ selected indicators shedding light on gender inequalities in education, employment and entrepreneurship. Data and metadata for all the indicators are easily and freely accessible and displayed through interactive visualizations. The Gender Data Portal is one of the main outputs of the OECD Gender Initiative, launched in 2010 to improve policies and promote gender equality in the economy in both OECD and non-OECD countries. The Portal is part of the new OECD Gender Equality website www.oecd.org/gender, which also features Closing the Gender Gap: Act Now, a publication that presents new analysis of the productivity losses caused by gender inequality and proposes policy solutions to close the gender gaps. While much progress has been accomplished in recent years, there are still relevant dimensions of gender inequalities that are poorly monitored and measured. The OECD Gender Portal is thus a work in progress, that aims at progressively filling these gaps through new indicators. The last data release, for Women's Day 2013, includes new gender-sensitive indicators of job quality, timely indicators of labor market participation, indicators on top and low-achieving students in different subjects and on entrepreneurial culture. The data cover OECD member countries, as well as Russia, Brazil, China, India, Indonesia, and South Africa.

Introduction

This study reproduces the results of the article Relationship of gender differences in preferences to economic development and gender equality (DOI: 10.1126/science.aas9899) and partially its supplementary material.

The code for the analysis can be found at the following GitHub page: https://github.com/scerioli/Global-Preferences-Survey

Preparation of the data

Data Collection, Cleaning, and Standardization

The data used in the Falk & Hermle 2018 is not fully available because of two reasons:

1. Data paywall: Some part of the data is not available for free. It requires to pay a fee to the Gallup to access them. This is the case for the additional data set that is used in the article, for instance, the one that contains the education level and the household income quintile. Check the website of the briq - Institute on Behavior & Inequality for more information on it.

2. Data used in study is not available online: This is what happened for the LogGDP p/c calculated in 2005 US dollars (which is not directly available online). We decided to calculate the LogGDP p/c in 2010 US dollars because it was easily available, which should not change the main findings of the article.

Global Preferences Survey

This data is protected by copyright and cannot be given to third parties.

To download the GPS data set, go to the website of the Global Preferences Survey in the section "downloads". There, choose the "Dataset" form and after filling it, we can download the data set.

Hint: The organisation can be also "private".

The following two relevant papers have to be also cited in all publications that make use of or refer in any kind to GPS dataset:

• Falk, A., Becker, A., Dohmen, T., Enke, B., Huffman, D., & Sunde, U. (2018). Global evidence on economic preferences. Quarterly Journal of Economics, 133 (4), 1645–1692.

• Falk, A., Becker, A., Dohmen, T. J., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences. IZA Discussion Paper No. 9674.

GDP per capita

From the website of the World Bank, one can access the data about the GDP per capita on a certain set of years. We took the GDP per capita (constant 2010 US$), made an average of the data from 2003 until 2012 for all the available countries, and matched the names of the countries with the ones from the GPS data set.

Gender Equality Index

The Gender Equality Index is composed of four main data sets.

• Time since women’s suffrage: Taken from the Inter-Parliamentary Union Website. We prepared the data in the following way. For several countries more than one date where provided (for example, the right to be elected and the right to vote). We use the last date when both vote and stand for election right were granted, with no other restrictions commented. Some counties were a colony or within union of the countries (for instance, Kazakhstan in Soviet Union). For these countries, the rights to vote and be elected might be technically granted two times within union and as independent state. In this case we kept the first date. It was difficult to decide on South Africa because its history shows the racism part very entangled with women's rights. We kept the latest date when also Black women could vote. For Nigeria, considered the distinctions between North and South, we decided to keep only the North data because, again, it was showing the completeness of the country and it was the last date. Note: USA data doesn't take into account that also up to 1964 black women couldn't vote (in general, Blacks couldn't vote up to that year). We didn’t keep this date, because it was not explicitly mentioned in the original data set. This is in contrast with other choices made, but it is important to reproduce exactly the results of the publication, and the USA is often easy to spot on the plots.

• UN Gender Inequality Index: Taken from the Human Development Report 2015. We kept only the table called "Gender Inequality Index".

• WEF Global Gender Gap: WEF Global Gender Gap Index Taken from the World Economic Forum Global Gender Gap Report 2015. For countries where data were missing, data was added from the World Economic Forum Global Gender Gap Report 2006. We modified some of the country names directly in the csv file, that is why we provide it as an input file.

• Ratio of female and male labour force participation: Average International Labour Organization estimates from 2003 to 2012 taken from the World Bank database (http://data.worldbank.org/indicator/SL.TLF.CACT.FM.ZS). Values were inverted to create an index of equality. We took the average for the period between 2004 and 2013.

In our extended analysis, we also involved the following index:

• United Nations Development Programme Gender Development Index taken from Human Development Reports 2020. Note that we have downloaded the two tables of the Human Development Index for males and females, and used the ratio of the two as a GDI index, as described in the report.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

For the second consecutive year, Mexico scored 0.77 in the gender gap index in 2023. This shows a gender gap of approximately 23 percent (women are 23 percent less likely to have equal opportunities than men). Since 2017, Mexico's score has been overall continuously increasing, which shows an improvement towards gender equality. That same year, the gender gap in the area of political empowerment in Mexico amounted to 51 percent.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Under the Workplace Gender Equality Act 2012, non-public sector employers with 100 or more staff must report to the WGEA annually, which covers over 12,000 Australian organisations. Information collected and contained in the data files are the gender composition of the workforce and governing bodies/boards, percentage of organisations with policy and/or strategies across a broad range of gender equality issues, paid parental leave and flexible work arrangement offerings.

Visit Data Explorer (https://data.wgea.gov.au/) for key trends and data visualisations

Visit Metadata registry (https://wgea.aristotlecloud.io/about/wgea/gender_equality_indicators) for further information about how we use the data to measure gender equality.

The Data Quality Declaration (https://www.wgea.gov.au/data/data-quality-declaration) addresses the overall quality of the Agency data in terms of relevance, timeliness, accuracy, coherence, interpretability, accessibility, and the institutional environment.

Tuvalu TV: CPIA: Gender Equality Rating: 1=Low To 6=High data was reported at 3.000 NA in 2017. This stayed constant from the previous number of 3.000 NA for 2016. Tuvalu TV: CPIA: Gender Equality Rating: 1=Low To 6=High data is updated yearly, averaging 3.000 NA from Dec 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 3.000 NA in 2017 and a record low of 3.000 NA in 2017. Tuvalu TV: CPIA: Gender Equality Rating: 1=Low To 6=High data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tuvalu – Table TV.World Bank: Policy and Institutions. Gender equality assesses the extent to which the country has installed institutions and programs to enforce laws and policies that promote equal access for men and women in education, health, the economy, and protection under law.; ; World Bank Group, CPIA database (http://www.worldbank.org/ida).; Unweighted average;

The survey focused on attitudes, opinions and experiences related to gender equality in different spheres of life in Finland. The main focus was on equality in working life, education and family life. Questions investigated opinions on the general status of men and women in Finland, estimates for gender equality development in the following 10 years, whether the respondents thought there should be more men or women in certain positions or occupational fields (e.g. in positions of power, in social and health services, ICT), and whether women's possibilities were equal to men's in occupational life. Attitudes were charted on gender roles in the family in terms of money matters and domestic responsibilities, gender roles in politics and in decision-making in different spheres of politics, and ways to reduce unjustified wage differences. Full-time students were asked about their gender-related experiences in study, for example, whether there was gender stereotyping in study materials or in the educational institution, whether a clear majority of students in their field consisted of men or women, did gender affect student treatment or grades, strictness of gender roles/norms in the institution, support for choosing a study field where the respondent's gender was a minority, and whether sexual minorities and rainbow families were taken into account in teaching or teaching material. Other questions investigated occurrences of sexual harassment and hate speech, kinds of harassment, the perpetrators and the context. The respondents were also asked whether there were people who depreciated or belittled their speech or suggestions on account of their gender and who. A number of questions investigated whether gender affected the wage level, fringe benefits, work loads, career advancement, job contracts, autonomy at work etc. in the workplace and whether gender was a hindrance in entrepreneurship and in what kind of situations. Further topics included attitudes in the workplace relating to absences of men and women due to family matters or paternal leaves, division of caring and other household tasks in R's family and who paid what in the household. Background variables included the respondent's age group, gender, region of residence (NUTS3), highest education attained, status in employment, economic activity, occupational status, number of employees R supervised, type of employment contract, average weekly working hours, whether R belonged to a minority group, type of minority group, living arrangements, marital status, gender of the spouse, spouse's economic activity, number and ages of children aged under 18 in the household, how often R met his or her children who lived elsewhere. For students, type of educational institution.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Gender equality is a core development objective in its own right. It is also smart development policy and sound business practice. It is integral to economic growth, business growth and good development outcomes. Gender equality can boost productivity, enhance prospects for the next generation, build resilience, and make institutions more representative and effective. In December 2015, the World Bank Group Board discussed our new Gender Equality Strategy 2016-2023, which aims to address persistent gaps and proposed a sharpened focus on more and better gender data. The Bank Group is continually scaling up commitments and expanding partnerships to fill significant gaps in gender data. The database hosts the latest sex-disaggregated data and gender statistics covering demography, education, health, access to economic opportunities, public life and decision-making, and agency.

Abstract

Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. This survey covers topics about gender dynamics and norms, unpaid caregiving, and life during the COVID-19 pandemic. Aggregated data is available publicly on Humanitarian Data Exchange (HDX). De-identified microdata is also available to eligible nonprofits and universities through Facebook’s Data for Good (DFG) program. For more information, please email dataforgood@fb.com.

Geographic coverage

This survey is fielded once a year in over 200 countries and 60 languages. The data can help researchers track trends in gender equality and progress on the Sustainable Development Goals.

Analysis unit

• Public Aggregate Data on HDX: country or regional levels
• De-identified Microdata through Facebook Data for Good program: Individual level

Universe

The survey was fielded to active Facebook users.

Kind of data

Sample survey data [ssd]

Sampling procedure

Respondents were sampled across seven regions: - East Asia and Pacific; Europe and Central Asia - Latin America and Caribbean - Middle East and North Africa - North America - Sub-Saharan Africa - South Asia

For the purposes of this report, responses have been aggregated up to the regional level; these regional estimates form the basis of this report and its associated products (Regional Briefs). In order to ensure respondent confidentiality, these estimates are based on responses where a sufficient number of people responded to each question and thus where confidentiality can be assured. This results in a sample of 461,748 respondents.

The sampling frame for this survey is the global database of Facebook users who were active on the platform at least once over the past 28 days, which offers a number of advantages: It allows for the design, implementation, and launch of a survey in a timely manner. Large sample sizes allow for more questions to be asked through random assignment of modules, avoiding respondent fatigue. Samples may be drawn from diverse segments of the online population. Knowledge of the overall sampling frame allowed for more rigorous probabilistic sampling techniques and non-response adjustments than is typical for online and phone surveys

Mode of data collection

Internet [int]

Research instrument

The survey includes a total of 75 questions, split across into the following sections: - Basic demographics and gender norms - Decision making and resource allocation across household members - Unpaid caregiving - Additional household demographics and COVID-19 impact - Optional questions for special groups (e.g. students, business owners, the employed, and the unemployed)

Questions were developed collaboratively by a team of economists and gender experts from the World Bank, UN Women, Equal Measures 2030, and Ladysmith. Some of the questions have been borrowed from other surveys that employ alternative modes of administration (e.g., face-to-face, telephone surveys, etc.); this allows for comparability and identification of potential gaps and biases inherent to Facebook and other online survey platforms. As such, the survey also generates methodological insights that are useful to researchers undertaking alternative modes of data collection during the COVID-19 era.

In order to avoid “survey fatigue,” wherein respondents begin to disengage from the survey content and responses become less reliable, each respondent was only asked to answer a subset of questions. Specifically, each respondent saw a maximum of 30 questions, comprising demographics (asked of all respondents) and a set of additional questions randomly and purposely allocated to them.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Other factors beyond sampling error that contribute to such potential differences are frame or coverage error and nonresponse error.

Data appraisal

Survey Limitations The survey only captures respondents who: (1) have access to the Internet (2) are Facebook users (3) opt to take this survey through the Facebook platform. Knowledge of the overall demographics of the online population in each region allows for calibration such that estimates are representative at this level. However, this means the results only tell us something about the online population in each region, not the overall population. As such, the survey cannot generate global estimates or meaningful comparisons across countries and regions, given the heterogeneity in internet connectivity across countries. Estimates have only been generated for respondents who gave their gender as male or female. The survey included an “other” option but very few respondents selected it, making it impossible to generate meaningful estimates for non-binary populations. It is important to note that the survey was not designed to paint a comprehensive picture of household dynamics but rather to shed light on respondents’ reported experiences and roles within households