The Female Opportunity Index 2021

An analysis of gender equality in 100 countries, and 10 French cities, looking at advancements in female leadership within government, corporations, STEM and entrepreneurship, as well as success enablers like access to education and parental leave.
Woman looking in the camera, smiling.
While there is no denying how difficult the last year has been for everyone, the pandemic has shone a light on many existing inequalities—not least between men and women in the workplace and beyond. Early estimates suggest that globally, women are more likely to have lost their job due to COVID-19 as compared to men, and have taken on the majority of childcare and education at home while schools were closed. Added to this is the fact that 70% of health workers around the world are female.
Woman with glasses working from home with a laptop.

Despite these enormous challenges, we’ve also seen amazing female heads of government leading the world in the way they’ve managed the pandemic, as well as incredible women who continue to take the lead towards gender equality while determining their future both personally and professionally. At N26 this is something we are passionate about. We firmly believe that we all need to work together to level the playing field. That's why we're on a journey to understand where we can champion change and make a difference. To explore this further we decided to commission a study looking into workplace achievements, and the factors that drive female independence. While there is still much work to be done, the results celebrate the French cities and global countries that encourage female opportunity and where women are thriving in governmental leadership, management, entrepreneurship and more.

The science part

The index began by selecting 100 countries around the world, across all continents, with comparable data on women in the workplace. To establish the level of gender parity from the very top, we first investigated how many years a country has been governed by a woman since 1970, as well as the total number of women in governmental or parliamentary positions. Next, we looked at women in managerial positions, as well as data around female entrepreneurs in each country, to determine which nations help to foster the strongest female leadership opportunities and achievements. Our research then turned to the number of women in the typically male-dominated STEM fields—science, technology, engineering, and mathematics. We focused not only on those actively studying, but also on the percentage of women actually working in that field after graduation. Next, we explored the average salary and the gender wage gap in each country. The data was complemented by investigating female access to education as an important indicator and enabler of opportunity, as well as legislation such as a woman’s right to divorce, workplace discrimination laws and more. As a country’s attitude towards starting a family and how that interacts with work is a clear expression of gender parity, we included the total days of maternity leave allowed in each country. To gain a deeper understanding of the situation on a local level, we decided to also conduct a focused study for 10 major French cities, looking at the career achievements of women in senior government, executive and managerial positions. This included the presence of female leadership in local municipalities, top corporations, and editorial boards of local newspapers, as well as the number of companies which have at least one female founder. The total score takes into consideration all of these data points to determine which French cities and global countries are most successfully leveling the playing field, and which still have some way to go to improve women’s access to equal opportunities.
“At N26 we firmly believe that everyone, regardless gender, should have the opportunity and freedom to live the lives they chose. And yes, there’s much more to life than money, but we think it’s a good place to start. When we feel in control of our finances, we feel more confident, more independent and more optimistic about our future, helping us to reach our full potential,”
says Adrienne Gormley, Chief Operating Officer at N26.
“We want to understand what can hold women back when it comes to being financially confident, to understand the drivers behind financial independence, and see how we can help to make a difference.”

Instructions for journalists

The final rankings below display the 10 French cities and 100 global countries in order from highest score to lowest. Each individual column is filterable, and the full methodology explaining how each factor was evaluated is at the bottom of the page.

Local city results

Local legends.

Female Opportunity Index: City Rankings in France

1Strasbourg175146.3360100
2Montpellier104882.8192582.86
3Paris64972.5111780.33
4Nice05454.6175074.36
5Toulouse04960.594072.11
6Lille195327.110071.51
7Marseille15260.27066.12
8Nantes63135.751756.88
9Bordeaux04528.612056.3
10Lyon04828.65050

Top countries in the ranking for female opportunity

1. Norway

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2. Finland

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3. Iceland

🇮🇸

14. France

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International results

Female opportunity index legends.

Female Opportunity Index: Global Country Rankings

1Norway1796.149998.9492.39896.293.3637100
2Finland298.919998.7591.894.795.496.91,12799.25
3Iceland795.1799.999.2992.895.795.110018295.19
4UK1592.7898.698.8892.991.896.993.227395.09
5Germany1593.8790.398.679194.9929540694.27
6New Zealand1494.169799.9492.792.296.394.912694.2
7Denmark594.1996.699.0391.89594.893.835093.38
8Latvia290.3697.598.4294.493.194.892.365892.77
9Estonia087.7296.999.0694.190.493.9911,16290.32
10Slovakia289.0884.597.8993.691.985.989.51,14890.25
11Switzerland896.1592.498.4190.79691.886.79890.08
12Canada095.019997.4894.994.399.592.535789.93
13Sweden098.3410098.9793.195.897.196.139089.71
14France197.119798.189193.793.894.629489.64
15Poland588.5789.599.1894.491.693.290.136489.23
16Australia391.2797.699.4993.69394.189.512689.2
17Slovenia289.8394.696.9795.394.995.488.836588.9
18Serbia391.7796.794.7694.890.890.586.236588.43
19Belgium193.397.298.289193.794.391.422688.08
20Argentina1092.9488.296.4497.487.390.7939088.03
21Austria197.5995.498.3691.79289.292.142087.93
22Lithuania183.4795.899.3195.194.398.384.643487.75
23Romania286.1694.597.6495.192.681.884.276187.36
24Portugal195.898.798.7294.493.489.290.621186.74
25Croatia289.9786.995.7194.291.687.489.639285.87
26South Korea489.684.797.3797.889.594.688.49085.44
27Spain099.2398.998.2292.39390.996.211285.42
28Chile890.618888.8683.589.288.786.821084.98
29Bulgaria092.3489.595.2292.890.986.38577384.75
30Israel587.9885.295.5194.791.198.875.910584.55
31Hungary079.9688.297.2192.991.188.785.81,12084.47
32Czechia089.591.396.6192.292.199.584.244383.87
33Ireland089.0390.898.9193.694.595.495.318283.74
34Ukraine390.588896.6391.48888.388.212683.73
35Italy093.6896.796.0993.29189.990.333483.66
36Costa Rica497.6590.591.3491.288.185.68112183.42
37Netherlands094.9695.99889.894.394.786.211283.24
38Brazil677.9195.194.3791.988.48387.412082.9
39Moldova285.1290.596.6892.290.683.790.312682.57
40Panama590.2289.895.2792.191.678.882.69882.54
41Philippines1685.6391.290.2191.989.182.674.66082.31
42Singapore088.6493.299.511001009575.511281.66
43Bolivia195.6487.897.0395.787.182.792.49081.57
44Macedonia092.1990.697.59488.484.789.927081.31
45Jamaica690.0592.393.8595.388.477.977.65681.16
46Montenegro087.718995.3994.591.2918836580.99
47Cuba095.2392.994.9791.886.691.888.712680.49
48USA086.7195.110092.494.594.281.2080.34
49Colombia094.2392.198.6492.190.582.491.512680.07
50Mozambique696.387.292.8890.389.161.492.56080.01
51Albania095.5788.993.5692.59087.681.636579.8
52Japan078.5485.495.2595.291.210081.140679.66
53Uruguay090.2493.893.193.790.387.290.59879.45
54Greece083.649294.2692.991.991.479.230179.36
55Russia081.190.299.2898.290.292.786.514079.14
56Peru095.2396.598.2392.890.385.476.79878.95
57Georgia091.0185.795.9189.385.395.976.735878.5
58Malta078.7693.796.9792.389.892.984.112678.27
59Ecuador095.189.693.4589.890.784.585.88477.88
60Rwanda110093.794.5790.886.268.383.78477.83
61South Africa097.5687.293.682.988.881.99112077.67
62El Salvador095.3694.895.19087.670.490.211276.56
63Kazakhstan083.8782.895.8495.990.593.780.612676.42
64Turkey381.5182.290.6691.185.679.682.711276.27
65Indonesia384.2973.692.8692.486.180.783.89076.05
66Thailand370.258399.1188.593.278.675.29075.81
67Venezuela088.0691.189.1291.889.887.775.418275.7
68Namibia092.0287.693.5494.191.980.481.58475.68
69Mexico096.1991.294.4590.98682.477.28475.65
70Armenia082.8784.995.3190.98688.582.614074.78
71Paraguay087.689594.191.687.876.778.312674.59
72Vietnam081.3581.395.5492.891.977.382.718273
73India1679.9173.689.5890.964.575.77818272.16
74Azerbaijan075.7577.995.4793.28787.281.412671.76
75China083.3979.598.1389.189.575.881.112871.73
76Botswana082.1589.492.7573.592.180.170.68471.37
77Laos086.2988.294.7690.494.662.576.69070.69
78UAE093.8380.695.7691.882.685.764.34570.65
79Sri Lanka295071.389.9890.982.291.256.38470.41
80Kenya088.6483.892.890.18968.579.49070.4
81Cambodia081.9585.994.388.690.570.675.59069.99
82Tanzania091.8589.888.491.89062.276.88469.92
83Uganda093.5185.274.5489.3857978.18469.52
84Malaysia083.2584.294.159291.288506069.22
85Qatar069.9279.796.3387.894.388.261.25068.7
86Bahrain074.2879.694.4789.78588.568.26068.59
87Ethiopia096.3381.987.5586.486.256.982.89067.74
88Ghana084.9989.994.3787.676.172.567.38467.29
89Cameroon089.5686.473.5590.582.96977.69866.38
90Tunisia083.537792.8694.974.572.475.63064.93
91Morocco084.947690.2779.670.176.573.39863.92
92Nepal088.0478.491.7692.787.767.152.75263.51
93Saudi Arabia075.8174.189.785080.888.3567062.13
94Oman057.0378.992.5288.275.38955.95060.87
95Iran053.6172.494.1787.965.886.260.827259.05
96Algeria086.9166.185.594.458.976.3709858.95
97Nigeria060.3482.586.5393.490.15057.18456.47
98Jordan081.327090.86826375.850.37056.34
99Egypt085.5867.35079.574.172.9639053.28
100Pakistan583.255079.9786.85051.455.68450

Methodology

The Female Opportunity Index 2021 analyzes and compares 100 countries for their achievements in female leadership, management and entrepreneurship, as well as their advancements in female access to education and parental leave. The countries were selected due to their availability of comparable data on women in the workplace, as well as their inclusion in the World Economic Forum Global Gender Gap Report 2020. The study is divided into two sections: a global country ranking analysing the above, and a local deep dive looking into the career achievements of women in senior government, managerial and editorial positions in 10 major French cities. The final index determines the global countries, and local cities, which have shown the greatest advancements in terms of equality and support for female achievement, as well as those which have much to improve.

Factors and Scoring

The global country index is comprised of four categories containing nine factors outlined below which measure female achievement, equality and support in a country: Political Leadership:
  • Female Head of Government (Years, 1970 - 2020)
  • Total Women in Government (Score)
Careers:
  • Women in Management (Score)
  • Women in Entrepreneurship (Score)
  • Women in STEM (Score)
Pay Equality:
  • Salary Level and Gender Wage Gap (Score)
Support:
  • Female Access to Education (Score)
  • Women's Legislation (Score)
  • Maternal Leave (Days)
The city index is comprised of 5 factors outlined below which measure female career achievement in a city:
  • Years Under Female Mayorship (1970-2020)
  • Female Share in Current Local Government (%)
  • Women in Corporate Leadership (Score)
  • Female Founders (%)
  • Newspaper Editorial Boards
Each factor consists of one or more indicators which were scored and averaged. The equation for scoring is as follows: z-Score = x - mean(X)Standard deviation(X)in short x - μσ For columns where a low value is better, the score is inverted such that a high score is always better: z-Score inverted = -1*x - mean(X)Standard deviation(X) in short -1 *x - μσ Data is normalised to a [50-100] scale, with 100 being the best score. Therefore, the higher the score, the better the city/country ranks for that factor in comparison to the other cities in the index. The formula used is min-max normalisation: score = (100-50) *x - min(X)max(X) - min(X)+50 The final score was determined by calculating the sum of the weighted average score of all of the indicators. All factors are based on the latest available data.

Global country index factors

Female Head of Government (Years, 1970 - 2020) The total number of years a country had a woman as an elected head of government between the period of 1970 to 2020. Sources: official government pages; Wikipedia. Total Women in Government (Score) The share of women in government positions, calculated into a score. This data column is a combination of the following factors, averaged over a period of 12 months:
  • The percentage of seats held by women in national parliaments as of January 1, 2021.
  • Percentage of women in ministerial positions as of January 1, 2021.
Source: World Bank; UN. Women in Management (Score) The share of women in management positions, as a score. This data column is a combination of the following factors:
  • Share of female employees in managerial positions (International Labour Organisation).
  • Share of women in senior and middle management positions (ILO).
  • The number of active companies founded after 2010 with at least one female founder (Crunchbase).
  • Workplace rights (Law): Whether women and men have the same legal rights and opportunities in the workplace (OECD).
  • Workplace rights (Attitudes): Percentage of the population who disagrees with the statement “It is perfectly acceptable for any woman in your family to have a paid job outside the home if she wants one” (OECD).
Sources: International Labour Organization (ILO); Crunchbase; OECD. Women in Entrepreneurship (Score) The share of women in entrepreneurial positions, as well as how supportive and accessible the entrepreneurial environment of a country is for women. This data column is presented as a score and combines the following factors:
  • Percentage of companies with at least one female founder (Crunchbase).
  • Percentage of companies with female participation in ownership (World Bank).
  • Percentage of companies with greater than 50% female ownership (World Bank).
  • Percentage of female business owners of total business owners according to the Mastercard Index of Women Entrepreneurs 2020 (MIWE).
  • Ease of doing business score (World Bank, 2017-2020 methodology).
  • Secure access to land assets (Law): whether women and men have the same legal rights and secure access to land assets (OECD).
  • Access to non-land assets (Law): whether women and men have the same legal rights and secure access to non-land assets (OECD).
  • Secure access to formal financial services (Law): whether women and men have the same legal rights to open a bank account and obtain credit in a formal financial institution (OECD).
  • Secure access to formal financial services (Practice): percentage of women among the total number of people aged 15 years and above who have an account at a financial institution (single or joint) (OECD).
Sources: World Bank; OECD; Crunchbase; Mastercard Index of Women Entrepreneurs 2020 (MIWE). Women in STEM (Score) The share of women in STEM and related research positions, as a score. This data column is a combination of the following factors:
  • Female researchers as a percentage of total researchers (OECD).
  • Female share of graduates in Engineering, Manufacturing and Construction programmes, tertiary (World Bank).
  • Female share of graduates in Science programs, tertiary (World Bank).
  • Female share of graduates from Science, Technology, Engineering and Mathematics (STEM) programs, tertiary (World Bank).
  • Vocational training attainment (WEF).
  • Mean performance on the mathematics scale for female eighth-grade students (NCES).
  • Female Share of Labour Force (WB).
Sources: World Bank, OECD; World Economic Forum, National Center for Education Statistics. Salary Level and Gender Wage Gap (Score) The estimated salary level and wage gap between genders, as a score. This data column is a combination of the following factors:
  • The ratio between the estimated earned income of women and men (WEF).
  • Estimated female income (WEF).
Sources: World Economic Forum. Female Access to Education (Score) The level of access to education for females in each country, as a score. This data column is a combination of the following factors:
  • Percentage of female enrollment in primary education (UNESCO)
  • Percentage of female enrollment in secondary education (UNESCO)
  • Mean years of schooling (both genders) (HDI)
Sources: UNESCO, UN Human Development Report 2018. Women's Legislation (Score) The degree to which female-positive legislation is present in a country, as a score. This data column is a combination of the following factors:
  • Divorce legality (OECD).
  • Women in Power according to the Political Empowerment Score (WEF).
  • Presence of paternity leave (WORLD Policy Analysis Center).
  • Presence of legislative prohibition of workplace discrimination based on sex (WORLD Policy Analysis Center).
  • Percentage of wages paid in a covered period of maternity leave (UN).
Sources: OECD, UN, WEF; WORLD Policy Analysis Center. Maternity Leave (Days) The total number of days of paid parental leave available to mothers in a country.
  • Data compiled by the OECD and UN nations was used where available.
  • Policies were checked on a per-country basis to confirm that no new policies had been put in place between now and the publication of the OECD and UN datasets.
  • Where policies were found to be out-of-date, the OECD methodology was used to determine the current number of days of paid parent and home care leave.
Sources: OECD, UN.

Local city index factors

Years Under Female Mayorship (1970-2020) The number of years under a female mayorship in a city. The total takes into account all women serving as mayor between January 1970 to July 2020. Sources: local city government pages; Wikipedia. Female Share in Current Local Government (%) The proportion of women among the top tier city council representatives of the local municipal government or equivalent. Includes the members of the mayor’s office and senior members of the city council. Sources: Official city government pages. Women in Corporate Leadership (Score) Reflects the percentage of female executives in top-performing companies in the city. The top companies in each city were identified using the Global Fortune 500 companies list. In smaller cities which did not have companies that were part of Fortune 500, a web search was performed to identify the top companies based on revenue. The number of C-level executives (CEO, CFO, CMO, CCO, COO, etc,) and the members of the management board for each company were then identified to assign a score to a city that reflects the proportion of female C-level management. Sources: Fortune magazine’s ‘Global Fortune 500’ ranking; official company sites. Female Founders (%) Percentage of active companies with at least one female founder which were founded within the last 10 years and have received funding since 2015. Sources: Crunchbase. Newspaper Editorial Boards The percentage of female Chief and Senior Editors in the most popular daily newspapers in each city. Sources: Local newspaper sites. (A list of the newspapers included can be provided upon request.) Update: This first iteration of this dataset was published in November 2019. As new and relevant reports have since been published, this data has been updated to reflect the most up-to-date figures, as of January 2021.


About N26

N26 is building the first mobile bank the world loves to use. Valentin Stalf and Maximilian Tayenthal founded N26 in 2013 and launched the initial product in early 2015. Today N26 has more than 5 million customers in 25 markets. The company employs more than 1.500 employees across 5 office locations: Berlin, New York Barcelona, Vienna and São Paulo. With a full German banking license, state-of-the-art technology and no branch network, N26 has redesigned banking for the 21st century and is available on Android, iOS, and desktop. N26 has raised close to $800 million from the world’s most established investors, including Insight Venture Partners, GIC, Tencent, Allianz X, Peter Thiel’s Valar Ventures, Li Ka-Shing’s Horizons Ventures, Earlybird Venture Capital, Greyhound Capital, Battery Ventures, in addition to members of the Zalando management board, and Redalpine Ventures. N26 currently operates in: Austria, Belgium, Denmark, Estonia, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland and the US, where it operates via its wholly-owned subsidiary, N26 Inc., based in New York. Banking services in the US are offered by N26 Inc. in partnership with Axos® Bank, Member FDIC.