Calculation of weights within each subindex TABLE B.2 Ratio Standard deviation Standard deviation per 1% point changeWeight Labour-force participation rate, % (females-to-males ratio) 0.160 0.063 0.199 Wage equality for similar work (survey), 1-7 scale (females-to-males ratio) 0.103 0.097 0.310 Estimated earned income, PPP, int.$ (females-to-males ratio) 0.144 0.069 0.221 Legislators, senior officials and managers, % (females-to-males ratio) 0.214 0.047 0.149 Professional and technical workers, % (females-to-males ratio) 0.262 0.038 0.121Economic Participation and Opportunity Ratio Standard deviation Standard deviation per 1% point changeWeight Literacy rate, % (females-to-males ratio) 0.145 0.069 0.191 Enrolment in primary education, % (females-to-males ratio) 0.060 0.167 0.459 Enrolment in secondary education, % (females-to-males ratio) 0.120 0.083 0.230 Enrolment in tertiary education, % (females-to-males ratio) 0.228 0.044 0.121Educational Attainment Ratio Standard deviation Standard deviation per 1% point changeWeight Women in parliament, % (females-to-males ratio) 0.166 0.06 0.31 Women in ministerial positions, % (females-to-males ratio) 0.208 0.048 0.247 Years with female head of state (last 50), Share of tenure years (females-to-males ratio) 0.116 0.086 0.443Political EmpowermentRatio Standard deviation Standard deviation per 1% point changeWeight Sex ratio at birth, % (females-to-males ratio) 0.010 0.998 0.693 Healthy life expectancy, years (females-to-males ratio) 0.023 0.441 0.307Health and Survival Note Population-weighted averages, including the 102 economies featured throughout all the 2006- 2023 editions of the Global Gender Gap Index. are calculated. Then we determine what a 1 percentage-point change would translate to in terms of standard deviations by dividing 0.01 by the standard deviation for each indicator. These four values are then used as weights to calculate the weighted average of the four indicators. This way of weighting indicators allows us to make sure that each indicator has the same relative impact on the subindex. For example, an indicator with a small variability or standard deviation gets a larger weight within the subindex than an indicator with a larger variability. Therefore, a country with a large gender gap in the first indicator will be more heavily penalized. Another example is the case of the sex ratio at birth indicator (within the Health and Survival subindex): where most countries have a very high sex ratio and the spread of the data is small, the larger weight will penalize more heavily those countries that deviate from this value. Table B2 displays the values of the weights used.8 Step 4. Calculation of final scores: For all subindexes, the highest possible score is 1 (gender parity) and the lowest possible score is 0 (imparity).9 A simple average of each subindex score is used to calculate the overall Global Gender Gap Index score – a final value that, like subindex scores, ranges between 1 (parity) and 0 (imparity). The parity and imparity benchmarks have remained fixed through report editions to allow for the comparison and relative ranking of countries10 in a given year, and across time. This allows readers to track individual country progress. Furthermore, the option of roughly interpreting the final index scores Global Gender Gap Report 2023 65

GGGR 2023