Annex B. Social Institutions and Gender Index methodology

The Social Institutions and Gender Index (SIGI) covers four dimensions, spanning major socio-economic areas that affect the entire lifetimes of women and girls (Figure A B.1):

  • The “Discrimination in the family” dimension captures social institutions that limit women’s decision-making power and undervalue their status in the household and the family.

  • The “Restricted physical integrity” dimension captures social institutions that increase women’s and girls’ vulnerability to multiple forms of violence and limit their control over their bodies and reproductive autonomy.

  • The “Restricted access to productive and financial resources” dimension captures women’s restricted access to, and control over, critical productive and economic resources and assets.

  • The “Restricted civil liberties” dimension captures discriminatory laws and practices restricting women’s access to, and participation and voice in, the public and social spheres.

Each dimension builds on four indicators. In theory, each indicator builds on a combination of three variables: the first variable aims to measure the level of discrimination in formal and informal laws, while the second and the third variables aim to measure the level of discrimination in social norms and practices, respectively. The variables used as proxies for each indicator depend on data availability and reliability, and on country coverage. For example, some variables are not available at all (such as information on the social acceptance of discriminatory inheritance practices), and some variables are only available for a few countries (such as the time spent on unpaid care work).

Consequently, discrepancies exist between the theoretical framework and the variables effectively included in the SIGI 2019. Overall, the SIGI framework builds on 27 core variables:

  • Fourteen categorical variables describe the level of discrimination in legal frameworks (available for all SIGI indicators but two: missing women and female genital mutilation). These variables are based on 144 questions out of the 312 used to draft the SIGI country profiles.

  • Three attitudinal variables describe the level of discrimination in social norms.

  • Ten variables on prevalence rates describe the level of discrimination in practices.

The variables, indicators, dimensions and, ultimately, the SIGI are built according to the steps below.

Quantitative variables: Truncating data at the equality benchmark and inverting the scale

Quantitative data are collected and harmonised to be comparable across countries/territories. Data sources vary according to the country/territory and the variable. For example, the prevalence of child marriage among girls is collected through the UN World Marriage Database, while the proportion of women members of parliament is based on the Inter-Parliamentary Union Database.

All the SIGI components (variables, indicators, dimensions and index) range from 0, indicating no discrimination, to 100, indicating absolute discrimination:

  • For some variables, equality is reached at 50 instead of 100. Equality in political representation, for example, is achieved when 50% of MPs are women. Therefore, countries/territories where 50% or more of their MPs are female have a score of 0.

  • For some other variables, the scale from no discrimination to absolute discrimination may be inverted to fit with the 0-100 scale.

Qualitative variables: Assigning a score

The qualitative legal information detailed in the SIGI country profiles is quantified using a coding manual based on a 5-level scale (0, 25, 50, 75 and 1) (Table A B.1).

The variables composing each indicator are aggregated using the SIGI aggregation formula.

Some indicators are based on one variable, while others are based on several. In the latter case, the indicator is calculated only if all variables are assigned a value.

For example, for the “Violence against women” (VAW) indicator, the aggregation is:

VAW = ln13eLaws on VAW+ 13eAttitudes towards domestic violence+ 13ePrevalence of domestic violence

The indicators composing each dimension are aggregated using the SIGI aggregation formula.

The dimensions aim to provide a summary measure of each area of discrimination. The dimension is calculated only if all indicators are assigned a value.

For example, for the dimension “Discrimination in the family” (DF), the aggregation is:

DF = ln14eChild marriage+ 14eHousehold responsibilities+ 14eInheritance+ 14eDivorce

The SIGI is calculated only if all dimensions are assigned a value, using the same aggregation formula.

SIGI = ln14eDF+ 14eRPI+ 14eRAPFR+ 14eRCL

The SIGI country profiles are derived from a questionnaire on gender-related legal frameworks – both formal and traditional/cultural – in the countries and territories covered. The questions are mainly divided into two groups: legal framework (formal laws) and de facto (customary, religious or traditional practices or laws). While most of the questions have “Yes” or “No” answers, two of them have numeric values (i.e. the questions on the minimum legal age for marriage for women and men). The list of questions is presented in Table A B.3.

References

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Notes

← 1. ActionAID (2013); Bangladesh Bureau of Statistics (2013); Cabo Verde National Institute of Statistics (2012); ECLAC (2010); ECLAC (2016); General Statistics Office of Viet Nam (2014-15); Instituto Nacional de Estadistica y Censos – Costa Rica; National Institute of Statistics of Rwanda (2013-14); National Statistics, Republic of China (Chinese Taipei) (2000); OECD SIGI Burkina Faso country study (2018); OXFAM (2017); République de Guinée (2002-03); Statistics Sierra Leone (2003-04); Timor-Leste Ministry of Finance (2007); Troisième enquête camerounaise auprès des ménages; UNSD time use data portal (2016); Zimbabwe 2014 LFS.

← 2. ActionAID (2013); Bangladesh Bureau of Statistics (2013); Cabo Verde National Institute of Statistics (2012); ECLAC (2010); ECLAC (2016); General Statistics Office of Viet Nam (2014-15); Instituto Nacional de Estadistica y Censos – Costa Rica; National Institute of Statistics of Rwanda (2013-14); National Statistics, Republic of China (Chinese Taipei) (2000); OECD SIGI Burkina Faso country study (2018); OXFAM (2017); République de Guinée (2002-03); Statistics Sierra Leone (2003-04); Timor-Leste Ministry of Finance (2007); Troisième enquête camerounaise auprès des ménages; UNSD time use data portal (2016); Zimbabwe 2014 LFS.

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