GeoDevelopment Observatory of Bolivia / Indicators
SDG 5: Gender equality
The SDG 5 gender equality index of the Municipal Atlas of the SDGs and its four gender parity indicators in schooling, poverty and work, for every municipality.
The SDG 5 (Gender equality) index of the Municipal Atlas of the Sustainable Development Goals in Bolivia 2020 (SDSN Bolivia) for all 339 municipalities, with the four gender parity indicators behind it: parity in secondary-school dropout (2017, Ministry of Education records), and parity in years of schooling of people aged 25–35, in multidimensional poverty by sex of the household head and in labour-force participation (all 2012, from the Population and Housing Census, INE). Each indicator is rescaled to 0–100 between a worst and a best value (parity, or the average of the best municipalities), so that higher is always better and values beyond the bounds are capped, and the index is the simple mean of the available rescaled indicators: 100 means the targets are met. The index is stored at 2017, the latest year of its indicators. The parity indicators are published with one decimal only, so they reproduce the index only approximately. Labour participation parity is missing for Huachacalla. The Atlas’s 2020 population and 2012 urbanization rate are included as context.
Variables of sdg05
index_sdg5: Gender equality index (0-100). SDG 5 (Gender equality) index of the Municipal Atlas of the SDGs in Bolivia 2020, on a 0-100 scale where 100 means the goal's targets are met (best value) and 0 the worst situation. Following the global SDG Index method (Lafortune et al., 2018), each of its 4 indicators is rescaled linearly to 0-100 between a worst value (generally the 2.5th-percentile tail of the municipal distribution) and a best value (the SDG target where one exists, otherwise the average of the five best municipalities, or expert judgement), with the direction set so that higher is always better and values beyond the bounds capped at 0 or 100; the index is the simple (equal-weight) mean of the available rescaled indicators. Components: Gender parity in secondary dropout; Gender parity in youth schooling; Gender parity in poverty (MPI); Gender parity in labour participation. The components refer to different years; the observatory stores the index at 2017, the latest reference year among them. The components are published with one decimal only (sdg5_1_gpyp takes just 6 distinct values), and with bounds as narrow as 0.6-1 one decimal shifts a component by up to about 12 points, so the stored components reproduce the index only approximately; the Atlas computed it from unrounded values.sdg5_1_gpsd: Gender parity in secondary dropout. Gender parity index of secondary-school dropout, 2017, from Ministry of Education records (SEIE). The Atlas gives no formula; the values (0-7, median 1.4, one decimal) track the ratio of the male to the female dropout rate (correlation 0.96 with sdg4_1_ssdrm / sdg4_1_ssdrf; 1 where the female rate is 0), so 1 or more means girls drop out no more than boys. The goal is one-directional: women should be at least as well off as men. In the SDG 5 index it is normalised linearly between 0 (worst; 2.5th-percentile tail) and 1 (best; SDG target: parity; values above 1 count as 100), values beyond the bounds capped.sdg5_1_gpyp: Gender parity in youth schooling. Gender parity index in years of education of young people aged 25-35, 2012: women's years of schooling relative to men's (1 = parity; below 1 means women have fewer years). Atlas calculation from the 2012 Population and Housing Census (INE). Published with one decimal only. In the SDG 5 index it is normalised linearly between 0.6 (worst; 2.5th-percentile tail) and 1 (best; SDG target: parity), values beyond the bounds capped.sdg5_1_gpmpi: Gender parity in poverty (MPI). Gender parity index in the multidimensional poverty index by sex of the household head, 2012 (Andersen & Branisa, 2020), from the 2012 Population and Housing Census (INE): whether female-headed households are more likely to be poor than male-headed ones across the 9 deprivations. Values below 1 mean female-headed households are worse off; the exact ratio is not stated. Published with one decimal only. In the SDG 5 index it is normalised linearly between 0.623 (worst; 2.5th-percentile tail) and 1 (best; SDG target: parity), values beyond the bounds capped.sdg5_5_gpop: Gender parity in labour participation. Ratio of the female to the male global labour-force participation rate (population aged 10 or older that works, with or without pay, or seeks work), 2012, dividing two official INE rates from the 2012 Population and Housing Census (INE) (equal to sdg8_5_ofrm / sdg8_5_oprm rounded to one decimal). In the SDG 5 index it is normalised linearly between 0.42 (worst; 2.5th-percentile tail) and 0.95 (best; SDG target / average of the top 5), values beyond the bounds capped.population_2020: Population (persons). Estimated municipal population in 2020 (persons), as printed in the Atlas municipal profiles ("Población estimada, 2020"). The Atlas does not name the source; the 339 values sum to 11,633,371, exactly INE's 2020 national population projection (Revisión 2020 series), so they are presumably INE's municipal projections. Not an input of any goal index. Differs from the gridded WorldPop-based pop dataset.urbano_2012: Urbanization rate (%). Share of the municipal population living in urban areas in 2012 (%), as printed in the Atlas municipal profiles ("Tasa de urbanización, 2012"), from the 2012 Population and Housing Census (INE). INE counts as urban the localities with 2,000 or more inhabitants, which is why 175 municipalities have a rate of 0. Not an input of any goal index (the Atlas treats 15 almost fully urban municipalities as having no applicable farm indicators for SDG 2; 11 of them are 95% or more urban by this rate, while Sucre, Tiquipaya and Potosí are 91–92% and Yunguyo de Litoral 0%).
Sources
- Andersen, L. E., Canelas, S., Gonzales, A., & Peñaranda, L. (2020). Atlas municipal de los Objetivos de Desarrollo Sostenible en Bolivia 2020. La Paz: Universidad Privada Boliviana, SDSN Bolivia. https://unsdsn.org/resources/municipal-atlas-of-the-sdgs-in-bolivia-2020
- Mendez, C., Gonzales, E., Leoni, P., Andersen, L., & Peralta, H. (2026). DS4Bolivia: A Data Science Repository to Study GeoSpatial Development in Bolivia [Data set]. GitHub. https://github.com/quarcs-lab/ds4bolivia