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Rachel Snow United Nations Population Fund

Capacity strengthening to estimate SDG indicators at lower geographic levels – Small Area Estimation (SAE). Rachel Snow United Nations Population Fund. SDG Indicator 3.7.1 : proportion of women age 15-49 years who have their need for family planning satisfied with modern methods.

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Rachel Snow United Nations Population Fund

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  1. Capacity strengthening to estimate SDG indicators at lower geographic levels – Small Area Estimation (SAE) Rachel Snow United Nations Population Fund

  2. SDG Indicator 3.7.1 : proportion of women age 15-49 years who have their need for family planning satisfied with modern methods Data sources: Nationally representative population surveys [including: Contraceptive Prevalence Surveys (CPS), Demographic and Health Surveys (DHS), Fertility and Family Surveys (FFS), Reproductive Health Surveys (RHS), Multiple Indicator Cluster Surveys (MICS), Performance Monitoring and Accountability 2020 surveys (PMA), World Fertility Surveys (WFS), etc..] Challenge: With sample sizes - level of geographic disaggregation limited - often to one level below national (e.g. regional, provincial etc.). Opportunity: • Censuses lack data on family planning, but include data related to use of family planning e.g. level of education, occupation, residence, hh wealth, children ever born, children surviving. • When a national household survey is conducted close to the census – opportunity to combine sources for SAE of Indicator 3.7.1 at lower geographic level

  3. Key Steps of Small Area Estimation Small Area Estimation (SAE) • Data Analysis and Assessment • Regression model coefficients for predicting probability of using contraception for an individual woman obtained from DHS data • The national coefficients from DHS are applied to Census Data to predict the probability of using contraception for individual women • The individual contraceptive use probabilities from census data are aggregated (using average) to district level Application of SAE • Estimate the number of women aged 15-49 (married or in union) in need of contraception • Identify priority districts Major Steps: 1. Identify common variables associated with contraceptive indicators in DHS and census data DHS CENSUS DHS Variable 1 2. Develop a model for predicting the probability of individual contraceptive use using DHS data Variable 2 Variable 3 …… CENSUS 3. Apply the model to census and estimate the probability of individual contraceptive use 4. Aggregate the estimation of individual contraceptive use to small area administrative level and map results

  4. Estimating proportion of women with need for family planning satisfied with modern methods (SDG Indicator 3.7.1) at district level, -Nepal DHS Data- regional level Note: Census year is same year as DHS year or close Small Area Estimation using Census and DHS- district level

  5. Wider Applications • SAE approach can be used to estimate other SDG indicators at lower geographic levels – FGM, gender based violence etc. • Applicability depends on: • Census and survey data collected around the same time • Relevant variables and data compatibility between census and survey- • Suitability of the prediction model- analysis of model fitness

  6. Lessons Learned: Strengthening capacity of NSOs to use SAE • Various training modalities • Week-long hands-on regional training in Asia Pacific Region in 2016 • Shorter workshops in 2017 in Abuja, the Global Data Forum, Kenya, and SDG Training in Korea last week - have touched NSOs from a range of countries • Background of participants crucial – Ease using both data sets • Preloading census data and DHS data • Multiple representatives from a given institution improves retention and use • Readiness for follow-up -

  7. Approach going forward • 2018 training of trainers – cascade approach • National hosting within each UNFPA region – where sufficient expertise is already present to support others • Preloaded data from one country – simplifies approach • Partnerships sought with other institutions – UNICEF, World Bank? • Common methods – different applications

  8. Thank you !

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