POVERTY & EQUITY NOTES SEPTEMBER 2020 · NUMBER 34 Mapping Deprivations in Mauritania Anais Dahmani-Scuitti, Jesse Doyle, Matthieu Lefebvre, Moritz Meyer, and Anirudh Rajashekar 1 Recent economic growth In Mauritania has helped reduce poverty, but spatial disparities in terms of both monetary welfare and access to services and opportunities remain. Designing policies and projects to improve living conditions requires localized and updated data not usually available from household surveys. Deprivation mapping—a new spatial deprivation analysis tool—uses administrative and geospatial settlement-level data (the lowest administrative unit in our case study Mauritania) to estimate settlement access deprivations across 4 dimensions: social services, basic infrastructure, opportunities, and exposure to weather/climate shocks. Database and visualizations (map) highlight and rank each settlement’s deprivation index, enhancing national data and showing spatial differences in the depth, complexity, and persistence of deprivations to inform policies and prioritize investments. Despite low monetary poverty in Mauritania, A deprivation map focuses on access to services large gaps in human capital endowment hinder and opportunities, which is imperative for people economic growth and contribute to chronic to generate income and achieve decent living poverty. In Mauritania, poverty—as measured at the standards. This is in contrast to a poverty map, which international poverty line of US$1.9 2011 PPP per day depicts variation in monetary welfare. The 2016 per capita—has dropped over the past decade from poverty map from the Mauritania Office National de 10.9 percent in 2008 to 6.0 percent in 2014. This la Statistique, (ONS) shows spatial differences in progress, however, masks disparities in living monetary welfare across 44 Moughataas (admin2 standards. level). 2 The deprivation map complements the poverty map by providing a more granular picture at Policymakers must understand overlapping the lowest geographic level (1,673 settlements deprivations when designing projects and compared to 44 Moughataas, see Figure 1). policies. Mauritania ranks 150 out of 157 countries on the Human Capital Index (HCI) (World Bank, 2019). A large share of Mauritanians face limited access to Methodology and Data services, such as education, and infrastructure, including paved roads and internet. This limits We selected deprivation dimensions and human capital accumulation and access to job indicators (see Table 1) based on several criteria: opportunities. In addition, limited access to key (a) use in previous studies on spatial disparity, (b) services such as hospital care undermines their relevance to Mauritania (validated in productivity and resilience, and reduces the ability of Government consultations), (c) availability and households to absorb adverse shocks. This is a growing concern in the face of climate change. 1 Authors listed in alphabetical order. 2 The poverty map for Mauritania is based on the national household survey Enquête Permanente sur les Conditions de Vie des ménages (EPCV) 2014 and the population census 2013. September 2020 · Number 34 1 comprehensiveness of the data, and (d) ease with Figure 1: Settlements in Mauritania, ONS 2012 which each dataset can be updated. For all indicators, except weather/climate shocks, we measure “access” by travel distance, based on the shortest road travel between each of the 1,673 settlements and the nearest “point of interest”, for instance a hospital (see Figure 3). 3 Where the point of interest is a line (that is, a main road), we estimate the distance of a settlement to the closest point of the line. We calculate the deprivation score for each indicator based on the relative position of each settlement in the national distribution. Figure 2: Hospitals, health point and centers, Table 1. Dimensions and indicators on deprivations Ministry of Health (2019) Dimension: Access to social services Distance (straight-line, travel) to nearest Hospital Health Distance (straight-line, travel) to nearest Health (WB/ Ministère de la Center Sante) Distance (straight-line, travel) to nearest Health Post Distance (straight-line, travel) to nearest school with low teacher-pupil ratio Education (UNICEF) Distance (straight-line, travel) to nearest school with latrine Distance (straight-line, travel) to any school Dimension: Access to basic infrastructure Roads Distance (straight-line) to nearest major road (Open Street Maps) (“jump distance”) Internet / 3G (Ministere de Distance (straight-line) to nearest 3G phone tower l’Emploi) Figure 3: Travel distance to nearest hospital Cellular Phone reception Distance (straight-line) to nearest 2G phone tower (Ministere de l’Emploi) Dimension: Access to opportunities Urban Centers Distance (straight-line, travel) to nearest urban (AfricaPolis) center 3 We use travel distance rather than straight-line distance (“as the “points of interest”. Results are robust to using travel time rather crow-flies”) as this more likely reflects the realities of access to than travel distance. September 2020 · Number 34 2 For each of 1,673 settlements (see Figure 1), we obtained data corresponding to each dimension Results from several sources. For “access to social services” we obtained data from the Mauritania’s Ministry of Our methodology was designed to be simple, Health (2019, Figure 2) and UNICEF (2017). “Access to replicable, and easy for policy makers to basic infrastructure” represents travel distances from understand. The deprivation index ranks all a settlement to the nearest road and the nearest 3G settlements along multiple indicators, and allows and 2G tower (Open Street maps and Ministry of mapping of non-monetary welfare disparities across Employment). “Access to opportunities” represents settlements. Results can also be averaged at higher the distance from the nearest urban center geographic units (Moughataa or Commune level), but (AfricaPolis project, OECD, 2019). Finally, “exposure this requires information on settlement population. to weather/climate shocks” uses the Standardized Given data constraints, we estimated settlement Precipitation Evapotranspiration Index (SPEI) population based on population density obtained measure, which estimates monthly moisture level or from Facebook. Localities with high deprivation index “effective rainfall” for gridded areas (0.5 spatial in the south-central area also represent a large share resolution). Our estimate of environmental shocks of the population (Figure 5). Comparing rankings at uses a settlement’s average SPEI during the growing the Moughataa level shows a 0.5 correlation between season (June-September) for 6 years (2010-2015). the monetary poverty map and the deprivation map. This means that, while deprivation in access to Final index calculation represents the weighted services may proxy for final monetary welfare average of deprivation scores across all indicators measures, they are not necessarily aligned—they and dimensions. The final index gives equal weights complement one another. For instance, some to each of the 4 deprivation dimensions (access to settlements might have decent access to social services, access to infrastructure, access to services and basic infrastructure but due to a opportunities, and environmental conditions), and to concentration of economic activity in Nouakchott each indicator within each dimension. This assumes and Nouadhibou, households are not able to that each indicator equally undermines social generate sufficient income to lift them above the cohesion and development, but the approach is poverty line. modifiable to reflect different interests and goals. Figure 4: Deprivation ranking, for each settlement in Overall, localities in Mauritania’s south-central Mauritania. area (“Triangle of Hope”) face high deprivations across multiple indicators (see Figure 4). People living in these areas must travel large distances to access key amenities, demonstrating the complex challenges of reducing poverty in Mauritania. Policy Making Implications Deprivation mapping can inform policies and projects, and help prioritize investments in social services and infrastructure. Deprivations maps complement monetary poverty monitoring; it is important that policy makers pay attention to both measures to close the spatial gap in living conditions. September 2020 · Number 34 3 Adding the findings from deprivations maps to Figure 6: Distances to health facilities discussions with governments and within the World Bank can help client countries to: (a) Allocate quotas for social programs, such as Mauritania’s Tekavoul and Elmaouna programs, even at the settlements level. (b) Produce maps and indicators on access to select services; for instance, distance to a health facility (Figure 6). Although national Mauritanian standards dictate that all citizens should be within 5 km of a health facility, our results suggest that this applies to only 2,224,501, or 58 percent of people. 4 (c) Produce highly disaggregated maps to show local-level access to internet services. Figure 5: Population density in 2018 in Mauritania, CIESN/ Facebook ABOUT THE AUTHORS Anais Dahmani-Scuitti, is a consultant for the World Bank’s Poverty and Equity Global Practice, and the Social Protection and Jobs Global Practice. Jesse Doyle is an Economist in the in the World Bank’s Social Protection and Jobs Global Practice. Matthieu Lefebvre is a Senior Social Protection Specialist in the in the World Bank’s Social Protection and Jobs Global Practice. Moritz Meyer is an Economist in the World Bank’s Poverty and Equity Global Practice. Anirudh Rajashekar is a consultant for the World Bank’s Poverty and Equity Global Practice and Urban and Disaster Risk Management Global Practice. This note series is intended to summarize good practices and key policy findings on Poverty-related topics. The views expressed in the notes are those of the authors and do not necessarily reflect those of the World Bank, its board or its member countries. Copies of the notes from this series are available on www.worldbank.org/poverty 4 We use total population estimates from WDI in 2013 (3,817,494) post, health center or hospital), 23 percent are between 5 and and population estimates from each locality produced by 10km, 21 percent between 10 and 50km, and 3 percent are Mauritania’s ONS to estimate the percent of population with greater than 50km away. access to health care services. We estimate that out of 1,673 localities, 53 percent are within 5 km to any health facilities (health September 2020 · Number 34 4