Mapping Deprivations in Mauritania

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.


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, large gaps in human capital endowment hinder economic growth and contribute to chronic poverty.In Mauritania, poverty-as measured at the international poverty line of US$1.9 2011 PPP per day per capita-has dropped over the past decade from 10.9 percent in 2008 to 6.0 percent in 2014.This progress, however, masks disparities in living standards.
Policymakers must understand overlapping deprivations when designing projects and 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 services, such as education, and infrastructure, including paved roads and internet.This limits human capital accumulation and access to job opportunities.In addition, limited access to key services such as hospital care undermines productivity and resilience, and reduces the ability of households to absorb adverse shocks.This is a growing concern in the face of climate change.
1 Authors listed in alphabetical order.A deprivation map focuses on access to services and opportunities, which is imperative for people to generate income and achieve decent living standards.This is in contrast to a poverty map, which depicts variation in monetary welfare.The 2016 poverty map from the Mauritania Office National de la Statistique, (ONS) shows spatial differences in monetary welfare across 44 Moughataas (admin2 level). 2 The deprivation map complements the poverty map by providing a more granular picture at the lowest geographic level (1,673 settlements compared to 44 Moughataas, see Figure 1).Table 1)  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). 3Where 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.For each of 1,673 settlements (see Figure 1), we obtained data corresponding to each dimension from several sources.For "access to social services" we obtained data from the Mauritania's Ministry of Health (2019, Figure 2) and UNICEF (2017)."Access to basic infrastructure" represents travel distances from a settlement to the nearest road and the nearest 3G and 2G tower (Open Street maps and Ministry of Employment)."Access to represents the distance from the nearest urban center (AfricaPolis project, OECD, 2019).Finally, "exposure to weather/climate shocks" uses the Standardized Precipitation Evapotranspiration Index (SPEI) measure, which estimates monthly moisture level or "effective rainfall" for gridded areas (0.5 spatial resolution).Our estimate of environmental shocks uses a settlement's average SPEI during the growing season (June-September) for 6 years (2010-2015).

Final index calculation represents the weighted average of deprivation scores across all indicators and dimensions.
The final index gives equal weights to each of the 4 deprivation dimensions (access to services, access to infrastructure, access to opportunities, and environmental conditions), and to each indicator within each dimension.This assumes that each indicator equally undermines social cohesion and development, but the approach is modifiable to reflect different interests and goals.

Results
Our methodology was designed to be simple, replicable, and easy for policy makers to understand.The deprivation index ranks all settlements along multiple indicators, and allows mapping of non-monetary welfare disparities across settlements.Results can also be averaged at higher geographic units (Moughataa or Commune level), but this requires information on settlement population.Given data constraints, we estimated settlement population based on population density obtained from Facebook.Localities with high deprivation index in the south-central area also represent a large share of the population (Figure 5).Comparing rankings at the Moughataa level shows a 0.5 correlation between the monetary poverty map and the deprivation map.This means that, while deprivation in access to services may proxy for final monetary welfare measures, they are not necessarily aligned-they complement one another.For instance, some settlements might have decent access to social services and basic infrastructure but due to a concentration of economic activity in Nouakchott and Nouadhibou, households are not able to generate sufficient income to lift them above the poverty line.
Overall, localities in Mauritania's south-central 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.
Adding the findings from deprivations maps to 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.and population estimates from each locality produced by Mauritania's ONS to estimate the percent of population with access to health care services.We estimate that out of 1,673 localities, 53 percent are within 5 km to any health facilities (health post, health center or hospital), 23 percent are between 5 and 10km, 21 percent between 10 and 50km, and 3 percent are greater than 50km away.
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

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.
based on several criteria: (a) use in previous studies on spatial disparity, (b) their relevance to Mauritania (validated in Government consultations), (c) availability and comprehensiveness of the data, and (d) ease with which each dataset can be updated.
Dimension: Access to social services Health (WB/ Ministère de la Sante) Distance (straight-line, travel) to nearest Hospital Distance (straight-line, travel) to nearest Health Center Distance (straight-line, travel) to nearest Health Post Education (UNICEF) Distance (straight-line, travel) to nearest school with low teacher-pupil ratio Distance (straight-line, travel) to nearest school with latrine Distance (straight-line, travel) to any school Dimension: Access to basic infrastructure Roads (Open Street Maps) Distance (straight-line) to nearest major road (-line, travel) to nearest urban center 3 We use travel distance rather than straight-line distance ("as the crow-flies") as this more likely reflects the realities of access to

Figure 4 :
Figure 4: Deprivation ranking, for each settlement in Mauritania.

Figure 6 :
Figure 6: Distances to health facilities Anais Dahmani-Scuitti, is a consultant for the World Bank's Poverty and Equity Global Practice, and the Social Protection and Jobs 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.
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.