Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data
This paper combines remote-sensed data and individual child, mother, and household-level data from the Demographic and Health Surveys for 5 countries in Sub-Saharan Africa to design a prototype drought-contingent targeting framework for use in scar...
| Main Authors: | , , |
|---|---|
| Format: | Brief |
| Language: | English |
| Published: |
World Bank, Washington, DC
2020
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/448401596001667053/Adaptive-Safety-Nets-for-Rural-Africa-Drought-Sensitive-Targeting-with-Sparse-Data http://hdl.handle.net/10986/34301 |
| id |
okr-10986-34301 |
|---|---|
| recordtype |
oai_dc |
| spelling |
okr-10986-343012021-05-25T10:54:39Z Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data Baez, Javier E. Kshirsagar, Varun Skoufias, Emmanuel DEMOGRAPHIC AND HEALTH SURVEY POVERTY MEASUREMENT CLIMATE HAZARD WELFARE IMPACT REMOTE SENSING CHILD STUNTING CROP PRODUCTION HARVEST CYCLE DRY SPELL DROUGHT This paper combines remote-sensed data and individual child, mother, and household-level data from the Demographic and Health Surveys for 5 countries in Sub-Saharan Africa to design a prototype drought-contingent targeting framework for use in scarce-data contexts. To accomplish this, the paper: (i) develops simple and easy-to-communicate measures of drought shocks; (ii) shows that droughts have a large impact on child stunting in these five countries, comparable, in size, to the effects of mother’s illiteracy or a fall to a lower wealth quintile; and (iii) shows that, in this context, decision trees and regressions predict stunting as accurately as complex machine learning methods that are not interpretable.2 Taken together, the analysis lends support to the idea that a data-driven approach may contribute to the design of a transparent and easy-to-use drought-contingent targeting framework 2020-08-10T14:52:39Z 2020-08-10T14:52:39Z 2020-07 Brief http://documents.worldbank.org/curated/en/448401596001667053/Adaptive-Safety-Nets-for-Rural-Africa-Drought-Sensitive-Targeting-with-Sparse-Data http://hdl.handle.net/10986/34301 English Poverty and Equity Notes;No. 26 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Brief Africa Middle East and North Africa Sub-Saharan Africa Djibouti |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
DEMOGRAPHIC AND HEALTH SURVEY POVERTY MEASUREMENT CLIMATE HAZARD WELFARE IMPACT REMOTE SENSING CHILD STUNTING CROP PRODUCTION HARVEST CYCLE DRY SPELL DROUGHT |
| spellingShingle |
DEMOGRAPHIC AND HEALTH SURVEY POVERTY MEASUREMENT CLIMATE HAZARD WELFARE IMPACT REMOTE SENSING CHILD STUNTING CROP PRODUCTION HARVEST CYCLE DRY SPELL DROUGHT Baez, Javier E. Kshirsagar, Varun Skoufias, Emmanuel Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| geographic_facet |
Africa Middle East and North Africa Sub-Saharan Africa Djibouti |
| relation |
Poverty and Equity Notes;No. 26 |
| description |
This paper combines remote-sensed data
and individual child, mother, and household-level data from
the Demographic and Health Surveys for 5 countries in
Sub-Saharan Africa to design a prototype drought-contingent
targeting framework for use in scarce-data contexts. To
accomplish this, the paper: (i) develops simple and
easy-to-communicate measures of drought shocks; (ii) shows
that droughts have a large impact on child stunting in these
five countries, comparable, in size, to the effects of
mother’s illiteracy or a fall to a lower wealth quintile;
and (iii) shows that, in this context, decision trees and
regressions predict stunting as accurately as complex
machine learning methods that are not interpretable.2 Taken
together, the analysis lends support to the idea that a
data-driven approach may contribute to the design of a
transparent and easy-to-use drought-contingent targeting framework |
| format |
Brief |
| author |
Baez, Javier E. Kshirsagar, Varun Skoufias, Emmanuel |
| author_facet |
Baez, Javier E. Kshirsagar, Varun Skoufias, Emmanuel |
| author_sort |
Baez, Javier E. |
| title |
Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| title_short |
Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| title_full |
Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| title_fullStr |
Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| title_full_unstemmed |
Adaptive Safety Nets for Rural Africa : Drought-Sensitive Targeting with Sparse Data |
| title_sort |
adaptive safety nets for rural africa : drought-sensitive targeting with sparse data |
| publisher |
World Bank, Washington, DC |
| publishDate |
2020 |
| url |
http://documents.worldbank.org/curated/en/448401596001667053/Adaptive-Safety-Nets-for-Rural-Africa-Drought-Sensitive-Targeting-with-Sparse-Data http://hdl.handle.net/10986/34301 |
| _version_ |
1764480610098741248 |