Guidelines to Small Area Estimation for Poverty Mapping
The eradication of poverty, which was the first of the millennium development goals (MDG) established by the United Nations and followed by the sustainable development goals (SDG), requires knowing where the poor are located. Traditionally, househo...
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Washington, DC : World Bank
2022
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| Online Access: | http://documents.worldbank.org/curated/en/099115306242236696/P1694340364c9803d0b7df097798bc42eac http://hdl.handle.net/10986/37728 |
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okr-10986-377282022-07-22T16:02:02Z Guidelines to Small Area Estimation for Poverty Mapping Corral, Paul Molina, Isabel Cojocaru, Alexandru Segovia, Sandra POVERTY MAPPING ESTIMATES FAY-HERRIOT MODEL AREA-LEVEL UNIT-LEVEL OFF-CENSUS YEARS DIAGNOSTICS The eradication of poverty, which was the first of the millennium development goals (MDG) established by the United Nations and followed by the sustainable development goals (SDG), requires knowing where the poor are located. Traditionally, household surveys are considered the best source of information on the living standards of a country’s population. Data from these surveys typically provide a sufficiently accurate direct estimate of household expenditures or income and thus estimates of poverty at the national level and larger international regions. However, when one starts to disaggregate data by local areas or population subgroups, the quality of these direct estimates diminishes. Consequently, national statistical offices (NSOs) cannot provide reliable wellbeing statistical figures at a local level. For example, the module of socioeconomic conditions of the Mexican national survey of household income and expenditure (ENIGH) is designed to produce estimates of poverty and inequality at the national level and for the 32 federate entities (31 states and Mexico City) with disaggregation by rural and urban zones, every two years, but there is a mandate to produce estimates by municipality every five years, and the ENIGH alone cannot provide estimates for all municipalities with adequate precision. This makes monitoring progress toward the sustainable development goals more difficult. 2022-07-20T18:40:11Z 2022-07-20T18:40:11Z 2022-06-16 Report http://documents.worldbank.org/curated/en/099115306242236696/P1694340364c9803d0b7df097798bc42eac http://hdl.handle.net/10986/37728 English en_US CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank Washington, DC : World Bank Economic & Sector Work :: Other Poverty Study Economic & Sector Work World |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
POVERTY MAPPING ESTIMATES FAY-HERRIOT MODEL AREA-LEVEL UNIT-LEVEL OFF-CENSUS YEARS DIAGNOSTICS |
| spellingShingle |
POVERTY MAPPING ESTIMATES FAY-HERRIOT MODEL AREA-LEVEL UNIT-LEVEL OFF-CENSUS YEARS DIAGNOSTICS Corral, Paul Molina, Isabel Cojocaru, Alexandru Segovia, Sandra Guidelines to Small Area Estimation for Poverty Mapping |
| geographic_facet |
World |
| description |
The eradication of poverty, which was
the first of the millennium development goals (MDG)
established by the United Nations and followed by the
sustainable development goals (SDG), requires knowing where
the poor are located. Traditionally, household surveys are
considered the best source of information on the living
standards of a country’s population. Data from these surveys
typically provide a sufficiently accurate direct estimate of
household expenditures or income and thus estimates of
poverty at the national level and larger international
regions. However, when one starts to disaggregate data by
local areas or population subgroups, the quality of these
direct estimates diminishes. Consequently, national
statistical offices (NSOs) cannot provide reliable wellbeing
statistical figures at a local level. For example, the
module of socioeconomic conditions of the Mexican national
survey of household income and expenditure (ENIGH) is
designed to produce estimates of poverty and inequality at
the national level and for the 32 federate entities (31
states and Mexico City) with disaggregation by rural and
urban zones, every two years, but there is a mandate to
produce estimates by municipality every five years, and the
ENIGH alone cannot provide estimates for all municipalities
with adequate precision. This makes monitoring progress
toward the sustainable development goals more difficult. |
| format |
Report |
| author |
Corral, Paul Molina, Isabel Cojocaru, Alexandru Segovia, Sandra |
| author_facet |
Corral, Paul Molina, Isabel Cojocaru, Alexandru Segovia, Sandra |
| author_sort |
Corral, Paul |
| title |
Guidelines to Small Area Estimation for Poverty Mapping |
| title_short |
Guidelines to Small Area Estimation for Poverty Mapping |
| title_full |
Guidelines to Small Area Estimation for Poverty Mapping |
| title_fullStr |
Guidelines to Small Area Estimation for Poverty Mapping |
| title_full_unstemmed |
Guidelines to Small Area Estimation for Poverty Mapping |
| title_sort |
guidelines to small area estimation for poverty mapping |
| publisher |
Washington, DC : World Bank |
| publishDate |
2022 |
| url |
http://documents.worldbank.org/curated/en/099115306242236696/P1694340364c9803d0b7df097798bc42eac http://hdl.handle.net/10986/37728 |
| _version_ |
1764487796881358848 |