Poverty mapping with aggregate census data: what is the loss in precision?
Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some cases, however, statistical authorities are reluctant, for reasons of confidentiality, to release household-level census data. This paper examines the loss in preci...
| Autores principales: | , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
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International Food Policy Research Institute
2002
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/156331 |
| _version_ | 1855541548927680512 |
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| author | Baulch, Bob Minot, Nicholas |
| author_browse | Baulch, Bob Minot, Nicholas |
| author_facet | Baulch, Bob Minot, Nicholas |
| author_sort | Baulch, Bob |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some cases, however, statistical authorities are reluctant, for reasons of confidentiality, to release household-level census data. This paper examines the loss in precision associated with using aggregated census data, such as village- or district-level means of the data. We show analytically that using aggregated census data will result in poverty rates that are biased downward (upward) if the rate is below (above) 50 percent and that the bias approaches zero as the poverty rate approaches zero, 50 percent, and 100 percent. Using data from Vietnam, we find that the average absolute error in estimating provincial poverty rates is about 2 percentage points if the data are aggregated to the enumeration-area level and around 3-4 percentage points if they are aggregated to the provincial level. Even census data aggregated to the provincial level perform reasonably well in ranking the 61 provinces by the incidence of poverty: the average absolute error in ranking is 0.92. |
| format | Artículo preliminar |
| id | CGSpace156331 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2002 |
| publishDateRange | 2002 |
| publishDateSort | 2002 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1563312025-11-06T07:24:20Z Poverty mapping with aggregate census data: what is the loss in precision? Baulch, Bob Minot, Nicholas surveys poverty censuses Spatially disaggregated maps of the incidence of poverty can be constructed by combining household survey data and census data. In some cases, however, statistical authorities are reluctant, for reasons of confidentiality, to release household-level census data. This paper examines the loss in precision associated with using aggregated census data, such as village- or district-level means of the data. We show analytically that using aggregated census data will result in poverty rates that are biased downward (upward) if the rate is below (above) 50 percent and that the bias approaches zero as the poverty rate approaches zero, 50 percent, and 100 percent. Using data from Vietnam, we find that the average absolute error in estimating provincial poverty rates is about 2 percentage points if the data are aggregated to the enumeration-area level and around 3-4 percentage points if they are aggregated to the provincial level. Even census data aggregated to the provincial level perform reasonably well in ranking the 61 provinces by the incidence of poverty: the average absolute error in ranking is 0.92. 2002 2024-10-24T12:43:50Z 2024-10-24T12:43:50Z Working Paper https://hdl.handle.net/10568/156331 en Open Access application/pdf International Food Policy Research Institute Baulch, Bob; Minot, Nicholas. 2002. Poverty mapping with aggregate census data: what is the loss in precision? MTID Discussion Paper 49. https://hdl.handle.net/10568/156331 |
| spellingShingle | surveys poverty censuses Baulch, Bob Minot, Nicholas Poverty mapping with aggregate census data: what is the loss in precision? |
| title | Poverty mapping with aggregate census data: what is the loss in precision? |
| title_full | Poverty mapping with aggregate census data: what is the loss in precision? |
| title_fullStr | Poverty mapping with aggregate census data: what is the loss in precision? |
| title_full_unstemmed | Poverty mapping with aggregate census data: what is the loss in precision? |
| title_short | Poverty mapping with aggregate census data: what is the loss in precision? |
| title_sort | poverty mapping with aggregate census data what is the loss in precision |
| topic | surveys poverty censuses |
| url | https://hdl.handle.net/10568/156331 |
| work_keys_str_mv | AT baulchbob povertymappingwithaggregatecensusdatawhatisthelossinprecision AT minotnicholas povertymappingwithaggregatecensusdatawhatisthelossinprecision |