SAE - A Stata Package for Unit Level Small Area Estimation
This paper presents a new family of Stata functions devoted to small area estimation. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for specific areas/sub-populations. This is accomplished b...
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| Format: | Working Paper |
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World Bank, Washington, DC
2018
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| Online Access: | http://documents.worldbank.org/curated/en/398721540906483895/sae-A-Stata-Package-for-Unit-Level-Small-Area-Estimation http://hdl.handle.net/10986/30650 |
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okr-10986-306502022-09-19T12:16:27Z SAE - A Stata Package for Unit Level Small Area Estimation Nguyen, Minh Cong Corral, Paul Azevedo, Joao Pedro Zhao, Qinghua SMALL AREA ESTIMATION POVERTY MAPPING BIG DATA GEOSPATIAL ECONOMICS STATA REMOTE SENSING This paper presents a new family of Stata functions devoted to small area estimation. Small area methods attempt to solve low representativeness of surveys within areas, or the lack of data for specific areas/sub-populations. This is accomplished by incorporating information from outside sources. Such target data sets are becoming increasingly available and can take the form of a traditional population census, but also large scale administrative records from tax administrations, or geospatial information produced using remote sensing. The strength of these target data sets is their granularity on the subpopulations of interest, however, in many cases they lack the ability to collect analytically relevant variables such as welfare or caloric intake. The family of functions introduced follow a modular design to have the flexibility with which these can be expanded in the future. This can be accomplished by the authors and/or other collaborators from the Stata community. Thus far, a major limitation of such analysis in Stata has been the large size of target data sets. The package introduces new mata functions and a plugin used to circumvent memory limitations that inevitably arise when working with big data. From an estimation perspective, the paper starts by implementing a methodology that has been widely used for the production of several poverty maps. 2018-11-01T18:44:01Z 2018-11-01T18:44:01Z 2018-10 Working Paper http://documents.worldbank.org/curated/en/398721540906483895/sae-A-Stata-Package-for-Unit-Level-Small-Area-Estimation http://hdl.handle.net/10986/30650 English Policy Research Working Paper;No. 8630 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research Publications & Research :: Policy Research Working Paper |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
SMALL AREA ESTIMATION POVERTY MAPPING BIG DATA GEOSPATIAL ECONOMICS STATA REMOTE SENSING |
| spellingShingle |
SMALL AREA ESTIMATION POVERTY MAPPING BIG DATA GEOSPATIAL ECONOMICS STATA REMOTE SENSING Nguyen, Minh Cong Corral, Paul Azevedo, Joao Pedro Zhao, Qinghua SAE - A Stata Package for Unit Level Small Area Estimation |
| relation |
Policy Research Working Paper;No. 8630 |
| description |
This paper presents a new family of
Stata functions devoted to small area estimation. Small area
methods attempt to solve low representativeness of surveys
within areas, or the lack of data for specific
areas/sub-populations. This is accomplished by incorporating
information from outside sources. Such target data sets are
becoming increasingly available and can take the form of a
traditional population census, but also large scale
administrative records from tax administrations, or
geospatial information produced using remote sensing. The
strength of these target data sets is their granularity on
the subpopulations of interest, however, in many cases they
lack the ability to collect analytically relevant variables
such as welfare or caloric intake. The family of functions
introduced follow a modular design to have the flexibility
with which these can be expanded in the future. This can be
accomplished by the authors and/or other collaborators from
the Stata community. Thus far, a major limitation of such
analysis in Stata has been the large size of target data
sets. The package introduces new mata functions and a plugin
used to circumvent memory limitations that inevitably arise
when working with big data. From an estimation perspective,
the paper starts by implementing a methodology that has been
widely used for the production of several poverty maps. |
| format |
Working Paper |
| author |
Nguyen, Minh Cong Corral, Paul Azevedo, Joao Pedro Zhao, Qinghua |
| author_facet |
Nguyen, Minh Cong Corral, Paul Azevedo, Joao Pedro Zhao, Qinghua |
| author_sort |
Nguyen, Minh Cong |
| title |
SAE - A Stata Package for Unit Level Small Area Estimation |
| title_short |
SAE - A Stata Package for Unit Level Small Area Estimation |
| title_full |
SAE - A Stata Package for Unit Level Small Area Estimation |
| title_fullStr |
SAE - A Stata Package for Unit Level Small Area Estimation |
| title_full_unstemmed |
SAE - A Stata Package for Unit Level Small Area Estimation |
| title_sort |
sae - a stata package for unit level small area estimation |
| publisher |
World Bank, Washington, DC |
| publishDate |
2018 |
| url |
http://documents.worldbank.org/curated/en/398721540906483895/sae-A-Stata-Package-for-Unit-Level-Small-Area-Estimation http://hdl.handle.net/10986/30650 |
| _version_ |
1764472530988433408 |