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...
| Main Authors: | , , , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2018
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| Subjects: | |
| 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 |
| Summary: | 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. |
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