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Small area estimation/Poverty Map in Stata

Author

Listed:
  • Minh Nguyen

    (World Bank)

  • Paul Andres Corral Rodas

    (World Bank)

  • Joao Pedro Wagner De Azevedo

    (World Bank)

  • Qinghua Zhao

    (World Bank)

Abstract

We present a new Stata package for small area estimations of poverty and inequality implementing methodologies from Elbers, Lanjouw, and Lanjouw (Econometrica, 2003). 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. A common outside source is census data which often lacks detailed information on welfare. Thus far, a major limitation towards such analysis in Stata has been the memory required to work with census data . The povmap package introduces new mata functions and a plugin used to circumvent memory limitations that will arise when working with big data.

Suggested Citation

  • Minh Nguyen & Paul Andres Corral Rodas & Joao Pedro Wagner De Azevedo & Qinghua Zhao, 2017. "Small area estimation/Poverty Map in Stata," 2017 Stata Conference 20, Stata Users Group.
    • Handle: RePEc:boc:scon17:20
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    File URL: http://fmwww.bc.edu/repec/scon2017/Baltimore17_Nguyen.pdf
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