João Pedro Azevedo

João Pedro Azevedo

Chief Statistician @ UNICEF | Development Economist

ISOPOVERTY

Map the growth-redistribution trade-offs needed to reach a poverty target by plotting iso-poverty, growth-poverty, and inequality-poverty curves — key tools for pro-poor policy analysis.

SSC Stata SSC GitHub Issues

Installation

Stata ssc install isopoverty

Description

isopoverty generates data for plotting three types of analytical curves used in poverty and inequality analysis:

  • Inequality-Poverty curves: How changes in inequality affect poverty measures.
  • Growth-Poverty curves: How growth affects poverty measures.
  • Iso-Poverty curves: Combinations of growth and inequality reduction that yield the same poverty level.

The tool builds on methodologies from Kakwani, Pernia, Bourguignon, and others studying pro-poor growth dynamics. Results are stored as matrices (r(ineqreduc), r(growth), r(frontier)) that can be exported using svmat for customized visualization.

Note: The iso-poverty computation is computationally intensive. It is recommended to first estimate the inequality-poverty and growth-poverty curves to identify optimal parameters.

Examples

* Inequality-poverty curve
isopoverty rdpc [fw=peso], stepinq(50) varpl(lp)

* Iso-poverty frontier with growth and inequality dimensions
isopoverty rdpc [fw=peso], stepinq(50) stepgrw(10) ///
    mininq(0) maxinq(.50) mingrw(0) maxgrw(1.50) ///
    target(25) int(2) frontier varpl(lp)

Citation

Azevedo, J.P. and Franco, S. (2006). “ISOPOVERTY: Stata module to generate data for Inequality-Poverty and Iso-Poverty curves.” Statistical Software Components S456752, Boston College Department of Economics.