- 1 Introduction
- 2 Poverty Indices
- 2.1 At Risk of Poverty Threshold (svyarpt)
- 2.2 At Risk of Poverty Ratio (svyarpr)
- 2.3 Relative Median Income Ratio (svyrmir)
- 2.4 Relative Median Poverty Gap (svyrmpg)
- 2.5 Median Income Below the At Risk of Poverty Threshold (svypoormed)
- 2.6 Foster-Greer-Thorbecke class (svyfgt, svyfgtdec)
- 2.7 Watts poverty measure (svywatts, svywattsdec)

- 3 Inequality Measurement
- 3.1 The Gender Pay Gap (svygpg)
- 3.2 Quintile Share Ratio (svyqsr)
- 3.3 Lorenz Curve (svylorenz)
- 3.4 Gini index (svygini)
- 3.5 Zenga index (svyzenga)
- 3.6 Entropy-based Measures
- 3.7 Generalized Entropy and Decomposition (svygei, svygeidec)
- 3.8 J-Divergence and Decomposition (svyjdiv, svyjdivdec)
- 3.9 Atkinson index (svyatk)
- 3.10 Which inequality measure should be used?

The R `convey`

library estimates measures of poverty, inequality, and wellbeing. There are two other R libraries covering this subject, vardpoor (Breidaks, Liberts, and Ivanova 2020Breidaks, Juris, Martins Liberts, and Santa Ivanova. 2020. *vardpoor: Estimation of Indicators on Social Exclusion and Poverty and Its Linearization, Variance Estimation*. Riga, Latvia: Central Statistical Bureau of Latvia. https://csblatvia.github.io/vardpoor/.) and laeken (Alfons and Templ 2013Alfons, Andreas, and Matthias Templ. 2013. “Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken.” *Journal of Statistical Software* 54 (15): 1–25. http://www.jstatsoft.org/v54/i15/.), however, only `convey`

integrates seamlessly with the R survey package (Lumley 2004Lumley, Thomas. 2004. “Analysis of Complex Survey Samples.” *Journal of Statistical Software* 9 (1): 1–19., 2010Lumley, Thomas. 2010. *Complex Surveys: A Guide to Analysis Using r: A Guide to Analysis Using r*. John Wiley; Sons., 2020Lumley, Thomas. 2020. “Survey: Analysis of Complex Survey Samples.”).

`convey`

is free and open-source software that runs inside the R environment for statistical computing. Anyone can review and propose changes to the source code for this software. Readers are welcome to propose changes to this book as well.

Individuals getting started in the field of poverty and inequality statistics might find the number of techniques described in this textbook overwhelming, especially on the topic of choosing which method might be most appropriate for each particular research question. For this reason, the authors of this textbook consider Dr. Ija Trapeznikova’s article Measuring income inequality an important summary of how to approach selecting between available techniques.