Insights and inference for the proportion below the relative poverty line

TL;DR

This paper analyzes the headcount ratio as a measure of relative poverty, deriving confidence intervals for it, and demonstrates its application on real income data to assess poverty changes.

Contribution

It introduces methods for constructing confidence intervals for the headcount ratio and evaluates their performance using theoretical analysis and real data.

Findings

Confidence intervals for $H_p$ are effective in estimating poverty proportions.

The methods perform well in large samples based on simulations.

Application to real data illustrates practical utility in poverty assessment.

Abstract

We examine a commonly used relative poverty measure called the headcount ratio ($H_p$), defined to be the proportion of incomes falling below the relative poverty line, which is defined to be a fraction $p$ of the median income. We do this by considering this concept for theoretical income populations, and its potential for determining actual changes following transfer of incomes from the wealthy to those whose incomes fall below the relative poverty line. In the process we derive and evaluate the performance of large sample confidence intervals for $H_p$. Finally, we illustrate the estimators on real income data sets.