Robustness properties of poverty indices

Drawing on recent work concerning the statistical robustness of inequality statistics we examine the sensitivity of poverty indices to data contamination using the concept of the influence function. We show that poverty and inequality indices have fundamentally different robustness properties, and demonstrate that an imporrtant commonly used subclass of poverty measures will be robust under data conta m ination. We investigate both the case where the poverty line is exogenenously fixed and where it must be estimated from the data.