Asymptotic and bootstrap inference for inequality and poverty measures

@inproceedings{Davidson2004AsymptoticAB,
  title={Asymptotic and bootstrap inference for inequality and poverty measures},
  author={Russell Davidson and Emmanuel Flachaire},
  year={2004}
}
A random sample drawn from a population would appear to offer an ideal opportunity to use the bootstrap in order to perform accurate inference, since the observations of the sample are IID. In this paper, Monte Carlo results suggest that bootstrapping a commonly used index of inequality leads to inference that is not accurate even in very large samples. Bootstrapping a poverty measure, on the other hand, gives accurate inference in small samples. We investigate the reasons for the poor… CONTINUE READING

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