Robustness Properties of Inequality Measures

Abstract

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Robust Value at Risk Prediction

“…We find that standard nonparametric bootstrap procedures for VaR computation have a very low breakdown point (BP), meaning that VaR forecasts can be heavily affected already by a few large observations, especially when longer forecast horizons of, for example, 10 days are considered. Using the robust GPD estimator in our approach, we are also able to develop a resampling procedure for VaR forecasting that controls for the instability generated by outlying observations in estimated GARCH residual distributions; see also Cowell and Victoria-Feser (1996).…”

Robust estimation of the Pareto tail index: a Monte Carlo analysis

“…Second, we multiply by 10 a fixed proportion (1, 2, 5 and 10 %) of randomly selected observations simulated from P(1, α). This corresponds to the "decimal point error"-a situation, when a person coding or cleaning the data inadvertently puts the decimal point in the wrong place and thus multiplies an observation by a factor of 10 (Cowell and Victoria-Feser 1996). We compare the performance of the estimators in two cases with respect to the ARE-setting it to 78 and 94 %.…”

“…To make matters worse, even small errors in estimation of the Pareto exponent can produce large errors in estimation of quantities based on estimates of the exponent such as extreme quantiles, upper-tail probabilities and mean excess functions (Brazauskas and Serfling 2000). Similarly, inequality measures computed for the data simulated from the Pareto model are largely affected by even small or moderate data contamination (Cowell and Victoria-Feser 1996).…”

A new multidimensional population health indicator for policy makers: absolute level, inequality and spatial clustering - an empirical application using global sub-national infant mortality data

“…Thus data quality would affect the analysis in our present study as outlying or erroneous subnational IMR's may thus have affected the calculated Theil measures. Future studies will need to further assess the sensitivity ("robustness") of this and other inequality measures to data distortions, especially in different parts of the distribution as this has been shown to be potentially important (Cowell and Victoria-Feser, 1996). The year which the supplemented data were available is listed below (mostly from [2000][2001][2002].…”