Interval Based Composite Indicators

Abstract

Composite indicators are increasingly important in country comparisons and in policy making. At the same time, the robustness of the results obtained and in particular of the rankings and the conclusions obtained from the analysis it is usually accepted with doubts. In this sense our proposal is to use interval data in order to measure the uncertainty related to the different composite indicators based on the different assumptions used as input. In this sense where composite indicators can be considered as models, for this reason it could be necessary to assess the uncertainties related to the different choices in the construction. The uncertainty can be represented by the interval data. The intervals keep the information related to the initial value of the composite indicator, but at the same time give information on the range of the results.

The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator

“…So, the idea is to consider some robustness checks and sensitivity analysis by considering different assumptions to evaluate its robustness. This work aims to internalize this robustness by considering the interval of possible results, which can be obtained by varying the composite indicator's assumptions (see [36] [37] [38] and [39]).…”