Samaa Hazem Hosny

This paper builds on the extensive literature of the benefit-of-the-doubt (BoD) methodology to set weights for composite indicators (CIs). The proposed methodology, meta-goal programming benefit of the doubt (MGP-BoD), proved to overcome some of the BoD shortcomings and enhance its performance. MGP-BoD belongs to the family of common-weights BoD models. It comprises of two sets of goals and two meta-goals. Among other merits, results prove two additional benefits of the MGP-BoD over older BoD. First, it enhances BoD discriminating power by eliminating all ties in CI values and, hence, country ranks. This high discriminating power is achieved in only one totally endogenous step. Second, MGP-BoD weights add up to one. This makes weights more insightful, interpretable, comparable to weights from other weighting systems, and easier to interpret compared to BoD. These additional merits favor MGP-BoD over previous weighting methods. In the meantime, the proposed method preserves a significantly high correlation with previous methods results as shown a set of Pearson and Spearman correlation tests to compare it to various previous methodologies. To validate the proposed methodology, it has been thoroughly tested using sensitivity and classification analyses. All tests are found highly significant. Nevertheless, the method has its own limitations that suggest future research points. Finally, the paper offers a new human development indicator (HDI) using 2012 data using MGP-BoD. The proposed HDI offers an alternative to the currently used equal-weights HDI that offers distinguishable country ranks and more policy-guiding weights. The highest weights are assigned to education variables.