Modified Human Development Index using Data Envelopment Analysis Approach

Abstract

: Composite Indicator is considered the mathematical aggregation which has wide usage for monitoring performances, conducting benchmarks, analyzing policies, and communicating publicly. Human Development Index (HDI) is the most popular index which measures human development through average achievement in its main dimensions: Health status, education status, and living standard but it is faced with several critiques, positive and negative. Moreover, HDI was tested to have a positive and significant correlation with natural resource abundance. Therefore, based on Mathematical Programming approaches, previously tested for Composite Indicators’ development, this research proposes a new calculated HDI using a Data Envelopment Analysis approach based on the Goal Programming model; including missing values’ estimation. This new proposed HDI was validated through Sensitivity Analysis of Normalization and Weighting methods; in addition to Wilcoxon Signed Rank Test. The first test shows a positive high correlation between the proposed HDIs and the United Nations HDI. Those tests ensure that HDI rankings are highly correlated and that they are unchanged given the different normalization and weighting techniques. Moreover, they reflect that the paired sample mean is not the same. This highlights the advantageous property of the proposed HDI; preserving both the advantages of Goal Programming and Data Envelopment Analysis approaches, in addition to others.