A Novel Two-Phase Approach to Computing a Regional Social Progress Index

In recent decades, concerns have emerged regarding the fact that standard macroeconomic statistics (such as gross domestic product) do not provide a sufficiently detailed and accurate picture of societal progress and well-being and of people’s true quality of life. This has further translated into concerns regarding the design of related public policies and whether these actually have the intended impact in practice. One of the first steps in bridging the gap between well-being metrics and policy intervention is the development of improved well-being measures. The calculation of a regional Social Progress Index (SPI) has been on the policymakers’ agenda for quite some time, as it is used to assist in the proposal of strategies that would create the conditions for all individuals in a society to reach their full potential, enhancing and sustaining the quality of their lives, while reducing regional inequalities. In this manuscript, we show a novel way to calculate a regional SPI under a two-phase approach. In the first phase, we aggregate the item-level information into subfactor-level indices and the subfactor-level indices into a factor-level index using an objective general index (OGI); in the second phase, we use the factor-level indices to obtain the regional SPI through a pure data envelopment analysis (DEA) approach. We further apply the method developed to analyse a single period of social progress in Peru. The manuscript is a contribution to the practical measurement of social progress.