Measuring Social Performance: A Principal Component Analysis-Based Social Performance Index for Microfinance Institutions in Pakistan

Abstract

The evaluation of microfinance institutions' social and financial performance has been a central focus of research. While multidimensional indexes effectively assess financial performance, social performance remains challenging due to its complexity and reliance on isolated indicators. This study addresses the gap by constructing a multidimensional social performance index using data from the MIX dataset, encompassing 10 indicators for 49 Pakistani MFIs. Principal Component Analysis was employed on two datasets: 254 observations on four variables for 49 MFIs and 78 observations on five variables for 36 MFIs. The four-variable, four-factor solution explained 100% of the data variance and yielded consistent scores, highlighting its robustness. Rankings were sensitive to variable and component selection, underscoring MFIs’ heterogeneity and the uniqueness of social performance dimensions. Subgroup analysis revealed a growing recognition of Islamic MFIs and superior performance by Microfinance Banks and Companies. These findings advocate for adopting multidimensional measures to better capture MFIs' social performance.