Index generation for good governance via multiplicative data envelopment analysis

While it is widely suggested that good governance is a prerequisite for development, many studies in recent years have called into question the calculation of World Governance Indicators (WGI) and the alleged relationship between good governance and development. From this point of view, this study aims to calculate a composite index to specify the level of good governance in 169 countries and examine the relationship between the good governance and human development. The study employs Emrouznejad and Cabanda (2010) output-oriented log-transformed multiplicative data envelopment analysis (MNCP) model, which is suggested to offer superior performance in composite index construction. This model outperforms standard DEA models in terms of its mathematical structure, providing solutions to criticisms regarding the calculation of the good governance index. The results indicate a correlation between the MNCP Model results and the HDI in countries of the higher-income group while showing no correlation between these variables in countries of other income groups. The overall findings reveal that, despite the widely accepted claims, good governance is not a necessary prerequisite for development in low, lower-middle, and upper-middle-income countries, while it is already an existing phenomenon in high-income countries.