In the context of the Sustainable Development Goals there is great interest in understanding and developing better measures to quantify and assess governance. This report aims to contribute by providing a clear assessment of the validity and reliability of indicators in two particular dimensions of governance: public financial management (PFM) and corruption.
Governance is a multidimensional phenomenon and there is no convergence regarding its conceptual understanding. The most widely used approach to governance measurement involves composite indices. This report therefore reviews indicator-based approaches to quantifying governance, and discusses how to construct composite/aggregate indicators and assess their quality.
The choice of these two dimensions of governance allowed a holistic analysis with comparison of both objective and subjective indicators. Additionally, both PFM and corruption are highly salient governance dimensions with strong policy relevance. Practical considerations highlighted the importance of using good data to carry the assessment: for PFM, datasets were chosen because of their applicability within the development context; for corruption, the datasets were chosen because they allowed different levels of indicator aggregation to be explored. Multivariate analysis was then used to assess the validity and reliability of the relevant indicators, with exploratory and confirmatory factor analysis to investigate whether the indicators designed to measure particular concepts were indeed consistent with the assumed structure.
The analysis suggests a meaningful way to further explore the appropriateness of governance indicators. For PFM measurement this would be the use of the OBS (Open Budget Survey): valid, reliable and particularly suited for the monitoring of underdeveloped PFM systems. For corruption, the use of the GCB (Global Corruption Barometer) in early stages of project formulation will be beneficial. Additionally, aggregate measures of corruption can be used to provide contextual background when evaluating project impact. Finally, within each indicator set, the dropping problematic or redundant indicators is recommend, merging indicators that line up with a congruent pattern of dimensionality, and classifying indicators that appear to be tautological.
Muriithi, K.; Jimenez, M.; Jannin, N.; Sajid, N.; Singh, S.; Sharma, S. Quantifying Governance: an indicator-based approach. LSE/DFID, London, UK (2015) 112 pp.