Statistical performance indicators and index—a new tool to measure country statistical capacity

Abstract

Strong statistical capacity is a prerequisite for producing reliable statistics that helps monitor a country’s governance and economic performance. This is particularly relevant for a large number of poorer countries, which have weaker statistical capacity but have to rely more on these statistics for various objectives such as monitoring poverty reduction or reporting to international donors. We present the Statistical Performance Indicators and Index (SPI) as the World Bank’s new official tool to measure country statistical capacity. The SPI is conceptually motivated, builds on a mathematical foundation, and significantly expands the number of indicators and the number of covered countries compared to its predecessor. The new index has a strong correlation with other common development indicators such as GDP per capita, governance, human capital, poverty, and inequality. It can also accommodate future improvements as the global data landscape evolves.

Reviewing Assessment Tools for Measuring Country Statistical Capacity

“…The SCI, however, has several key limitations, including an outdated framework, a focus on poorer countries only, and a lack of underlying conceptual and mathematical principles. The SPI recently replaces and offers several advantages over the SCI on both the conceptual and empirical fronts (Dang et al, 2023). In particular, the SPI explicitly offers standard desiderata for a statistical index (i.e., simple, coherent, motivated, rigorous, implementable, replicable, incentive consistent).…”

“…We provide the latest update for the SPI country scores in 2022 in Appendix A, Table S4, with further result breakdowns by income and region in Figures S1 and S2. Further comparison between the SPI and the SCI is provided in Dang et al (2023).…”

“…Notably, of the other assessment tools considered in this study (including the SCI), only the SPI offers an explicit discussion of its conceptual and mathematical foundations in peer-reviewed academic publications (Cameron et al, 2021;Lokshin, 2022;Dang et al, 2023). Consequently, we employ the SPI's five pillars as a reference point in the subsequent comparison of the different tools.…”

“…In summary, a successful statistical system offers highly valued and well-used statistical services, generates high quality statistical indicators that can also track progress for the SDGs, draws on all types of data sources relevant to the indicators that are to be produced, develops both hard infrastructure (including legislation, governance, standards) and soft infrastructure (including skills, partnerships), and has the financial resources to deliver. Figure A.1 (Dang et al, 2023) offers an alternative visual description of the beneficial interactions of the different data pillars, which reinforce each other through stakeholders' partnership, joint accountability, better capacity, and meeting user needs. Improvements in performance can be represented as a virtuous data cycle that can become self-sustaining.…”

“…The Statistical Capacity Index (SCI) was a tool developed by the World Bank in 2004 to assess global improvements in country statistical capacity (World Bank, 2020). Most recently, it was replaced by the Statistical Performance Indicators and Index (SPI), which offers a clearer conceptual framework and broader country coverage (Dang et al, 2023).…”