Probabilistic Projections of Country‐Level Trajectories Toward UN SDG Indicator 4.1.1: Attaining Minimum Proficiency in Reading and Mathematics

ABSTRACT As of this writing, there are 4 years remaining for countries to reach their Sustainable Development Goals deadline of 2030 as agreed to by the member countries of the United Nations. Countries are, therefore, naturally interested in projections of progress toward these goals. A variety of statistical measures have been used to report on country‐level progress toward the goals, but they have not utilized methodologies explicitly designed to obtain optimally predictive measures of rate of change as the foundation for projecting trends. The focus of this paper is to provide Bayesian probabilistic projections of country‐level trajectories toward the SDG goal of attaining minimum proficiency in reading and mathematics, with particular emphasis on competencies among lower secondary school children. Using data from the OECD, the World Bank, the UNDP, and UNESCO, we employ a novel combination of Bayesian hierarchical growth curve modeling and Bayesian model averaging to obtain optimal estimates of the rate of change in minimum proficiency percentages and then use those estimates to develop overall and country‐specific probabilistic projections. Four case study countries are also presented to show how the methods can be used for individual country projections.