Author:
Hughes Barry B.,Irfan Mohammod T.,Solórzano José,Yang Vivian,Moyer Jonathan D.
Abstract
Analysis of progress toward the Sustainable Development Goals (SDGs) requires clear understanding of current conditions of SDG target variables and indicators for countries around the world. There is no depository for country-specific, up-to-date information on the 169 targets and 230 indicators across the 17 goals. In fact, data are scattered across hundreds of sources and are very frequently incomplete and incompatible. The International Futures (IFs) forecasting system includes integrated models that span the issue areas covered by the SDGs to facilitate analysis of alternative scenarios through the 2030 goal horizon and beyond. To initialize variables the IFs project created an algorithmic toolkit called the “preprocessor” that draws upon extensive datasets from many statistical sources, filling holes (using estimated relationships) and reconciling inconsistent data (via methods including use of accounting systems within and across the issue areas). The IFs preprocessor “nowcasts” values for 186 countries across more than 100 SDG-related indicators for a user-specified base-year. This manuscript documents the methodology of that nowcasting and provides examples of recent and current-year estimated values for variables across the SDGs.
Subject
Statistics, Probability and Uncertainty,Economics and Econometrics,Management Information Systems
Cited by
5 articles.
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