Complexity Economics and Sustainable Development: A Computational Framework for Policy Priority Inference
Three features make sustainable development very challenging to governments and analysts: multidimensionality, interconnectedness, and complexity. It is multidimensional because one needs to consider a wide variety of policy issues. It is interconnected because these many dimensions are interdependent. It is complex because the macro-level development data used in performance evaluation emerges from micro-level interventions, so one needs to consider vertical causal channels. Despite the growing availability of government spending data across various policy dimensions, approaches developed in econometrics and machine learning offer limited solutions because expenditure data and development indicators are not big enough or sufficiently detailed to meet the technical requirements of these methods.This book develops a novel computational approach to handle these challenging features. It builds on a well-founded socioeconomic theory and provides a parsimonious modelling framework to explain the link between public expenditure and development. It walks the reader through a detailed construction of the analytic toolkit and, then, acquaints them with a diverse set of empirical applications using publicly available data.