Complexity Economics and Sustainable Development A Computational Framework for Policy Priority Inference
Complexity Economics and Sustainable Development: A Computational Framework for Policy Priority Inference by Omar A. Guerrero, published by Cambridge University Press on January 25, 2024, spans 420 pages and is presented in English. This book addresses the Sustainable Development Goals established by the UN, focusing on critical issues such as poverty, education, economic growth, and climate. It introduces a novel framework that utilizes complexity science, agent-based modeling, and computational social science to tackle the limitations of traditional statistical approaches in analyzing development data.
Readers will find a comprehensive exploration of how to quantify the relationship between public expenditure and development while considering complex interdependencies and governance structures. The book includes extensive data on global development indicators and provides open-source code, making it a valuable resource for those interested in empirical applications and policy implications. By building on interdisciplinary socioeconomic theory, this work aims to enhance understanding of development challenges and offer insights relevant to a broad audience in the fields of business, economics, and development.
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The Sustainable Development Goals are global objectives set by the UN. They cover fundamental issues in development such as poverty, education, economic growth, and climate. Despite growing data across policy dimensions, popular statistical approaches offer limited solutions as these datasets are not big or detailed enough to meet their technical requirements. Complexity Economics and Sustainable Development provides a novel framework to handle these challenging features, suggesting that complexity science, agent-based modelling, and computational social science can overcome these limitations. Building on interdisciplinary socioeconomic theory, it provides a new framework to quantify the link between public expenditure and development while accounting for complex interdependencies and public governance. Accompanied by comprehensive data of worldwide development indicators and open-source code, it provides a detailed construction of the analytic toolkit, familiarising readers with a diverse set of empirical applications and drawing policy implications that are insightful to a diverse readership.
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