Forecasting Future Development under the Interactions among Sustainable Development Goals

Yuqing Xu, Yu Chen (), Min Cao, Lijiao Chang, Yuying Bai, Yue Li and Yaqi Guo
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Yuqing Xu: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China
Yu Chen: International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
Min Cao: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China
Lijiao Chang: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China
Yuying Bai: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China
Yue Li: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China
Yaqi Guo: Key Laboratory of Virtual Geographic Environment, Ministry of Education of PRC, Nanjing Normal University, Nanjing 210023, China

Sustainability, 2023, vol. 15, issue 22, 1-11

Abstract: Simulating the performance of the Sustainable Development Goals (SDGs) provides guidance to policymakers for faster achievement of the 2030 Agenda. However, current modeling and forecasting methods are not well thought out in terms of interactions between the SDGs. This study developed an iteration forecasting model considering the interactions of SDGs and simulated the SDGs’ progress from 2021 to 2030 for 41 cities in the Yangtze River Delta under various sustainable development paths. The results indicated that the cities with the highest levels of sustainable development in the Yangtze River Delta would only achieve half of the goals by 2030 if they continued on their past paths. Learning from other cities resulted in a more significant improvement in the achievement of SDGs. Furthermore, the higher the development cost, the better the achievement of the goals. Compared to the other goals, SDG11 and SDG13 required higher development costs to be achieved. We optimized the development paths by taking development costs and goal attainment into account. The results showed that cities with high levels of economic development are more likely than cities with low levels of economic development to achieve SDG8 and SDG9 by 2030, while the opposite is true for SDG15.

Keywords: SDG forecast; development path optimization; synergies and trade-offs; spatial spillover effects; Yangtze River Delta (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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