Assessing the effectiveness of SDGs implementation in reducing intra-urban spatial inequality: A spatiotemporal heterogeneous modeling in China

Local governments have initiated independent policies to contribute to implementing the Sustainable Development Goals (SDGs). However, the spatiotemporally heterogeneous impacts of the implementation of SDGs (SDGI) on intra-urban development inequality have not been given sufficient attention. This study examines the spatiotemporally heterogeneous effects of locally implemented SDGI on intra-urban development inequality in China (SDG 10). Firstly, we utilize nighttime light (NTL) satellite data and the grid population data to estimate the intra-urban Gini coefficients as a proxy for intra-urban spatial development inequality. Then we employ natural language processing (NLP) technologies to assess the intensity of SDGI as implemented by local governments. Secondly, a System Generalized Method of Moments (GMM) model is applied, followed by the Geographically and Temporally Weighted Regression (GTWR) model, to evaluate the spatial and temporal heterogeneous effects of SDGI on urban inequality. Third, we employ the BP Neural Network approach to validate the analysis results. The GTWR model results show that the temporal variations in the narrowing effect of SDGI follow a U-shaped trend. The median (25 %, 75 %) estimations of the SDGI coefficients are −0.007(−0.004,0.005) in 2012, then reaching a peak value of −0.072 (−0.087, −0.061) by 2018, while decreased to be −0.026 (−0.042, −0.027) in 2022. Urbanization and infrastructure development, which served as control variables, were found to significantly reduce inequality, whereas foreign direct investment (FDI) and higher unemployment rates tended to exacerbate intra-urban spatial inequality. The performances of SDGI on reducing urban inequality have shown significant spatial heterogeneity. Cities with higher SDGI intensity demonstrated a higher narrowing effect on urban inequality in the southwest, maybe due to clean energy investments and ecological compensation programs. The narrowing effects from SDGI were limited in highly developed first-tier cities, cities experiencing population outflows, and cities with higher sustainable development costs. Cities with higher SDGI intensity and narrowing effects reached their peak year of reducing inequality 1–2 years earlier. These findings highlight the importance of an earlier SDGI in narrowing urban equality and provide policy implications for decision-makers to address intra- and inter-city inequality for a sustainable development future.