The deep integration of the digital and real economies is a critical force reshaping the global economic landscape. At the same time, new high-quality productive forces that are distinguished by their high level of efficiency, quality, and technology mark a new phase in productivity evolution. Understanding the spatial interplay between these two phenomena is crucial for coordinated development. This study empirically investigates their bidirectional relationship and spatial spillover effects. With panel data from 30 provinces in China (2011–2022), we use the Generalized Spatial Three-Stage Least Squares (GS3SLS) approach to estimate a spatial simultaneous equations model. The results reveal a significant bidirectional positive correlation, with the promotional effect of digital–real integration on new quality productive forces being slightly stronger. However, we also identify significantly negative spatial spillover effects between them. These findings underscore the necessity of strengthening their interactive development, fostering interregional cooperation, and optimizing source allocation to alleviate adverse spillovers. This study systematically examines their spatial dynamics and proposes policy recommendations to foster the coordinated advancement of both digital–real integration and New Quality Productive Forces.

Based on panel data from 274 prefecture-level cities in China (2011–2022), this study employs a peer effects model to examine three questions: whether peer effects exist in sustainable rural development, what mechanisms underlie them, and which regions are imitated. It thereby offers a new perspective on the endogenous drivers of rural development. The main findings are as follows. Baseline regression results confirm a significant positive peer effect on rural sustainable development. This result remains robust after a series of tests addressing endogeneity and robustness, including the replacement of explanatory variables, data indentation, exclusion of provincial capitals, placebo tests, and instrumental variable estimation. Heterogeneity analysis reveals that central and western regions are more inclined to learn from other cities in the process of sustainable rural development, whereas the eastern region leans more toward innovation. After the Rural Revitalization Strategy was introduced in 2017, regions have actively explored new rural development models, leading to a decline in the peer effects coefficient compared to the pre-2017 period. Mechanism analysis indicates that both learning-based imitation and competitive imitation serve as channels for peer effects in rural sustainable development. A region’s own development experience does not suppress peer effects. Economically more developed regions are more likely to become imitation targets. Moreover, performance pressure on local officials and the degree of competition among prefecture-level cities strengthen the peer effects. After reclassifying peer groups based on economic structure and geographical location, results show that in the process of rural sustainable development, local governments primarily learn from other regions within the same province that share similar economic structures and are geographically proximate. Based on these findings, this paper proposes differentiated policy recommendations to support sustainable rural development.