Abstract

With ongoing improvements in infrastructure, extensive data consistently demonstrate that the development of rural power infrastructure plays a significant role in driving agricultural growth. However, the existing research has only scratched the surface in comprehensively assessing the multifaceted impact of different aspects of power infrastructure, primarily owing to the narrow scope of performance indicators. To address this gap, this study employs principal component analysis (PCA) to develop panel threshold models and data-driven predictive models based on an indicator framework. Using Fujian Province as a case study, this research systematically analyzes the impact of rural power infrastructure development on agriculture across four stages, i.e., generation, transmission, distribution, and consumption. The findings highlight the crucial role of the consumption stage in nurturing agricultural growth through rural power infrastructure construction. Notably, the investigation reveals that residential electricity consumption and the number of service users have a significantly positive impact on rural agricultural development, while the influence of agricultural electricity consumption remains comparatively limited when compared with the secondary and tertiary sectors. Furthermore, the data-driven predictive model introduced in this study provides a more precise forecast of future trends in rural agricultural development. This research underscores the critical importance of conducting in-depth explorations to uncover the actual role of power infrastructure development in the context of rural agriculture. With regards to rural power infrastructure construction, it is advisable to invest prudently, formulate relevant policies, with a specific focus on the consumption stage, and implement targeted technology upgrades to enhance productivity and ultimately promote agricultural development.

Full Text
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