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<p>Improving infrastructure investment efficiency is critical to address global investment gap and resource constraints, thereby promoting sustainable economic development. This study aims to explore the peer effects in local governments’ new infrastructure investment (NII) decision-making and uncovers the underlying mechanisms driving these effects. Utilizing panel data from 258 Chinese prefecture-level cities (2012–2022), this study employs a spatial econometric model to examine how intergovernmental spatial interactions shape the NII decision-making. Furthermore, the impacts of learning mechanism, competition mechanism, and exogenous shocks on the peer effects are explored. The findings show that: (1) Significant peer effects exist in NII decision-making of local governments across all seven spatial correlation contexts, with transportation networks and industrial linkages exerting the strongest influence. (2) Cities exhibit asymmetric imitation patterns based on their level of economic development: underdeveloped cities exhibit stronger imitation of developed counterparts, which primarily serve as benchmarks. This behaviour reflects rational adaptation strategies under uncertainty, as local governments seek to minimise risks and leverage experiential learning. (3) Learning mechanisms reinforce irrational imitation through accumulated experience, leading to self-reinforcing path dependence. Competition mechanisms—especially industrial competition in central China—are major drivers, complemented by fiscal and talent competition in central and western regions. Moreover, national policy pilots (e.g. National Big Data Comprehensive Pilot Zones) serve as pivotal reference points, accelerating policy convergence among local governments. This study offers a comprehensive understanding of the existence, asymmetry, and multidimensional drivers of peer effects in NII decision-making. It provides both theoretical and policy insights for optimizing regional infrastructure coordination and promoting sustainable inclusive development.</p>

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Peer effects in local government decision-making on new infrastructure investment: evidence from Chinese 258 cities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月9日

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  • Tengfei Huo,
  • Shixiang Liu,
  • Youfeng Qiao,
  • Yujie Zhang,
  • Bingsheng Liu

摘要

Improving infrastructure investment efficiency is critical to address global investment gap and resource constraints, thereby promoting sustainable economic development. This study aims to explore the peer effects in local governments’ new infrastructure investment (NII) decision-making and uncovers the underlying mechanisms driving these effects. Utilizing panel data from 258 Chinese prefecture-level cities (2012–2022), this study employs a spatial econometric model to examine how intergovernmental spatial interactions shape the NII decision-making. Furthermore, the impacts of learning mechanism, competition mechanism, and exogenous shocks on the peer effects are explored. The findings show that: (1) Significant peer effects exist in NII decision-making of local governments across all seven spatial correlation contexts, with transportation networks and industrial linkages exerting the strongest influence. (2) Cities exhibit asymmetric imitation patterns based on their level of economic development: underdeveloped cities exhibit stronger imitation of developed counterparts, which primarily serve as benchmarks. This behaviour reflects rational adaptation strategies under uncertainty, as local governments seek to minimise risks and leverage experiential learning. (3) Learning mechanisms reinforce irrational imitation through accumulated experience, leading to self-reinforcing path dependence. Competition mechanisms—especially industrial competition in central China—are major drivers, complemented by fiscal and talent competition in central and western regions. Moreover, national policy pilots (e.g. National Big Data Comprehensive Pilot Zones) serve as pivotal reference points, accelerating policy convergence among local governments. This study offers a comprehensive understanding of the existence, asymmetry, and multidimensional drivers of peer effects in NII decision-making. It provides both theoretical and policy insights for optimizing regional infrastructure coordination and promoting sustainable inclusive development.