Replication Data for: High-Speed Rail, Factor Mobility, and Multidimensional Urban–Rural Integration: Evidence from the Chengdu–Chongqing City Cluster in China

Description

This dataset contains the raw data used in the paper "High-Speed Rail, Factor Mobility, and Multidimensional Urban–Rural Integration: Evidence from the Chengdu–Chongqing City Cluster in China". The dataset includes county-level data for the Chengdu–Chongqing city cluster from 2007 to 2023. Users can process the raw data following the steps described in "Steps to reproduce" to construct the final analysis dataset, which includes: - The multidimensional Urban–Rural Integration (URI) index and its three dimensions (economic, social, and spatial); - High-speed rail (HSR) opening variable; - Mediating variables capturing factor mobility; - Moderating variable (Policy Support for URI); - Control variables. All empirical results reported in the paper (baseline regressions, mediation analysis, heterogeneity analysis, and moderation tests) can be replicated after processing the data according to the provided steps. Corresponding author: Shan Shen (Shan.S@cqu.edu.cn), Chongqing University.

Steps to reproduce

Steps to reproduce: 1. Data sources: - County-level socioeconomic variables: Provincial and municipal statistical yearbooks, statistical communiqués, and local government reports (2007–2023). - High-speed rail (HSR) opening dates: Official China Railway website[](https://www.12306.cn/). - Nighttime light data: Resource and Environment Science and Data Center, Chinese Academy of Sciences[](http://www.resdc.cn/). 2. Sample construction: - Start with 156 counties in the Chengdu–Chongqing city cluster. - Exclude counties with severe missing data, those that were 100% urbanized in 2007, or experienced administrative boundary changes during 2007–2023. - Final sample: 142 counties, forming a balanced panel with 2,414 observations. 3. Data processing steps: - Impute missing values using linear interpolation. - Standardize all continuous variables using the Min-Max method (0–1 scale). - Construct the multidimensional Urban–Rural Integration (URI) index and its three sub-dimensions (economic, social, spatial) using the Multidimensional Development Index (MDI) approach. - Construct mediating variables (labor mobility, capital mobility, technology mobility, commodity circulation, land mobility). - Construct the moderating variable (Policy Support for URI, PSURI) and all control variables. After completing the above data processing steps, the final dataset can be used to replicate all empirical results in the paper.

Institutions

• Chongqing University

  Chongqing, Chongqing
• Jinan University

  Guangdong, Guangzhou
• Singapore University of Social Sciences

  SG.01, Singapore

Categories

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