Does Public Data Openness Reduce Boundary Pollution? Evidence from Interprovincial Neighboring Cities in China

Published: 30 June 2025| Version 1 | DOI: 10.17632/hry2njz8hy.1
Contributor:
Peiyu Li

Description

Description of the Five Datasets city_border.dta This panel dataset contains data on interprovincial neighboring cities in China from 2008 to 2021. It includes environmental indicators, socioeconomic variables, and public data openness measures used for the main empirical analysis of boundary pollution. city_all.dta This dataset covers all prefecture-level cities in China during the same period. It serves as a broader sample for robustness checks and additional analyses beyond the border cities. firm_border.dta Panel data of industrial firms located in the boundary regions, including firm-level performance, pollution emissions, and innovation indicators. It supports the study of firm behavior in response to public data openness and environmental policies. do.do A Stata DO file containing all code for data cleaning, variable construction, and econometric modeling. Running this script reproduces the empirical results presented in the paper. Replication_Package_Readme.pdf A documentation file explaining the contents of the replication package, data sources, processing steps, and instructions for reproducing the study results. It also includes contact information for inquiries.

Files

Steps to reproduce

Download all files from the replication package, including datasets (city_border.dta, city_all.dta, firm_border.dta) and the Stata DO file (do.do). Open Stata (version 15 or higher recommended) and set the working directory to the folder containing the downloaded files. Run the provided do.do script sequentially. The script performs data cleaning, variable construction, and executes all regression analyses as presented in the paper. Output files and results will be generated as specified in the script comments. Compare these results with those reported in the manuscript to verify replication. For any questions or issues, please refer to the Readme.pdf or contact the author.

Institutions

  • Shandong University

Categories

Regional Studies, Applied Economics

Licence