Impact of digital economy on innovation and entrepreneurship: Evidence from China

Published: 9 March 2026| Version 1 | DOI: 10.17632/8vwvc3kp7h.1
Contributors:
Kai ZHAO, Yu Gao, Zeping Chen

Description

This file outlines the process for replicating the econometric analysis presented in the study: Impact of digital economy on innovation and entrepreneurship: Evidence from China. This folder contains the replication materials for the empirical analyses presented in the paper. It includes the dataset and Stata code used to reproduce the main results. The do-file contains detailed comments explaining each step of the empirical procedure, which facilitates replication and understanding. If any issues arise during replication, please ensure that all dependencies and packages are properly installed. For any questions regarding the code or data, please contact the corresponding author.

Files

Steps to reproduce

Stata 18 was used for the empirical analysis. The code should be compatible with Stata 15.1 or later versions. The code was tested on a standard desktop computer with Windows OS. The program requires at least 2GB of memory. The expected running time to execute the complete empirical analysis is approximately 20-25 minutes. Required Stata Packages: reghdfe - for high-dimensional fixed effects regressions. ftools - required by reghdfe. estout - for exporting regression results. xthreg2 - for unbalanced panel threshold effect test. Before running any of the replication do-files: Ensure all required packages listed above are installed in Stata. Verify the data and code are in the same working directory.

Institutions

Categories

Innovation, Entrepreneurship, Digital Economy

Funders

  • Shandong Provincial Natural Science Foundation
    Grant ID: ZR2023MG075
  • Shandong Provincial Natural Science Foundation
    Grant ID: ZR2024QE171
  • Shandong Province Youth Innovation and Technology Support Program for Higher Education Institutions
    Grant ID: 2023KJ111
  • Qingdao Social Science Planning Research Program
    Grant ID: QDSKL2401067

Licence