Economics Letters 250, pp. 112293.
ISSN/ISBN: Not available at this time. DOI: 10.1016/j.econlet.2025.112293
Abstract: The reliability of China's GDP data has been a significant topic in economic research. However, few studies have estimated the strategies taken to improve data quality. This study examines the impact of the Enterprises’ Direct Report Reform on economic data quality in China. Using a novel statistical method based on Benford's Law to detect firm-level data manipulation, we employ a staggered difference-in-differences specification and find that the reform has reduced the degree of manipulation by approximately 15 % of a standard deviation, with this reduction primarily attributable to improvements in the data quality of private enterprises. Our analysis indicates that the reform is effective by engaging enterprises in data reporting, rather than simply imposing stricter monitoring within governments.
Bibtex:
@article{,
title = {How can governments mitigate statistical data manipulation? Evidence from China's enterprises’ direct report reform},
journal = {Economics Letters},
volume = {250},
pages = {112293},
year = {2025},
issn = {0165-1765},
doi = {https://doi.org/10.1016/j.econlet.2025.112293},
url = {https://www.sciencedirect.com/science/article/pii/S0165176525001302},
author = {Jingyu Zhang and Zhongyu Wang and Xiao Tang},
}
Reference Type: Journal Article
Subject Area(s): Economics