ABSTRACT
Drawing on a unique dataset of 520 estimates from 32 studies, we analyze the effect of financial development on economic growth in China quantitatively using a meta-regression analysis. We find that the effect of financial development on economic growth, corrected for publication biases, is positive and statistically significant and that banking-sector development plays a dominant role in the economic growth of China. Moreover, there is weak evidence of the existence of Type-I publication bias and strong evidence of the existence of Type-II publication bias. We also find that sample size, the language of the studies, the empirical model, and the use of data from different regions are the sources of the heterogeneity of the estimates.
Supplemental data
Supplemental data for this article can be accessed online at https://doi.org/10.1080/1540496X.2022.2136940
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Notes
1. The Big Four state-owned banks are the Industrial & Commercial Bank of China, the China Construction Bank Corporation, the Agricultural Bank of China, and Bank of China.
2. Data source: Chinese Statistical Yearbooks.
3. The list of the 10 Chinese economics journals includes Social Sciences in China (中国社会科学), Management World (管理世界), Economic Research Journal (经济研究), China Economic Quarterly (经济学季刊), The Journal of World Economy (世界经济), Journal of Financial Research (金融研究), China Industrial Economics (中国工业经济), Journal of Quantitative & Technical Economics (数量经济技术经济研究), Chinese Rural Economy (中国农村经济), and Economic Perspectives (经济学动态).
4. Among the 184 English studies and 40 Chinese studies that were obtained from the primary search, only 32 papers met the three criteria. The earliest and the latest articles are Tan (Citation1999) and Zhuang et al. (Citation2019), respectively.
5. In some research, authors average data over time horizons, in order to strip out the cyclical effect of the data.