Abstract
Based on the annual corporate data of Shanghai and Shenzhen A-shares from 2011 to 2018 and the Digital Financial Inclusion Index of Peking University, this paper empirically examines the impact of China's digital finance development on the investment efficiency of enterprises. The research finds that: the development of digital finance reduces the investment efficiency of enterprises. This may be due to the development of digital finance leading to the financialization of enterprises. This paper puts forward how to guide digital finance in a good direction to influence the investment efficiency of enterprises.
Highlights
Since the advent of the 4G, digital finance has been developing with each passing day
According to the theory presented by Huang Yiping in 2018 China's digital finance can be traced back to the launch of Alipay’s account system in 2004, the industry generally regards the opening of Yu EBAO in 2013 as the first year of China's digital finance development
As enterprises are in different characteristic states, the above tests are difficult to avoid heterogeneity bias, and the impact of digital finance development on enterprise investment efficiency may be different
Summary
Since the advent of the 4G, digital finance has been developing with each passing day. Since 2006, the Chinese government has vigorously promoted the development of inclusive finance, taken measures such as the establishment of microfinance companies, the establishment of "inclusive finance Business department" in financial institutions, and in rural areas to carry out "two rights" mortgage pilot measures. It often gets half the result with twice the effort and lacks commercial sustainability. Enterprises in the improvement of profitability, and to maintain good credit In this way, it can increase the business quota but more importantly, realize more rapid and convenient successful financing under the development of digital finance. The following parts of this paper are organized as follows: Part 2 is research design, introducing data source, model specification, and estimation methods; Part 3 is analysis, descriptive statistics, benchmark regression; Part 4 is heterogeneity analysis; Part 5 is the conclusion
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