My KIPP Blog – Week 9-11
As mentioned in the previous blog post, the impact of digital inclusive finance on the urban-rural income gap in China is an issue that I would like to further investigate.
In order to investigate this issue, it is definitely necessary to read some relevant theories and literature. For example, Lewis first proposed the theory of binary economic structure that divides the economy of developing countries into urban and rural sectors in Economic Development with Unlimited Supplies of Labour, McKinnon’s theory of financial development in developing countries in Money and Capital in Economic Development , and Kuznets’ income gap hypothesis.
The main data I intend to use is the Digital Inclusive Finance Index compiled by Peking University. This set of indices includes the overall digital inclusive finance index, the breadth of coverage of digital finance, the depth of use of digital finance, and the degree of digitisation of inclusive finance. The usage depth index also includes indices for payments, credit, insurance, credit, investment, money funds and other business categories. The index spans the period 2011-2021 and covers 31 provinces, 337 cities above prefecture level and about 2,800 counties in Mainland of China. In addition, I also intend to collect various data to combine with the Digital Inclusion Index for analysis, such as urban-rural income ratio, government economic behaviour (regional fiscal expenditure/GDP), urbanisation rate (urban population/total population), etc.
Based on the above data, probably I will use multiple regression analysis to observe the impact of digital inclusive finance on the urban-rural income gap. For example, I will use the urban-rural income ratio as the Explained Variable, the total digital inclusion index and the three secondary indices (breadth of coverage, depth of use and degree of digitisation) as the Explanatory Variables, and government economic behaviour and urbanization rate as the Control Variables.
Recent comments