2011-2022 financial technology level of each province in the country (constructed according to Baidu index, including original data + processing code)
1. Time: 2011-2022
2. Scope: 31 provinces and cities
3. Indicators:
Province, year, financial technology, Internet finance, Fintech, artificial intelligence, big data, cloud computing, blockchain, biometrics, mobile payment, online payment, third-party payment, online loan, online loan, online loan, online bank, Electronic Banking, Internet Banking, Direct Banking, Jinke_1, Jinke_2, Jinke_3, Jinke_4, Jinke_5, Jinke_6, Jinke_7, Jinke_8, Permanent Residence population, lnpeople
4. Reference method:
This paper manually sorted out the Baidu search index of financial technology-related keywords in various provinces from 2011 to 2017, and aggregated them into a financial technology index to measure the development level of financial technology related to small and micro enterprise credit in each province.
The collation method is divided into the following steps: First, based on the credit business practice of commercial banks for small and micro enterprises, and referring to the research results of scholars Shen Yue and Guo Pin (2015) and Jagtiani and Lemieux (2017), combined with the data availability of Baidu search index , identified the main keywords related to the bank's small and micro enterprise credit business and related to financial technology.
5. Keywords:
Including basic technical perspectives such as "big data, cloud computing, artificial intelligence, blockchain, biometrics"; financial payment perspectives such as "online payment, mobile payment, third-party payment";
From the perspective of financial technology intermediary service models, such as "online loan, online financing, online financing, online small loan, online loan, online bank, online bank, electronic bank, online bank, open bank, Internet bank, direct selling bank";
The direct appellation angle of financial technology is "Internet finance, financial technology".
Secondly, collect the Baidu search index of the above-mentioned keywords, and summarize them from the perspectives of technology, capital payment, intermediary service mode and direct appellation.
In order to ensure a reasonable balance of the importance of each index, the entropy method was used to determine the weight, and finally multiple indexes were synthesized into a comprehensive index.
Finally, the comprehensive index is synthesized by the entropy method, and then divided by the resident population of each province to measure the level of financial technology development related to small and micro enterprise credit in each province.
https://download.csdn.net/download/m0_71334485/88291377
