Abstract
This article mainly studies the national minority areas. First, it systematically sorts out the financial exclusion theory and the financial development literature of the minority areas, and combines the economic and financial data at the provincial and county levels to empirically analyze the financial exclusion in the minority areas. The status quo, the influencing factors and the consequences of this, and some suggestions for managing financial exclusion in ethnic areas.
Highlights
The study of financial exclusion began in the early 1990s (Leyshon & Thrift, 1993, 1994, 1995)
From the perspective of regional distribution, ethnic regions account for 58.91% of the country’s land area, and only have 10.23% of the country’s banking outlets, with an average of 0.0026 outlets per square kilometer, while the national average is 0.0146, which is much higher than in ethnic areas, it can be seen that the distribution of outlets in ethnic areas is too small and the density is too low
From the perspective of population distribution, ethnic regions have 14.26% of the country’s population and 10.23% of the country’s banking outlets, with an average of 0.76 per 10,000 people, which is lower than the national level of 1.01, but the gap is not large. (Note: The area and population data of each province comes from the National Bureau of Statistics, as of the end of 2016)
Summary
The study of financial exclusion began in the early 1990s (Leyshon & Thrift, 1993, 1994, 1995). The number of employees per 10,000 people in Inner Mongolia and Ningxia provinces is much higher than the national level This shows that there is an imbalance in the geographical distribution of employees in financial institutions in ethnic areas, and there are large differences between regions. 2.3 Deposits and loans of financial institutions in ethnic areas From the 2016 GDP statistics of all provinces and cities in the country released by the National Bureau of Statistics, as of the end of 2016, the balance of deposits and loans in ethnic areas accounted for 8.46% and 11.14% of the country's total. Yunnan still has the highest loan balance, reaching 2.35 trillion yuan, and the least is Tibet, only 0.30 trillion yuan, which is 7.83 times the difference, a huge gap This shows that the development of deposits and loans in ethnic areas is extremely uneven, and the gap is obvious. The weighted average method is used to comprehensively measure the financial exclusion index, and the weight calculation method is carried out in the following steps:
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