Based on the intermediation effect test within the bank.
Note: ***, ** and * mean significant at the level of 1%, 5% and 10%, respectively. Source: own calculations. Software: Stata.
Risks
2021
,
9
, 99
21 of 27
7.2.2. Based on the Intermediary Effect Test Outside the Bank
In this paper, we use the external market competition intensity (HHI) and residents’
willingness to save (PSaving) as the intermediate variables to test the transmission chan-
nels. For the measurement of bank competition intensity, the commonly used Herfindahl-
Hirschman index (HHI) is selected as the proxy variable, and the market share is calculated
by the number of branches of each bank. For households’ willingness to save, regional
per capital saving (PSaving) is selected as the proxy variable. Table
14
shows the test
results of the mediation effect model. The mediating variable HHI was not included in
column (1).The results showed that the total effect of Fintech 1 on z-score is
−
0.0141, which
is significant at the 1% level. Column (2) shows that the effect of Fintech 1 on HHI is
−
0.0182, and it is significant at the level of 1%. By comparing the coefficient size of the
core explanatory variable Fintech 1 in columns (1) and (3), the regression coefficient of
Fintech 1 increased after the mediation variable was included. This means Fintech further
controls banking risks by strengthening competitive channels, which is in line with the
view of ‘competitive vulnerability theory’. Similarly, items (4), (5), and (6) are listed as the
regression results of the per capital savings (PSaving), and the regression coefficient of Fin-
tech 1 after inclusion is significantly higher than before. This illustrate that Fintech boosts
households’ willingness to save and causes bank deposits to move, further increasing bank
risks. Therefore, the research results of this paper support hypothesis 3.
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