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Table 4.
Variable setting in 2SLS.
Variable Name
Variable Symbol
Dependent variable
Z
Z-Score
Exogenous variables
Urban innovation index
Innovation
Endogenous variables
Fintech level
Fintech 1
Bank-level control variables
Size, DAR, CAR, Netprf, CIR, NIRR, SAR
City-level control variables
PGDP, FinDev
Macro-level control variables
M2
Instrumental variable
Urban innovation index
Innovation
Source: own calculations.
The regression results of the instrumental variables are shown in Table
5
. Column (1)
in the table shows, the correlation coefficient between exogenous instrumental variables
urban innovation index (Innovation) and the explained variable bank risk-taking (Z-Score)
does not pass the significance test. This shows that there is no correlation between the
two, and the instrumental variable of urban Innovation index is exogenous. Column (2)
in the table shows the regression results of the first stage. The results state that there is
a significant correlation between Urban Innovation Index and Fintech 1, the degree of
Fintech development it replaces. Therefore, this fully shows that the instrumental variables
satisfy both exogenous and correlation requirements. Column (3) in the table replaces
the original Fintech 1 with the fitted values Fintech 1_hat of all regression results in the
first stage, and performs regression with the explained variable Z-Score. The results show
that the correlation coefficient between Fintech development degree and bank risk taking
is
−
0.0169861, which is significantly correlated at the level of 5%. After considering the
possible endogenous problems between Fintech and bank risk, the development of Fintech
can significantly curb banks’ risk-taking, which is consistent with the previous results.
Table 5.
Regression results of two-stage least square method (2SLS).
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