Explore the link between Financial Structures and Economic Growth

1 Variable Definition

The definitions, specific meanings and symbols of variables studied in this paper are shown in the following table.

Meaning of table x variables

category	symbol	meaning
Depth	GFDD.DI.02	Deposit money banks' assets to GDP (%)
Stability	GFDD.SI.01	Bank Z-score
Other Economic	GFDD.OE.01	Consumer price index (2010=100, December)
Access	GFDD.AI.03	Firms with a bank loan or line of credit (%)
Access	GFDD.AI.20	Credit card (% age 15+)
Access	GFDD.AI.23	Mobile phone used to pay bills (% age 15+)
Access	GFDD.AI.34	Investments financed by banks (%)
Access	GFDD.AI.35	Working capital financed by banks (%)
Access	GFDD.AM.04	Investments financed by equity or stock sales (%)

2 Descriptive Statistics of Variables

Table X Descriptive Statistics

Variable	Mean	Std.Dev.	Min	Max
gfdddi02	60.63444	43.98217	0.392568	257.224
gfddsi01	14.01161	9.067189	-0.451923	64.4264
gfddoe01	125.9714	152.6162	94.5781	4665.79
gfddai03	34.21103	17.61162	3.8	79.6
gfddai20	17.84324	20.16423	0	82.5848
gfddai23	4.326267	5.93272	0	37.1049
gfddai34	14.8875	8.954845	0.8	38.5
gfddai35	11.59926	6.279308	0.8	30.1
gfddam04	4.616667	3.429408	0	15.4

It can be seen from the above table that the standard deviation of the consumer price index is the largest among all variables, which indicates that the consumer price index of different banks has a great variation range, with a value of 152.6162.According to the dependent variable, deposit money banks' assets to GDP, the maximum value is 257.224, the minimum, 0.392568, the standard deviation, 43.98217, and the average, 60.63444. With respect to the variable Bank Z-score, its maximum value is 64.4264, the minimum, -0.451923, the standard deviation, 9.067189, and the average, 14.01161.

3 Correlation analysis of variables

In order to study the factors that affect the performance of banks, the variables are selected from access, depth, efficiency, other, other economic and stability. Before the formal regression analysis, the correlation analysis was carried out to explore the correlation between independent variables and the linear correlation between explanatory variables and independent variables. The results are shown in the following table. Comment by TYT: 原文直接给的英文“other, other economic”就直接挪过来，确定下是不是两个other Comment by TYT: 这里是不是少了表，记得插入

Correlation analysis mainly studies the correlation between variables. The range of correlation coefficient is between-1 and 1. The larger the absolute value, the closer the correlation between variables is. Qiu Haozheng (2006) put forward a detailed classification method of correlation coefficient, ∣r∣=1, which is completely correlated;∣r∣≤0.70 <0.99, highly correlated;0.40 ≤∣r∣<0.69, moderately correlated;0.10≤∣r∣<0.39, low correlation;∣r∣< 0.10, weak or irrelevant.

Generally, correlation analysis is needed before regression analysis to preliminarily judge the relationship between explanatory variables and interpreted variables. Therefore, pearson correlation analysis is used to analyze the linear correlation between variables. The specific results are shown in Table 2.

It can be seen from the above table that most of the correlation coefficients between independent variables are less than 0.5, indicating that the correlation degree between independent variables is small, and the correlation coefficients between dependent variables and independent variables are only individually greater than 0.5, so we should explore the causal relationship between independent variables and dependent variables through regression analysis.

Table X Correlation Analysis Table 1

	gfdddi02	gfddoe01	gfddai03	gfddai20	gfddai23	gfddai34	gfddai35	gfddam04
gfdddi02	1
gfddoe01	-0.2059	1
gfddai03	0.4155	-0.4226	1
gfddai20	0.8827	-0.2007	0.3735	1
gfddai23	0.7977	-0.2151	0.4077	0.9556	1
gfddai34	0.3473	-0.2402	0.6735	0.1696	0.261	1
gfddai35	0.2802	-0.3179	0.8555	0.1077	0.1196	0.7283	1
gfddam04	-0.2372	0.0276	-0.1422	-0.2234	-0.4136	-0.3086	-0.0694	1

Table X Correlation Analysis Table 2

	gfddsi01	gfddoe01	gfddai03	gfddai20	gfddai23	gfddai34	gfddai35	gfddam04
gfddsi01	1
gfddoe01	0.1032	1
gfddai03	0.7779	-0.4219	1
gfddai20	0.0181	-0.1988	0.3547	1
gfddai23	0.8177	-0.2196	0.4216	0.9452	1
gfddai34	-0.0528	-0.2378	0.6428	0.1705	0.2547	1
gfddai35	0.2082	-0.3195	0.8652	0.0954	0.1474	0.688	1
gfddam04	0.1769	0.0241	-0.1212	-0.2246	-0.4021	-0.3101	-0.0481	1

4 regression analysis

4.1 regression analysis

In order to explore the specific influence relationship, the following regression model was constructed.

gfdddi02	Coef.	robust.std.err	t	P>|t|	[95% Conf.Interval
gfddoe01	-0.0174635	0.0857947	-0.2	0.847	-0.2380057	0.2030787
gfddai03	-0.4269511	0.8353712	-0.51	0.631	-2.574341	1.720439
gfddai20	6.339178	1.794365	3.53	0.017	1.726615	10.95174
gfddai23	-20.99733	10.40286	-2.02	0.01	-47.73873	5.744067
gfddai34	0.9361124	0.7217221	1.3	0.251	-0.9191335	2.791358
gfddai35	0.6808618	1.724007	0.39	0.709	-3.750839	5.112562
gfddam04	-2.124557	1.569369	-1.35	0.234	-6.158748	1.909633
_cons	36.9883	20.51093	1.8	0.31	-15.73672	89.71331
F(7, 5) = 7.90
Prob>F=0
R-squared = 0.9171
Adj R-squared = 0.8011
Root MSE = 16.011

The R square of the model is 0.9171, and the adjusted r square is 0.8011, indicating that the independent variable can explain 80.11% of the dependent variable, and the model fitting effect is very good. And the statistical value of f is 7.9, and the test result of f test is significant, that is, at least one independent variable has significant influence on the dependent variable, and the model is meaningful.

In addition, in the t test of regression coefficient, because the p values of credit card and mobile phone used to pay bills are less than 0.05, the regression coefficients of credit card and mobile phone used to pay bills have passed the significance test, which shows that they have significant influence on the dependent variable.

The regression equation obtained is

Y=36.9883+gfddoe01*-0.0174635+gfddai03*-0.4269511+gfddai20*6.339178+gfddai23*-20.99733+gfddai34*0.9361124+gfddai35*0.6808618+gfddam04*-2.124557

4.2 Robustness analysis

To test the robustness of the above model, the dependent variable is replaced by Bank Z-score from Deposit money banks' assets to GDP, and the regression results are as follows. It can be seen from the table that the p value of credit card and mobile phone used to pay bills is still less than 0.05 in the equation, which indicates that credit card and mobile phone used to pay bills have significant influence on the dependent variable, and the robustness of the model has been verified.

gfddsi01	Coef.	robust.std.err	t	P>|t|	[95% Conf.Interval
gfddoe01	0.0175336	0.0358044	0.49	0.642	-0.0700767	0.1051439
gfddai03	-0.4530194	0.3455447	-1.31	0.238	-1.298537	0.3924981
gfddai20	-1.096349	0.588331	-1.86	0.012	-2.535943	0.3432448
gfddai23	7.385612	3.372901	2.19	0.071	-0.86758	15.6388
gfddai34	-0.2145848	0.2747104	-0.78	0.464	-0.8867769	0.4576072
gfddai35	1.107059	0.6637819	1.67	0.146	-0.5171564	2.731275
gfddam04	0.9514052	0.6042903	1.57	0.166	-0.52724	2.43005
_cons	1.895037	8.14141	0.23	0.824	-18.02628	21.81635
F(7, 6) = 1.06
Prob>F= 0.0185
R-squared = 0.5525
Adj R-squared = 0.0304
Root MSE = 6.6972