[Retracted] How Does the Urgency of Borrowing in Text Messages Affect Loan Defaults? Evidence from P2P Loans in China

Table 10

Correlation coefficient matrix of variables.

Correlation coefficient	Default	Amount	Month	Interest	Grade	Sex	Age	Edu	Income	Length	Ability	Willing	Urgency	Purp
Default	1
Amount	−0.050	1
Month	−0.073	0.240	1
Interest	−0.026	0.234	0.864	1
Grade	−0.181	0.088	−0.032	−0.067	1
Sex	0.043	−0.053	−0.050	−0.048	0.01	1
Age	0.032	0.151	−0.034	−0.033	0.065	0.019	1
Edu	−0.228	0.122	−0.012	−0.039	0.093	-0.023	0.043	1
Income	0.055	0.539	0.03	0.038	0.050	0.011	0.155	0.027	1
Length	0.318	0.088	−0.018	0.011	0.044	0	0.048	0.098	0.084	1
Ability	−0.008	0.01	−0.103	−0.033	−0.006	−0.015	0.008	0.075	0.022	0.320	1
Willing	−0.036	−0.066	−0.119	−0.097	0.045	−0.003	−0.02	0.037	−0.056	0.202	0.235	1
Urgency	0.055	0.006	−0.051	−0.052	0.033	0.023	−0.012	0.071	0.026	−0.004	−0.024	0.019	1
Purp	−0.062	−0.019	0.041	0.019	0.012	−0.001	−0.081	0.034	−0.064	0.050	−0.031	−0.005	−0.043	1

Note: the symbols , , and indicate significance at the 10%, 5%, and 1% levels, respectively.