Financial literacy, behavioral traits, and ePayment adoption and usage in Japan

Financial Innovation

Table 6 Heterogeneous effects of financial literacy on ePayment adoption by behavioral traits (IV estimations)

	Using e-money	Using mobile payment apps	Using either e-money or mobile payment apps
	(1)	(2)	(3)
Panel A:
Financial literacy	0.101***	0.039**	0.084***
Financial literacy	[0.030]	[0.019]	[0.031]
Financial literacy * Risk aversion	0.004	0.041***	0.019
Financial literacy * Risk aversion	[0.016]	[0.010]	[0.016]
Risk aversion	− 0.017	− 0.056***	− 0.034***
Risk aversion	[0.013]	[0.009]	[0.013]
Herd behavior	0.014	0.017***	0.019**
Herd behavior	[0.009]	[0.005]	[0.009]
Other covariates
Anderson canon. corr. LM statistic	440.445	440.445	440.445
Cragg–Donald Wald F statistic	502.005	502.005	502.005
Sargan statistics (p-value)	0.3259	0.5525	0.8312
Panel B:
Financial literacy	0.118***	0.035***	0.127***
Financial literacy	[0.013]	[0.007]	[0.013]
Financial literacy * Herd behavior	− 0.054*	− 0.022	− 0.057*
Financial literacy * Herd behavior	[0.030]	[0.018]	[0.031]
Herd behavior	0.004	0.017***	0.010
Herd behavior	[0.010]	[0.005]	[0.010]
Risk aversion	− 0.015*	− 0.029***	− 0.022***
Risk aversion	[0.008]	[0.005]	[0.008]
Other covariates
Anderson canon. corr. LM statistic	433.22	433.22	433.22
Cragg–Donald Wald F statistic	606.369	606.369	606.369
Sargan statistics (p-value)	0.3124	0.3744	0.7636

*, **, ***Indicate significance at the 10%, 5%, and 1% levels, respectively. Standard errors are in brackets. Our regressions also control for occupation, frequency of acquiring news, and prefectural dummies. The first stage estimation results are presented in Appendix 1