“…For example, in the case of Age75_79, the results for E-mobile, D-fast-mobile, M-fast, and All-fast-mobile show that respondents in this group increase the probability that electronic money, debit card, mobile payments, and credit cards would be top-ranked by 9% point (Bar with horizontal lines), 12% point (Black bar), 12% point (Gray bar) and 20% point (Light gray bar), while respondents on average increase the probability that electronic money, debit card, mobile payments, and credit cards would be top-ranked by 31% point (Black triangle), by 38% point (Black circle), by 36% point (Dark gray circle) and by 32% point (Light gray circle). These results are similar to the findings by Hayashi and Toh (2020) using the US data that banked households that are lower income, less educated, older, not in the labor force, disabled, unmarried, or in a rural area are significantly more likely to lack a smartphone and home internet access, are less likely to use mobile banking and thus are unlikely to benefit from faster payments. In contrast, three right panels of Figure 3 show that the results of the counterfactual simulations for middle-age, high-income, and high-asset holdings groups: Age55_59, Income_1500_, and Asset_2000_.…”