Skip to main content

Advertisement

SpringerLink
Log in

Attributes needed for Japan’s central bank digital currency

  • Article
  • Published:
The Japanese Economic Review Aims and scope Submit manuscript

Abstract

The issuance of central bank digital currencies became a real policy issue after the announcement of Facebook’s Libra. Which types of product attributes should central bank digital currencies have to be widely accepted? We answer this question by analyzing consumers’ acceptance of hypothetical payment methods. We used Japanese data from the 2019 Financial Literacy Survey to estimate a model of consumers’ ranking of the frequency of the use of five payment methods via three statistical models. The estimates of three models showed that the respondents to the survey value payment methods with shorter transaction times and mobile payment methods. Based on the estimates of these models, we conducted counterfactual simulations for the introduction of the hypothetical mobile version of noncash payment methods that required a shorter transaction time. We found that these hypothetical products would be the most frequently used payment methods on average; however, respondents with experience of financial troubles and with small financial asset holdings would use them less frequently. The results suggest that if the Bank of Japan wanted to issue a central bank digital currency that would be used almost every day as a replacement for cash, policy tools should be utilized to encourage the use of it by these groups as well.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Availability of data and material

Not applicable.

Code availability

Not applicable.

Notes

  1. See also Auer and Böhme (2020), Armelius et al. (2020), and Shah et al. (2020) for recent examples of technologies for achieving universally accessible CBDCs.

  2. Details are available on the JCB Japanese website (Accessed April 26, 2020).

    https://www.global.jcb/ja/press/00000000162855.html

  3. Interested readers can refer to the Appendix in Fujiki (2019) regarding the use of payment methods in Japan.

  4. More details are available at https://www.orico.co.jp/creditcard/oricocardpaywave/#feat-04 (Accessed April 26, 2020).

  5. The link to the press release is https://prtimes.jp/a/?c=6846&r=89&f=d6846-89-pdf-0.pdf (Accessed April 26, 2020).

  6. The details of the two surveys are available upon request from the Mobile Marketing Data Laboratory website: https://mmdlabo.jp/company/ (Accessed April 26, 2020).

  7. This section depends heavily on Sect. 4 of Fujiki (2020a).

  8. Note that Overconfidence is not measured using the gap between the self-perceptions of the score of Objective financial literacy and the actual score of Objective financial literacy as in Anderson et al. (2017).

  9. It is possible to apply the LCL model to the ROL model; however, because our partial rank data contain numerous ties, we cannot apply the methods proposed by Yoo (2020, p. 420) to estimate a latent class ROL model using this Stata statistical package.

  10. We also estimate the LCL models for C = 2 and 3, which replace \({Z}_{j}\) in Eq. (4) by \(X_{i} \otimes Z_{j}\). However, we cannot obtain reliable results because the command lclogit2 does not converge.

  11. We also estimated bootstrapped standard errors for the parameter estimates following the suggestion by Train (2008). While we conducted 2000 replications, we found that 583 (or 30%) out of 2,000 replications did not yield parameter estimates, and the remaining 1,417 replications yielded bootstrapped standard errors whose absolute values are large relative to the absolute values of the parameter estimates.

  12. See https://www.jreast.co.jp/e/press/20051101/index.html for the mobile Suica service as of 2006 (Accessed April 26, 2020).

  13. Details of Sony Bank WALLET are available at https://moneykit.net/en/card/ (Accessed April 26, 2020).

References

  • Ackerberg, D., Benkard, L., Berry, S., & Pakes, A. (2007). Econometric tools for analyzing market outcomes. In J. Heckman & E. Leamer (Eds.), The handbook of econometrics (Vol. 6A, pp. 4171–4276). North-Holland.

    Chapter  Google Scholar 

  • Akana, T., & Ke, W. (2020). Contactless payment cards: Trends and barriers to consumer adoption in the U.S. Federal Reserve Bank of Philadelphia. Consumer Finance Institute. Working paper, DP 20–03

  • Amamiya, M. (2020). Central bank digital currency and the future of payment and settlement systems. Remarks at the Future of Payments Forum, February 27, 2020. https://www.boj.or.jp/en/announcements/press/koen_2020/ko200306a.html/. Accessed 21 Sept 2020

  • Anderson, A., Baker, F., & Robinson, D. T. (2017). Precautionary savings, retirement planning and misperceptions of financial literacy. Journal of Financial Economics, 126(2), 383–398.

    Article  Google Scholar 

  • Armelius, H., Guibourg, G., Johansson, S., & Schmalholz, J. (2020). E-krona design models: Pros, cons and trade-offs. Sveriges Riksbank Economic Review, 2020(2), 80–96.

    Google Scholar 

  • Auer, R., & Böhme, R. (2020). The technology of retail central bank digital currency. BIS Quarterly Review, March 2020, 85–100.

  • Bank of Japan, (2020a). The Bank of Japan’s approach to central bank digital currency. https://www.boj.or.jp/en/announcements/release_2020/data/rel201009e1.pdf. Accessed 9 Oct 2020

  • Bank of Japan, (2020b). Payment and Settlement Systems Department: Technical challenges for the central bank digital currency to have cash equivalent functions. (in Japanese). https://www.boj.or.jp/research/brp/psr/data/psrb200702.pdf. Accessed 6 July 2020

  • Beggs, S., Cardell, S., & Hausman, J. (1981). Assessing the potential demand for electric cars. Journal of Econometrics, 17(1), 1–19.

    Article  Google Scholar 

  • Beshears, J., Choi, J. J., Laibson, D., & Madrian, B. C. (2018). Behavioral household finance. The handbook of behavioral economics—foundations and applications (Vol. 1, pp. 177–274). Amsterdam: Elsevier.

    Google Scholar 

  • Borzekowski, R., & Kiser, E. K. (2008). The choice at the checkout: Quantifying demand across payment instruments. International Journal of Industrial Organization, 26(4), 889–902.

    Article  Google Scholar 

  • Borzekowski, R., Kiser, E. K., & Ahmed, S. (2008). Consumers’ use of debit cards: Patterns, preferences, and price response. Journal of Money, Credit and Banking, 40(1), 149–172. https://doi.org/10.1111/j.1538-4616.2008.00107.x

    Article  Google Scholar 

  • Brown, M., Hentschel, N., Mettler, H., & Stix, H. (2020). Financial innovation, payment choice and cash demand—Causal evidence from the staggered introduction of contactless debit cards. Oesterreichische Nationalbank. Working Papers 230

  • Chen, H., Felt, M., & Huynh, K. P. (2017). Retail payment innovations and cash usage: Accounting for attrition by using refreshment samples. Journal of the Royal Statistical Society, Series A, 180(2), 503–530.

    Article  Google Scholar 

  • Chen, H., Huynh, K. P., & Shy, O. (2019). Cash versus card: Payment discontinuities and the burden of holding coins. Journal of Banking & Finance, 99, 192–201.

    Article  Google Scholar 

  • Esselink, H., & Hernández, L. (2017). The use of cash by households in the euro area. European Central Bank. Occasional Paper Series, No. 201

  • Fok, D., Paap, R., & Van Dijk, B. (2012). A rank-ordered logit model with unobserved heterogeneity in ranking capabilities. Journal of Applied Econometrics, 27, 831–846.

    Article  Google Scholar 

  • Fujiki, H. (2019). How do we choose to pay using evolving retail payment technologies? Some additional results from Japan. Tokyo Center for Economic Research. TCER working paper series, No. E135

  • Fujiki, H. (2020a). Who adopts crypto assets in Japan? Evidence from the 2019 financial literacy survey. Journal of the Japanese and International Economies, 58, 101107. https://authors.elsevier.com/sd/article/S0889-1583(20)30044-7. Accessed 2 Nov 2021

  • Fujiki, H. (2020b). The use of noncash payment methods for regular payments and the household demand for cash: Evidence from Japan. Japanese Economic Review, 71, 719–765. https://doi.org/10.1007/s42973-020-00049-5

    Article  Google Scholar 

  • Fujiki, H. (2020c). Are the actual and intended sources of financial knowledge the same? Evidence from Japan. Japan and the World Economy, 55, 101026. https://www.sciencedirect.com/science/article/pii/S092214252030027X. Accessed 2 Nov 2021

  • Fujiki, H., & Tanaka, M. (2018a). How do we choose to pay using evolving retail payment technologies? Evidence from Japan. Journal of the Japanese and International Economies, 49, 85–99.

    Article  Google Scholar 

  • Fujiki, H., & Tanaka, M. (2018b). Choice of payment instruments for low-value transactions in Japan. In D. Bundesbank (Ed.), War on cash: is there a future for cash? International cash conference 2017 (pp. 416–468). Deutsche Bundesbank.

    Google Scholar 

  • Greene, C., O’Brien, S., & Schuh, S. (2017). U.S. consumer cash use, 2012 and 2015: An introduction to the diary of consumer payment choice. Federal Reserve Bank of Boston. Research Data Reports Paper, No. 17–6

  • Hansen, B. E. (2021) Econometrics. https://www.ssc.wisc.edu/~bhansen/econometrics/Econometrics.pdf/ Accessed 2 Feb 2021

  • Hausman, J. A., & Ruud, P. A. (1987). Specifying and testing econometric models for rank-ordered data. Journal of Econometrics, 34, 83–104.

    Article  Google Scholar 

  • Hayashi, F., & Toh, Y. L. (2020). Mobile banking use and consumer readiness to benefit from faster payments. Federal Reserve Bank of Kansas City. Economic Review, 105(1), 21–36.

    Google Scholar 

  • Henry, C. S., Huynh, K. P., & Welte, A. (2018). 2017 Method-of-payments survey results. Bank of Canada. Bank of Canada Staff Discussion Paper, No. 2018–17

  • Hirschman, E. C. (1982). Consumer payment systems: The relationship of attribute structure to preference and usage. The Journal of Business, 55(4), 531–545.

    Article  Google Scholar 

  • Huynh, K. P., Molnar, J., Shcherbakov, O., & Yu, Q. (2020). Demand for payment services and consumer welfare: The introduction of a central bank digital currency. Bank of Canada. Staff Working Paper 2020–7

  • Jonker, N., Hernandez, L., de Vree, R., & Zwaan, P. (2018). From cash to cards: How debit card payments overtook cash in the Netherlands. De Nederlandsche Bank. DNB occasional study, No.16

  • Kadoya, Y., & Khan, M. S. R. (2020). Financial literacy in Japan: New evidence using financial knowledge, behavior, and attitude. Sustainability, 12(9), 3683.

    Article  Google Scholar 

  • Koulayev, S., Rysman, M., Schuh, S., & Stavins, J. (2016). Explaining adoption and use of payment instruments by U.S. consumers. The RAND Journal of Economics, 47(2), 293–325.

    Article  Google Scholar 

  • Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5–44.

    Article  Google Scholar 

  • Newson, R. (2002). Parameters behind “nonparametric” statistics: Kendall’s tau, Somers’ D and median differences. Stata Journal, 2(1), 45–64.

    Article  Google Scholar 

  • Pichler, P., Summer, M., & Weber, B. (2020). Does digitalization require central bank digital currencies for the general public? Oesterreichische Nationalbank. Monetary Policy & the Economy, Q4(19), 40–56.

    Google Scholar 

  • Schuh, S., & Briglevics, T. (2014). US consumer demand for cash in the era of low interest rates and electronic payments. European Central Bank. European Central Bank Working Paper Series, No. 1660

  • Sekita S., Kakkar, V., & Ogaki, M. (2018). Wealth, financial literacy, and behavioral biases: Evidence from Japan. Institute for Economic Studies, Keio University. Keio-IES Discussion Paper Series, DP2018-023

  • Shah, D., Arora, R., Du, H., Darbha, S., Miedema, J., & Minwalla, C. (2020). Technology approach for a CBDC. Bank of Canada. Staff Analytical Note 2020–6

  • Stata Press, (2019). Stata choice models reference manual. Release 16. https://www.stata.com/manuals/cm.pdf. Accessed 24 Jan 2021

  • Train, E. K. (2008). EM algorithms for nonparametric estimation of mixing distributions. Journal of Choice Modelling, 1(1), 40–69.

    Article  Google Scholar 

  • Trütsch, T. (2020). The impact of contactless payment on cash usage at an early stage of diffusion. Swiss Journal of Economics Statistics, 156, 5. https://doi.org/10.1186/s41937-020-00050-0

    Article  Google Scholar 

  • Vallée, G. (2018). How long does it take you to pay? A duration study of Canadian retail transaction payment times. Bank of Canada. Staff Working Paper 2018–46

  • Wakamori, N., & Welte, A. (2017). Why do shoppers use cash? Evidence from a shopping diary. Journal of Money, Credit and Banking, 49(1), 115–169.

    Article  Google Scholar 

  • Yoo, H. I. (2020). lclogit2: An enhanced command to fit latent class conditional logit models. Stata Journal, 20(2), 405–425.

    Article  Google Scholar 

Download references

Acknowledgements

I thank Jozsef Molnar for sharing his work related to this draft. I would like to thank an anonymous referee who provided many useful suggestions to improve the earlier drafts. I would also like to thank Shinichi Fukuda, Kim P. Huynh, Kentaro Iwatsubo, Franck Jovanovic, Takeshi Kimura, Shigeto Kitano, Jesse Leigh Maniff, Ryuzo Miyao, Hajime Tomura, Hirofumi Uchida, Kenichi Ueda, Marcel Voia, and Nobuyoshi Yamori for their comments. I received permission from the Central Council for Financial Services Information to use data from the 2019 Financial Literacy Survey. I gratefully acknowledge the financial support of the Japan Society for the Promotion of Science through KAKENHI Grant No. 18K01704.

Funding

Japan Society for the Promotion of Science through KAKENHI Grant No. 18K01704.

Author information

Authors and Affiliations

  1. Faculty of Commerce, Chuo University, 742-1 Higashinakano, Hachioji-shi, Tokyo, 192-0393, Japan

    Hiroshi Fujiki

Authors
  1. Hiroshi Fujiki
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Not applicable.

Corresponding author

Correspondence to Hiroshi Fujiki.

Ethics declarations

Conflict of interest

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 109 KB)

Appendix

Appendix

See Appendix Table 1 and 2.

Table 1 Means of the control variables by subsamples of actual rank (1)
Full size table
Table 2 Means of the control variables by subsamples of actual rank (2)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fujiki, H. Attributes needed for Japan’s central bank digital currency. JER 74, 117–175 (2023). https://doi.org/10.1007/s42973-021-00106-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42973-021-00106-7

Keywords

JEL Classification

Search

Navigation