RDP 2024-02: Valuing Safety and Privacy in Retail Central Bank Digital Currency 5. Diagnostic Tests

Zan Fairweather, Denzil Fiebig, Adam Gorajek, Rochelle Guttmann, June Ma and Jack Mulqueeney

April 2024

The merit of our empirical strategy depends heavily on the successful randomisation of options in the table shown to the survey participants. To gauge the success of the randomisation we compare the mean age, sex, and income of respondents who saw the various account possibilities (Figure 2). The results are consistent with effective randomisation, the measured means all being very similar relative to their natural ranges.

Since the estimates of the parameters in our model of account choice are secondary in importance to the derived estimates of willingness to pay, we leave those parameter estimates to Appendix B. The key takeaway is that all the estimates have plausible signs and magnitudes. The 95 per cent confidence interval for the intercept estimates are (−0.15, 0.04) for the baseline model, and (−0.17, 0.03) and (−0.18, 0.02) for the extensions, and so are consistent with attentive survey respondents.

Livermore et al (2023) produce a comprehensive set of descriptive statistics relating to the survey. We do not repeat them here.

Figure 2: Randomisation Testing
Sample mean, by account options shown to survey participants, 2022
Figure 2: Randomisation Testing - a three panel dot plot with shading showing the average demographics (in particular: age, the share of people who are female, and average household income) of people who saw the different accounts possibilities. The message is that the people who saw each different account were similar in terms of demographics. This suggests effective randomisation. The shading around the dots represents uncertainty around our estimates.

Note: Shading shows 95 per cent confidence intervals.

Source: RBA calculations, based on data from Ipsos.