Appendix B: Regression Results | RDP 2024-02: Valuing Safety and Privacy in Retail Central Bank Digital Currency

RDP 2024-02: Valuing Safety and Privacy in Retail Central Bank Digital Currency Appendix B: Regression Results

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

April 2024

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Table B1: Probit Model Regression Results
Variable	(1)		(2)		(3)
Variable	Baseline probit model	Average marginal effects^(a)	Extension probit model (age, income)	Average marginal effects^(a)	Extension probit model (cash use)	Average marginal effects^(a)
$Δ H i g h F e e_{i}$	−0.48 (−0.56, −0.39)	−0.15 (−0.18, −0.13)	−0.49 (−0.58, −0.41)	−0.16 (−0.18, −0.13)	−0.50 (−0.59, −0.41)	−0.16 (−0.18, 0.14)
$Δ C o m m e r c i a l A c c t_{i}$	0.07 (−0.09, 0.23)	0.02 (0.03, 0.08)	0.03 (−0.15, 0.20)	0.01 (−0.05, 0.06)	0.02 (−0.15, 0.19)	0.01 (−0.05, 0.06)
$Δ R b a V i s_{i}$	−0.48 (−0.73, −0.23)	−0.16 (−0.24, −0.08)	−0.48 (−0.74, −0.23)	−0.15 (−0.23, −0.07)	−0.51 (−0.77, −0.26)	−0.16 (−0.24, −0.08)
$Δ C o m m e r c i a l V i s_{i}$	−0.61 (−0.85, −0.37)	−0.20 (−0.27, −0.12)	−0.59 (−0.85, −0.34)	−0.19 (−0.27, −0.11)	−0.60 (−0.85, −0.34)	−0.19 (−0.27, −0.11)
$Δ A u s t r a c V i s_{i}$	−0.41 (−0.56, −0.27)	−0.13 (−0.18, −0.09)	−0.40 (−0.55, −0.25)	−0.13 (−0.17, −0.08)	−0.43 (−0.58, −0.28)	−0.13 (−0.18, −0.09)
$Δ A u s t r a c R b a V i s_{i}$	−0.44 (−0.68, −0.21)	−0.14 (−0.22, −0.07)	−0.45 (−0.20, −0.20)	−0.14 (−0.22, −0.07)	−0.48 (−0.73, −0.22)	−0.15 (−0.23, −0.07)
$Δ A u s t r a c C o m m e r c i a l V i s_{i}$	−0.95 (−1.19, −0.71)	−0.31 (−0.38, −0.24)	−0.91 (−1.16, −0.66)	−0.29 (−0.36, −0.22)	−0.90 (−1.15, −0.66)	−0.29 (−0.36, −0.21)
$(A g e_{i} - \bar{A g e}) \times Δ H i g h F e e_{i}$			0.04 (−0.02, 0.09)
$(A g e_{i} - \bar{A g e}) \times Δ C o m m e r c i a l A c c t_{i}$			−0.01 (−0.11, 0.09)
$(A g e_{i} - \bar{A g e}) \times Δ R b a V i s_{i}$			0.09 (−0.06, 0.24)
$(A g e_{i} - \bar{A g e}) \times Δ C o m m e r c i a l V i s_{i}$			0.03 (−0.12, 0.17)
$(A g e_{i} - \bar{A g e}) \times Δ A u s t r a c V i s_{i}$			0.07 (−0.02, 0.15)
$(A g e_{i} - \bar{A g e}) \times Δ A u s t r a c R b a V i s_{i}$			0.04 (−0.11,0.18)
$(A g e_{i} - \bar{A g e}) \times Δ A u s t r a c C o m m e r c i a l V i s_{i}$			0.07 (−0.08, 0.22)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ H i g h F e e_{i}$			0.05 (−0.08, 0.18)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ C o m m e r c i a l A c c t_{i}$			−0.08 (−0.33, 0.17)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ R b a V i s_{i}$			−0.08 (−0.46, 0.29)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ C o m m e r c i a l V i s_{i}$			−0.05 (−0.40, 0.30)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ A u s t r a c V i s_{i}$			−0.10 (−0.32, 0.12)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ A u s t r a c R b a V i s_{i}$			−0.01 (−0.37, 0.36)
$(H h I n c_{i} - \bar{H h I n c}) \times Δ A u s t r a c C o m m e r c i a l V i s_{i}$			−0.10 (−0.48, 0.28)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ H i g h F e e_{i}$					0.03 (0.00, 0.06)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ C o m m e r c i a l A c c t_{i}$					−0.02 (−0.08, 0.04)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ R b a V i s_{i}$					0.04 (−0.04, 0.13)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ C o m m e r c i a l V i s_{i}$					0.04 (−0.04, 0.13)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ A u s t r a c V i s_{i}$					0.02 (−0.03, 0.08)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ A u s t r a c R b a V i s_{i}$					0.07 (−0.02, 0.16)
$(C a s h U s e_{i} - \bar{C a s h U s e}) \times Δ A u s t r a c C o m m e r c i a l V i s_{i}$					0.03 (−0.06, 0.11)
Constant	−0.06 (−0.15, 0.04)		−0.07 (−0.17, 0.03)		−0.08 (−0.18, 0.02)
No of observations	997		997		983^(b)
Notes: 95 per cent confidence intervals are in parentheses. The delta symbol ‘ $Δ$ ’ represents a difference between dummy variables for accounts A and B, e.g. $Δ$ HighFee_i = HighFee_iA – HighFee_iB. Age variables are scaled by 10 (to represent decades), HhInc variables are scaled by $100,000, and CashUse variables are scaled by 10, for presentational purposes. The income interactions should be treated as approximations, since respondents only report income ranges and 10 per cent of the sample has its income top-coded. Average marginal effects are marginal effects evaluated at true observations for all individuals in the sample and averaged, using Stata's 'margins, dydx()’ command. The CashUse* variable has 14 missing observations for Consumer Payments Survey respondents who did not record any in-person transactions in the week of the payments diary. Source: RBA calculations, based on data from Ipsos.