Appendix: Relationships between revenue elasticities
This Appendix demonstrates why the four profiles in Fig. 3 are approximately linear. To see why this is the case, it is useful to consider each profile separately. Consider first \(\eta _{T_{1},\tau _{1}}\). From Eq. (35), since \(\eta _{y_{1},1-\tau _{1}}=\varepsilon _{1}\) for a single individual, then
$$\begin{aligned} \eta _{T_{1},\tau _{1}}=\eta _{T_{1},\tau _{1}}^{\prime }-\left( \frac{\tau _{1}}{1-\tau _{1}}\right) \left( \eta _{T_{1},y_{1}}\right) \varepsilon _{1} \end{aligned}$$
(A.1)
Hence, it can be seen that the slope of the relationship between \(\eta _{T_{1},\tau _{1}}\) and \(\varepsilon _{1}\) is constant with respect to changes in \(\varepsilon _{1}\), given by \(-\left( \frac{\tau _{1}}{1-\tau _{1} }\right) \left( \eta _{T_{1},y_{1}}\right) \) where, from (37), \(\eta _{T_{1},y_{1}}=\frac{y_{1}}{y_{1}-a_{k}^{*}}\). The single-person \(\eta _{T_{1},\tau _{1}}\) profile is therefore exactly linear, given a fixed tax structure and the individual’s income.
For two individuals in a couple, first consider person 1, where from (35) and (25):
$$\begin{aligned} \eta _{T_{1},\tau _{1}}=\eta _{T_{1},\tau _{1}}^{\prime }-\left( \frac{\tau _{1}}{1-\tau _{1}}\right) \left( \eta _{T_{1},y_{1}}\right) \varepsilon _{1} \left[ \frac{(1+\varepsilon _{1})(1+\varepsilon _{2})}{(1+\varepsilon _{1})(1+\varepsilon _{2})-(\varepsilon _{1}\varepsilon _{2})^{2}}\right] \end{aligned}$$
(A.2)
For most plausible values of \(\varepsilon _{1}\) and \(\varepsilon _{2}\), it can be expected that \((\varepsilon _{1}\varepsilon _{2})^{2}\) is small.Footnote 17 Thus, from Eq. (A.2), if \((\varepsilon _{1}\varepsilon _{2})^{2}\approx 0\), the variation between \(\eta _{T_{1},\tau _{1}}\) and \(\varepsilon _{1}\) reduces to:
$$\begin{aligned} \eta _{T_{1},\tau _{1}}\approx \eta _{T_{1},\tau _{1}}^{\prime }-\left( \frac{\tau _{1}}{1-\tau _{1}}\right) \left( \eta _{T_{1},y_{1}}\right) \varepsilon _{1} \end{aligned}$$
(A.3)
Following a similar process for person 2, from (41 ) and (25) it can be shown that:
$$\begin{aligned} \eta _{T_{2},\tau _{1}}=\left( \frac{\tau _{1}}{1-\tau _{1}}\right) \left( \frac{y_{2}}{y_{2}-a_{s}^{*}}\right) \left( \frac{\varepsilon _{1}\varepsilon _{2}}{1+\varepsilon _{1}}\right) \left[ \frac{(1+\varepsilon _{1})(1+\varepsilon _{2})}{(1+\varepsilon _{1})(1+\varepsilon _{2})-(\varepsilon _{1}\varepsilon _{2})^{2}}\right] \quad \end{aligned}$$
(A.4)
and:
$$\begin{aligned} \eta _{T_{2},\tau _{1}}\approx \left( \frac{\tau _{1}}{1-\tau _{1}}\right) \left( \frac{y_{2}}{y_{2}-a_{s}^{*}}\right) \left( \frac{\varepsilon _{1}\varepsilon _{2}}{1+\varepsilon _{1}}\right) \end{aligned}$$
(A.5)
if \((\varepsilon _{1}\varepsilon _{2})^{2}\approx 0\). However, unlike the case for \(\eta _{T_{1},\tau _{1}}\) in (A.3), the approximation for \( \eta _{T_{2},\tau _{1}}\) does not display a simple linear relationship with \( \varepsilon _{1}\). That is, both the exact specification in (A.4) and the approximation in (A.5) suggest nonlinear relationships between \( \eta _{T_{2},\tau _{1}}\) and \(\varepsilon _{1}\).