# Buy and/or Pay Disparity: Evidence from Fully Autonomous Vehicles
## 4 Result
### WTB and PV  
Throughout Models (1) to (3), we find positive correlations between WTB and PV of approximately 0.172, indicating the 'overall' trend that people with a high level of WTB are likely to have higher PV and vice versa. Nevertheless, whether individuals' attitudes, expressed in latent factors, also show positive (or negative) trends in both WTB and PV needs to be clarified. As mentioned in Section 3.2, if there is a disparity in WTB/PV in the latents, then the changes in latents might divert the overall relationship between WTB and PV. Furthermore, as people can have multiple latents, looking into how the \begin{table}
\begin{tabular}{l r r r} \hline \hline
**Variables** & **Model (1)** & **Model (2)** & **Model (3)** \\ \hline \multicolumn{4}{c}{_Dependent Variable: PV_} \\
**Latents** & \(-\)0.029 *** 0.004) & \(-\)0.030 *** (0.004) \\ \multicolumn{4}{l}{Pollution} & 0.086 *** (0.004) & 0.086 *** (0.004) \\ \multicolumn{4}{l}{Merit} & 0.148 *** (0.003) & 0.152 *** (0.003) \\ \multicolumn{4}{l}{Fear} & \(-\)0.021 *** 0.003) & \(-\)0.023 *** (0.003) \\ \multicolumn{4}{l}{**Socio-Economics**} \\ In (Income) & 0.069 *** (0.003) & 0.069 *** (0.003) \\ \multicolumn{4}{l}{Houeshold Size} & \(-\)0.011 *** 0.003) & \(-\)0.011 *** (0.003) \\ \multicolumn{4}{l}{_In (age)_} & 0.026 *** (0.003) & 0.026 *** (0.003) \\ \multicolumn{4}{l}{Female} & \(-\)0.001 (0.003) & \(-\)0.0008 (0.003) \\ \multicolumn{4}{l}{Marry} & 0.022 *** (0.003) & 0.022 *** (0.003) \\ \multicolumn{4}{l}{**Car-Related**} \\ Car Ownership & \(-\)0.010 *** 0.025) & \(-\)0.010 *** (0.002) \\ \multicolumn{4}{l}{FCV} & 0.008 *** (0.002) & 0.008 *** (0.002) \\ \multicolumn{4}{l}{Diesel} & 0.011 *** (0.002) & 0.011 *** (0.002) \\ \multicolumn{4}{l}{Hybrid} & 0.045 *** (0.002) & 0.045 *** (0.002) \\ \multicolumn{4}{l}{Plug-in Hybrid} & 0.024 *** (0.002) & 0.024 *** (0.002) \\ \multicolumn{4}{l}{EV} & 0.016 *** (0.002) & 0.016 *** (0.002) \\ \multicolumn{4}{l}{Constant} & 0.550 *** (0.045) & 0.550 *** (0.045) \\ \multicolumn{4}{l}{Dependent Variable: WTB} \\ PV & & & & 0.172 *** (0.002) \\ \multicolumn{4}{l}{**Latents**} \\ Nature & 0.072 *** (0.004) & 0.077 *** (0.004) \\ \multicolumn{4}{l}{Pollution} & 0.048 *** (0.004) & 0.033 *** (0.004) \\ \multicolumn{4}{l}{Merit} & 0.240 *** (0.003) & 0.215 *** (0.003) \\ \multicolumn{4}{l}{Fear} & \(-\)0.076 *** (0.003) & \(-\)0.073 *** (0.003) \\ \multicolumn{4}{l}{**Socio-Economics**} \\ In (Income) & 0.076 *** (0.003) & 0.064 *** (0.003) \\ \multicolumn{4}{l}{Household Size} & 0.006 *** (0.003) & 0.008 *** (0.003) \\ \multicolumn{4}{l}{In (age)} & \(-\)0.067 *** (0.003) & \(-\)0.071 *** (0.003) \\ \multicolumn{4}{l}{Female} & \(-\)0.049 *** (0.003) \\ \multicolumn{4}{l}{Marry} & 0.013 *** (0.003) & 0.009 *** (0.003) \\ \multicolumn{4}{l}{**Car-Related**} \\ Car Ownership & \(-\)0.008 *** (0.002) & \(-\)0.007 *** (0.002) \\ \multicolumn{4}{l}{FCV} & \(-\)0.006 *** (0.002) & \(-\)0.007 *** (0.002) \\ \multicolumn{4}{l}{Diesel} & 0.007 *** (0.002) & 0.005 *** (0.002) \\ \multicolumn{4}{l}{Hybrid} & 0.035 *** (0.002) & 0.028 *** (0.002) \\ \multicolumn{4}{l}{_Plug-in Hybrid_} \\ \multicolumn{4}{l}{EV} & 0.011 *** (0.002) & 0.007 *** (0.002) \\ \multicolumn{4}{l}{Constant} & 1.618 *** (0.044) & 1.524 *** (0.043) \\ \multicolumn{4}{l}{**Fit Indices**} \\ RMSEA & & 0.069 & 0.069 & 0.067 \\ \multicolumn{4}{l}{AIC} & 6.01 \(\times\) 10\({}^{6}\) & 6.41 \(\times\) 10\({}^{6}\) & 6.65 \(\times\) 10\({}^{6}\) \\ \multicolumn{4}{l}{CFI} & 0.843 & 0.842 & 0.843 \\ \multicolumn{4}{l}{GFI} & 0.842 & 0.842 & 0.843 \\ \multicolumn{4}{l}{AGFI} & 0.802 & 0.802 & 0.81 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Coefficient estimates of structural equation (N = 180,771). * \(p\) \(<\) 0.1, ** \(p\) \(<\) 0.05, *** \(p\) \(<\) 0.01. \(p\) stands for _p_-value. Standard errors in parentheses. individual latents are correlated would also implicate which aspects and how much people are attracted/not attracted to FAVs. Implications from these results can also contribute to policies on motivating people to adopt FAVs.