Estimation Results
Table 4 reports the estimation results. The estimated coefficients can be directly interpreted as mean estimates of the WTP, except for the coefficient of the purchase price, which is the estimated mean of the log of the price coefficient. The estimates are in line with economic theory. A higher price, higher fuel costs or higher emissions are associated with lower levels of utility. The associated coefficients of these attributes are all statistically significant.
Regarding fuel types, the coefficients for diesel, CNG, biofuel and hydrogen are negative and statistically significant. This implies that these fuel types are, on average, valued less than gasoline (the reference fuel type). The least preferred fuel type is diesel with a WTP per vehicle that is €3230 lower than gasoline.Footnote 9 The coefficient for full-electric is negative but insignificant while only the coefficient for hybrid-electric is positive and significant. The mean WTP for a hybrid-electric vehicle, the most favoured fuel type, is €812 higher than a gasoline counterpart. The estimated standard deviation for hybrid of €3272 suggests there exists a very large degree of heterogeneity in preferences. Overall, consumers appear to favour gasoline and electric fuel types. These results may be driven by factors that are inherently related to (and therefore represented by) the respective fuel type but omitted in our model, such as harmful \(\hbox {NO}_x\) emissions for diesel or the relatively limited availability of refuelling stations for full-electric and hydrogen cars.
Regarding fuel costs, the average respondent values a decrease of €1 in fuel costs per 100 km at €434 at the moment of vehicle purchase. At an average annual mileage of 13,000 km, this implies a required pay-back period of only 3.3 years. It appears that car buyers with respect to fuel costs do not display far-forward looking behaviour, apply very high discount rates or use decision rules that are not based on valuation principles which a rational agent would use. This finding is very much in line with the mean required pay-back periods for US car drivers estimated by Greene et al. (2013). On the other hand, the results of Espey and Nair (2005) imply that US car buyers apply much lower discount rates, more accurately reflecting the outcome of valuation based on the (discounted) net present value. Compared to the results of Achtnicht (2012) and Hackbarth and Madlener (2013, 2016) for German car buyers, our estimates for the WTP to reduce fuel costs are somewhat lower. The subsequent driving cost analysis in Sect. 4.3 further illustrates the short implicitly required pay-back periods in the context of driving a hybrid car.
The mean WTP to reduce a vehicle’s emissions with 1 g per kilometre is €36.70. This coefficient is highly significant. All else equal, the average consumer prefers a car with lower emissions. The degree of preference heterogeneity in emissions is large, considering the estimated standard deviation of €30.81.
Table 4 Mixed logit model estimation results The estimation results of the second model yield insights in the relationship between socio-economic characteristics and preferences for emission reductions. Particularly, we find differences in WTP along the lines of gender, age and education but not income and car segment. The mean WTP to reduce a vehicle’s emissions with 1 g per kilometre of the reference group in this model is €21.62 (male, age 19–39, low education and a small segment car; the group with the lowest WTP). Females have a significantly higher WTP than males. Regarding age, we do not find differences between groups 19–39 and 40–64 while the WTP amongst individuals older than 64 is €17.19 higher. With respect to education, we do not find a significant difference between lower and medium education groups while the higher education group has a significantly higher WTP. Regarding income, we do not find statistically significant differences between groups. Finally, we do not find a statistically significant relationship between car segment and the WTP for emissions.Footnote 10
Willingness to Pay for Emission Reductions
To translate the WTP for emission reductions per kilometre into the WTP for emission reductions, we need to consider the effect of the purchase on the car’s emissions.Footnote 11 From the perspective of the car buyer, there is a direct effect on emissions during the period of ownership over the car. After re-selling the car, future owners are accountable for the car’s reduced emissions. This complicates estimating the WTP for emission reductions based on the WTP for emissions per kilometre because we do not know after how many kilometres the car is sold and the emission-attribute’s resale value at that point in time. By making the assumption that, during its entire lifetime, a car bought by individual i is owned by individuals that have the same WTP as individual i (and this WTP is fully paid), we can obtain an estimate for the WTP for emission reductions. Under this assumption, the WTP for emission reductions (\(WTP^{tonne}\)) equals the WTP for emission reductions per kilometre (\(-WTP^{attribute}\) i.e. minus the emissions parameter estimate), divided over the car’s expected lifetime mileage E[Tkm], which in turn is divided by one million to transform grams into tonnes:
$$WTP^{tonne}_i = \frac{-WTP^{attribute}_i}{E[Tkm]/1000000}$$
(9)
Assuming an expected total mileage of 184,000 km for cars (Ricardo-AEA 2015), this results in a mean WTP per tonne of emission reductions of €199 and, since equation five is distributed according to the distribution of \(WTP^{attribute}\), a standard deviation of €167.
Based on the method proposed by Revelt and Train (2000), we calculate individual-level coefficients for the emissions parameter. Figure 1 provides a graphical description of the WTP distribution using kernel density estimates, based on these individual level-estimates and equation nine. As a result of assuming a normal distribution for the emissions attribute and the fact that equation nine does not affect the shape of this distribution, the distribution of WTP for emission reductions appears normal, has a mean of €199 and a minimum and maximum of − €94 and €562, respectively.Footnote 12 This highlights the considerable heterogeneity in preferences for emissions that we estimate.
In practice, people will not sell cars to others with a similar WTP because they have no incentive to do so nor can they differentiate between buyers on the basis of their WTP. Taking this into account, we could determine the WTP for emission reductions according to:
$$WTP^{tonne}_i = \frac{-WTP^{attribute}_i+E[P^{attribute}_{E[km_i]}]}{E[km_i]/1000000}$$
(10)
where \(E[P^{attribute}_{E[km_i]}]\) refers to the expected resale value of the attribute after buyer i’s expected mileage \(E[km_i]\). This equation says that the WTP for emissions reductions is equal to the net WTP for the attribute, divided over the individual’s mileage, which in turn is divided by one million to transform grams into tonnes. Unfortunately, information about individual mileage and expected resale value of the attribute is unavailable. By making several assumptions, we can get an estimate of the WTP for emission reductions based on this equation. For the expected mileage, we take the average annual mileage in the Netherlands (13,000 km) and multiply by the average ownership duration (4.1 years) to arrive at an assumption for E[km] equal to 53,300 km (CBS 2017). Considering that we have very little information about the resale value of the attribute after 53,300 km, our assumptions for this parameter are arbitrary. Suppose the resale value of the attribute decreases linearly in the mileage.Footnote 13 Let us further assume that the value of the attribute after 0 km (i.e. with 184,000 km remaining) is equal to €36.70, the mean WTP for the attribute. The expected resale value after 53,300 km then equals €26.07.Footnote 14 According to (10), the mean WTP under these assumptions equals €199.Footnote 15 The most pessimistic assumption for the attribute’s resale value would be to set it equal to €0 at any remaining mileage, resulting in an estimated mean WTP for emission reductions equal to €689.Footnote 16
A Driving Cost and WTP Comparison of Hybrid and Gasoline Types
While there appears to be a latent preference for lower emissions, reductions will only materialise if actually available clean car types will be purchased. In that respect, hybrid cars seem to be promising considering that they generally emit less \(\hbox {CO}_2\) and have lower fuel cost. Moreover, compared to gasoline, hybrid is the only fuel type for which we estimate a positive WTP. In addition, the number of actually available hybrid models in the Netherlands has increased from 13 in 2011 to 71 at this moment (November 2019). This subsection aims to further the understanding of the preferences for (non-plug-in) hybrid cars and of the degree of forward looking behaviour of buyers of hybrids. We make pair-wise comparisons of the driving costs and WTP of two actually available models that are sold with both a hybrid and gasoline engine. Importantly, the hybrid and gasoline types that we compare are nearly identical in the attributes for which we did not estimate the WTP.
Specifically, for the two hybrid-gasoline pairs, we estimate the (distribution of the) willingness to pay a premium for the hybrid versus the gasoline type based on the WTP estimates for emissions, fuel costs and fuel type. Consequently, we compare the WTP for the hybrid with (i) the estimated savings from lower fuel costs, and (ii) the actual market premium and vehicle sales records. By comparing the WTP for the hybrid with the estimated fuel savings we gain further insight into the degree of forward looking behaviour of car buyers. By comparing the distribution of the WTP for the hybrid with the actual market premium and vehicle sales records we obtain anecdotal evidence of whether our stated-preference results appear aligned with revealed-preference data.
We compare the hybrid and gasoline types of a Toyota C-HR and Toyota Yaris.Footnote 17 These models are available with highly comparable gasoline and hybrid engines and are nearly identical in other respects. This analysis assumes that consumers regard the hybrid and gasoline types as identical, except for the fuel type, fuel costs and emissions. A drawback of using real-life models is that the reported emissions and fuel consumption levels are based on laboratory tests, which cannot be trusted. This is further complicated by the difference in accuracy of lab-tests for hybrid and gasoline types (ICCT 2019). However, the differences in fuel consumption and emissions of the models in our comparison are somewhat reflective of the real-world performance increase of hybrids compared to gasoline cars of 23% in the EU, as estimated by Emissions Analytics (2019). The hybrid’s reported emissions and fuel consumption are 36% and 15% lower for the C-HR and Yaris, respectively. In addition to the results presented in the current subsection, we have repeated the analysis for two hypothetical hybrid-gasoline pairs. The results of this sensitivity analysis are reported in Table 8 and Figs. 6 and 7 in “Appendix 4”. The outcomes are comparable to the results reported here.
Table 5 and Fig. 2 report the results of the driving cost comparison for the Toyota C-HR (first column) and Toyota Yaris (second column). The calculation of the WTP for the hybrid’s lower fuel cost, lower emissions and hybrid fuel type attributes are based on the estimated mean WTP for those attributes, as reported in Table 4. For example, the WTP for the improvement in the hybrid C-HR’s fuel cost (row b) is calculated as the estimated mean WTP for a decrease in fuel costs of €1 per 100 km (€433.84) multiplied by the difference in fuel costs (in € per 100 km) between the gasoline and hybrid types (i.e. €\(1.65/l\times (6.1-3.8)l/100\,{\mathrm{km}}\)), which equals €1646. The bottom of Table 5 shows the annual fuel savings at various annual mileages and reports the implied pay-back period of the WTP for the hybrid’s fuel cost attribute (corresponding to row (b)), and the emissions and hybrid fuel type attributes (corresponding to row (c)) in between brackets. For example, at an annual mileage of 13,000 km, the annual fuel savings of the C-HR hybrid are calculated as the difference in litres of fuel consumption per 100 km (i.e \((6.1-3.8)l/100\,{\mathrm{km}}\)) times the fuel price per litre (€1.65/l), multiplied by the annual mileage (13,000 km), which equals €493.35. This implies a required pay-back period of 3.3 and 5.5 years for the fuel cost (row b), and fuel type and emissions attributes (row c), respectively.
For the Yaris, one important difference in the gasoline and hybrid type is the higher monthly vehicle tax (MRB) of the hybrid type (€7.33 per month) due to its slightly higher weight (+ 35 kg).Footnote 18 The reported annual fuel savings for the Yaris are net of these higher taxes. Panel a and b of Fig. 2 show the implied pay-back period in mileage terms for the hybrid C-HR and for the Yaris at an annual mileage of 13,000 km (this only matters for the Yaris due to the difference in fixed monthly taxes).
The results for the C-HR display the short required pay-back period from fuel savings. For the mean respondent, the WTP for lower fuel costs is earned back after 43,300 km or 3.3. years. The total premium (fuel costs, fuel type and emissions) is earned back after 115,000 km, well below the expected lifetime mileage of a gasoline car (184,000 km). For the Toyota Yaris, pay-back from ‘gross’ fuel savings takes slightly longer. When accounting for the higher MRB taxes, pay-back takes much longer.Footnote 19
On the basis of the method proposed by Revelt and Train (2000), we can use the WTP estimates for the various characteristics from Sect. 4.1 to estimate the approximate distribution of the WTP for the hybrids. For the Yaris, we use the estimates for the WTP for fuel costs to control for the higher MRB taxes.Footnote 20 Figure 3 shows kernel density estimates of the distribution of the WTP for the hybrid types of the C-HR (panel a) and Yaris (panel b), respectively. The solid lines provide the distribution for the full sample whereas the dotted lines provide the distribution for individuals that currently own a similarly sized vehicle and indicated a reference price in the neighbourhood of the listing price, i.e. this concerns individuals who appear likely to be in the market for the respective vehicle. The vertical dash-dotted line indicates the actual price premium for the hybrid type.
Taking the actual price premium in consideration, our results indicate that nearly all respondents (98%) prefer the hybrid type of the C-HR over the gasoline type. In case of the Yaris, approximately two-thirds (67%) of the respondents prefers the hybrid over the gasoline type. Based on this, we would expect the share of hybrids in actual total sales to be higher for the C-HR than for the Toyota Yaris, which is also observed. Interestingly, despite that our model and results are not tailored for analysing revealed preferences, the actual share of the hybrid types in total sales (97% for the C-HR and 74% for the Yaris; see Table 5) quite closely matches the estimated share of respondents who are WTP at least the hybrid’s actual premium. It is particularly interesting to note that, despite the higher purchase price and MRB taxes for the hybrid Yaris, which cause long pay-back periods, it is still the preferred type by most consumers, both in practice and based on this stated-preference analysis. For these two highly specific cases, the stated-preference results do not appear to be misaligned with revealed-preference data.
Table 5 Driving cost comparison based on existing hybrid and gasoline types of a Toyota C-HR and Toyota Yaris.