The determinants of the voting decision

We first explore the determinants of the voting equation from the bivariate probit model. Even if we may compare the sign and significance of the estimated coefficients between alternatives, we cannot directly balance the magnitude of effects. In order to do so, one needs to calculate the derivatives, i.e.

the marginal effects³³. Table 3.4 presents the marginal effects on the vote equation for the nine environmental initiatives. The results for the two placebo initiatives figure in table 2 in appendix 2.

5.1.1 The economic and demographic variables

The effect of income levels appears to vary widely across environmental initiatives and does not offer a clear-cut determinant of the demand for environmental quality³⁴. A unit increase in income clearly raises the probability of approval in 2 cases (halving traffic, electricity market referendum). A positive income effect is also observed in the green tax reform II initiative, but it vanishes when we control for

32 The conditional bivariate probit model with censoring is estimated with the maximum likelihood estimator of Van de Ven and Van Praag (1981). Two-step estimations give almost identical results.

33 Marginal effects have been calculated at the sample mean of the independent variables

34 In order to check the robustness of that conclusion, we fit several other specifications excluding alternatively the age, education and income variables since these are likely to be correlated. The sign and significance of the parameters did not change

political preferences and attitudes. On the other hand, the marginal effect on income appears to be significant and negative for the solar and nuclear ban initiatives as well as the energy conservation initiative (but at a 90% confidence interval only). For the two placebo initiatives, high income individuals appear to vote more in favor of the adhesion of Switzerland to the UNO. In the case of the SNB gold surplus referendum, no significant effect is found.

Our results differ from Kahn and Matsusaka (1997), who obtain a concave relationship between income and the rate of approval in 10 (out of 16) initiatives³⁵. For nuclear initiatives, we obtained similar results to Fort and Bunn (1988) since richer counties appear to favor nuclear power in U.S.

state initiatives. We also do not completely support Thalmann (2004), who obtains non-significant income coefficients for the solar and energy conservation initiative³⁶.

Comparing the initiatives, the effect of income on the demand for environmental quality depends on the instrument proposed and the type of environmental quality that it aims to preserve. High income citizens seem on average more sensitive to the type of costs the initiative involves. For example, they are more likely to refuse the initiatives increasing energy prices since they will bear the greatest burden in absolute terms. However, when the instrument seems more favorable to high incomes (as in the case of green tax reform) or imposes costs in a less predictable manner throughout society (traffic halving), richer citizens appear less inclined to refuse environmental initiatives. When comparing the 2 nuclear objects, the high income voters appear also to more strongly oppose the most costly initiative (nuclear ban). However, the previous conclusion has to be considered with caution since high income citizens are no more likely to support the surplus gold initiative, which intends to alleviate future tax increases.

We try to control for the distribution of the costs of environmental initiatives by including variables capturing the respondent’s occupation, car ownership and place of residence (alpin, nuclear). We intend to control for the income composition effect, i.e. people whose income is issued from activities penalized/favored by environmental protection measures are considered are more likely to oppose/accept the initiatives. Turning to occupation, the workers in industry or transport sectors did not appear to be more opposed to environmental propositions and the workers in the tourist and hotel sector more favorable to them. Indeed, most coefficients even if they have the expected sign are not significant. It is however surprising that the workers in the transportation activities did not strongly reject the initiatives aiming to increase gasoline prices and reduce traffic. We explain it by the fact that we could not distinguish between workers in road, rail and air traffic as well as between the private and public transport sector.

35 The income square variable has been dropped from the vote equation since it never appears significant.

36 As said earlier, the result of Thalmann (2004) may however not offer reliable estimates since no exclusion-restriction criterion has been used.

Tab. 3.4 Marginal effect on the vote equation (model including political variables) Traffic halving Motorless

sunday Nuclear

moratorium Nuclear ban Solar Energy

conservation

package Green tax reform I Green tax reform II Electricity market liberalization Coeff. Z Coeff. Z Coeff. Z Coeff. Z Coeff. Z Coeff. Z Coeff. Z Coeff. Z Coeff. Z gender 0.0660 1.27 0.1070*** 2.72 0.0393 1.02 0.0605 1.56 -0.0146 -0.27 0.0275 0.52 0.0263 0.48 -0.0030 -0.06 -0.0764* -1.71 age -0.0167 -0.9 -0.0575*** -4.5 -0.0503*** -4.12 -0.0340*** -2.63 -0.0382** -2.24 -0.0414** -2.5 -0.0310* -1.78 -0.0218 -1.11 -0.0051 -0.3 educ 0.0249** 2.16 0.0127 1.41 0.0133 1.5 0.1517* 1.81 0.0434*** 3.2 0.0432*** 3.23 0.0510*** 4.05 0.0039 0.3 0.0055 0.54 french -0.1029* -1.67 -0.0413 -0.91 -0.0668 -1.49 -0.0362 -0.8 -0.0613 -0.86 0.1050 1.55 -0.0314 -0.44 -0.0141 -0.2 -0.1600*** -3.14 income 0.0231*** 2.57 -0.0030 -0.43 -0.0001 -0.01 -0.0153** -2.21 -0.0367*** -3.44 -0.0193* -1.89 -0.0148 -1.37 0.0102 0.99 0.0276*** 3.5 car -0.1472*** -3.32 -0.1304*** -4.44 -0.0737*** -2.7 -0.0477* -1.74 -0.0748* -1.86 -0.0544 -1.46 -0.1652*** -3.73 -0.0389 -0.94 -0.0229 -0.71 city -0.0129 -0.2 0.0157 0.31 -0.0174 -0.35 0.0343 0.68 0.0680 0.99 0.1374** 2.15 0.0968 1.4 -0.0482 -0.78 0.0111 0.17 nuclear 0.0709 1.22 0.0285 0.62 0.0431 0.97 0.0301 0.66 0.0440 0.71 -0.0619 -1.04 0.0139 0.22 0.0275 0.5 -0.0320 -0.67 alpin -0.0534 -0.61 -0.0222 -0.38 0.0027 0.05 0.0941* 1.65 0.1786** 2.24 0.1394* 1.79 0.1761** 2.02 0.0814 0.89 0.0053 0.08 ind -0.0920 -1.47 -0.0499 -1.03 -0.1008** -2.12 -0.0582 -1.22 -0.0764 -1.19 -0.1056* -1.67 -0.0157 -0.25 -0.0265 -0.4 0.0585 0.95 transp 0.1270 0.54 -0.1218 -1.42 -0.1972*** -2.32 -0.1638** -2.01 0.0741 0.62 0.0817 0.74 0.2202* 1.85 0.1192 0.96 -0.0490 -0.6 hotel 0.0794 1.22 0.0531 0.3 0.2527* 1.94 0.4131*** 3.28

left 0.2405*** 3.29 0.3171*** 6.66 0.2700*** 5.66 0.2874*** 5.86 0.2061*** 2.71 0.1278* 1.75 0.2259*** 2.89 0.3237*** 4.37 0.0472 0.73 right -0.0666 -0.93 -0.1404*** -2.54 -0.1924*** -3.61 -0.2018*** -3.83 -0.0534 -0.65 -0.0222 -0.28 -0.0514 -0.65 -0.0981 -1.41 -0.0365 -0.62 openessCH -0.0235 -1.1 -0.0131 -0.94 -0.0079 -0.58 -0.0231 -1.61 -0.0617*** -2.98 -0.0352* -1.76 -0.0332 -1.61 -0.0219 -1.04 -0.0313* -1.98 equityCH 0.0208 1.09 0.0429*** 3.26 0.0205 1.6 0.0213* 1.64 0.0455** 2.11 0.0277 1.33 0.0414* 1.95 -0.0165 -0.82 -0.0286* -1.74 jobCH -0.0259 -1.46 0.0161 1.22 0.0138 1.08 0.0150 1.17 -0.0203 -1.02 -0.0304 -1.56 -0.0086 -0.43 0.0242 1.33 -0.0237 -1.48 stateCH -0.0211 -1.17 -0.0185* -1.58 -0.0410*** -3.56 -0.0391*** -3.4 -0.0405** -2.23 -0.0363** -2.06 -0.0380** -2.11 -0.0440*** -2.48 0.0418*** 2.78

* significant at 10% level, ** significant at 5% level, *** significant at 1% level. Marginal effects are those of the determinants on the probability of approval given participation. For the dummy variable, the marginal effect is for a discrete change of dummy variable from 0 to 1

Car ownership appears to be a strong determinant of voting behavior. Indeed, voters with cars appear less favorable not only to measures aiming at restraining traffic but also to increases in the price of gasoline. The impact of car ownership is much less when the energy price increases are smaller (solar initiative, energy conservation package) or remain unknown (green tax reform II). The effect of car ownership is stronger and more significant when political variables are excluded from the estimations.

The number of cars possessed by an individual may be considered as a good predictor of the environmental preferences of citizens since it appears to play no significant role in non-environmental decisions.

As frequently observed by others³⁷, one of the main demographic determinants of voters’ choices on environmental initiatives is education. Highly educated voters are more likely to accept environmental initiatives, especially those aiming at taxing non-renewable energy. However, the effect of education on approval is less significant when the initiative concerns nuclear energy. In the case of the nuclear ban, the inclusion of a quadratic education term appears pertinent. This may reflect the contrary views well-informed voters may share on the ecological consequences of nuclear electricity production.

The variable alpin has the excepted sign. It is positive and significant for the initiatives aiming at taxing fuel energy and thus favoring hydroelectric electricity production. The citizens of alpine cantons did logically not support the green tax reform II initiative, which also intended to tax hydroelectric energy.

However, the voters living in nuclear cantons did not behave differently than others.

The coefficients grasping the influence of a voter’s age are, as expected, significant and negative.

Older voters tend to vote less in favor of the environment in each case. This result is frequent in the literature examining voting behavior on environmental issues. Urban voters are also more likely to support environmental quality, which will give credit to the differential-exposure theory. However, the estimates generally remain not significant. Gender also does not appear to systematically influence the voting decisions even if women are more likely to support traffic restrictions. Finally, cultural differences in Switzerland show that French speakers do not generally vote differently than others (except in the cases of the “traffic halving” and “electricity market liberalization” initiatives).

5.1.2 The political variables

Another question motivating the analysis is to examine if the demand for environmental quality may be grasped by economic and demographic factors only or if it would also require the inclusion of less objective variables such as political preferences.

In order to examine this problematic, we contrast the unrestricted (including the political variables) and the restricted specifications using a likelihood ratio test. For each initiative, the likelihood ratio tests (see table 3.5) reject the null hypothesis that the restricted and unrestricted equations are equal. So adding the political variables significantly enhances the overall fit and the explanatory power of the model. Testing linear restrictions on the political variables also rejects the hypothesis that these variables are null. Thus, political preferences explain a non-negligible part of voting behavior.

37 Thalmann (2004), Kahn (2002), Kahn and Matsusaka (1997) and Deacon and Shapiro (1975)

Political orientation appears indeed the main determinant of voters’ choice. The voters identifying themselves with leftist parties are more likely to approve environmental initiatives. On the contrary, the voters on the extreme right of the political scene are rather opposed to environmental ballot propositions. This dichotomy is found for all environmental propositions but the effects are higher when the environmental initiative would require a sizeable intervention of the states. The political orientation variables also appear to be a strong determinant of voters’ attitudes in non-environmental initiatives. The electricity market liberalization referendum does not fit the conclusion. However, this is not surprising when one considers that both left and right parties share conflicting views within themselves and between cantonal sections.

Table 3.5 Likelihood ratio test

Initiatives/referendum Likelihood ratio test Chi2(12)

Traffic halving (March 2000) 64.74

Solar initiative (Sept. 2000) 86.47 Energy conservation package (Sept. 2000) 76.85 Green tax reform I (Sept. 2000) 72.21 Green tax reform II (December 2001) 104.05 Electricity Market Liberalization (Sept. 2002) 251.91

Nuclear ban (May 2004) 146.28

Nuclear Moratorium (May 2004) 151.81

Motorless Sunday (May 2004) 144.98

UNO membership (March 2002) 88.99

Surplus gold reserve of SNB (Sept. 2002) 292.41

The other political variables, catching voters’ preferences on specific subjects, show less regularity across initiatives and remain in most cases non significant. The only noticeable exceptions are that voters preferring competition to state’s regulation tend to reject environmental initiatives. There is also some evidence that people wishing for a more equitable income distribution favor environmental legislation. It suggests that the environmental protection instruments, in order to enhance their acceptability, should keep state intervention as negligible as possible. In this regard, voluntary approaches and the grandfathering of permits seem to constitute a judicious alternative.