Distributive Conflicts and Willingness to Pay for the Environment

Distributive Conflicts and Willingness to Pay for the Environment1

Antonio M. Jaime-Castillo Universidad de Málaga José M. Echavarren Universidad Pablo de Olavide Javier Álvarez-Gálvez Universidad Loyola de Andalucía

Abstract: According to several studies there is a positive relationship between affluence and willingness to pay for the environment. Previous studies suggest that if environmental quality is a normal good, higher-income individuals would be more willing to pay for environmental protection than lower-income individuals. In this paper we argue that the positive relationship between willingness to pay for the environment and income is the result of a distributive conflict between redistributive taxes and environmental taxes. We test our hypotheses using data from ISSP (Environment III) for a sample of European countries. We use a biprobit multilevel model in order to test the effect of income and other control variables on the willingness to pay taxes for the environment and redistributive taxes. Our results show that rich (poor) individuals are more (less) willing to pay environmental taxes and less (more) willing to pay redistributive taxes. Rich individuals dislike redistributive taxes given that they are net losers from the redistribution game, while they might support higher environmental taxes because the environment is a public good. In addition, other explanatory variables have the opposite effect on the willingness to pay environmental taxes and redistributive taxes.

Keywords: contingent valuation, environment, willingness to pay, income effects, redistribution

1 Draft version. An earlier version of this paper was presented at the III REPS Conference in Pamplona (Spain), 2011. We are grateful to all the participants in the session for helpful comments and suggestions, particularly to Pau Marí-Klose, José A. Noguera, Toni Llácer and Inés Calzada. The usual disclaimer applies. 1 1. Introduction

Environmental issues have grown in importance since the mid-twentieth century. From that time onwards the rise of environmental problems and the development of ecologist movements have spread swiftly across the industrialized world. Environmental problems have become global too, and some authors even consider that ecological crisis threatens modern society itself (Lovelock 2009). Needless to say, societies are part of the problem as well as part of the solution and this is why social scientists become more concerned about environmental behaviors and preferences during the last decades, which in turn will be very important in the design of sustainable policies. In this paper we focus on social preferences for environmental taxation, one of the main tools for green policies. Focusing on taxation rather than in other kind of pro- environmental preferences allows us to connect the preferences for environmental taxes with the whole debate about the fiscal structure of modern welfare states. When we focus on environmental preferences an important question arises: why are individuals willing to pay for the environment and which differences can we find between social groups in regard to this question. From a traditional point of view in economics, paying for the environment does not fit well with an individual rational cost-benefit approach. Why should someone pay for a public good that by definition is non-excludable? The literature offers two different answers to this question: a) some institutional contexts might foster trust and cooperation between rational individuals, enabling them to overcome collective dilemmas (Ostrom 1990); b) following a normative approach it could be argued that people are driven by altruistic motives and choose to follow social norms (Guagnano et al 1994). In this paper we focus more specifically on the question of why some people are more willing than others to pay for environmental goods. Several studies have found relevant differences among social groups with regard to environmental issues (Inglehart 1997; Galtung 1964). Even those authors who focus on the relative homogeneity of environmental concerns throughout society admit that differences do exist and can play a role in contemporary societies2 (Jones & Dunlap 1992). However, a more in-depth analysis is needed by focusing on the factors that explain those differences. In order to shed light on this issue, we identify the factors that help us to explain the differences

2 Although for these authors those differences might be small and decreasing in time. 2 concerning the willingness to pay taxes for the environment as part of the more general distributive conflicts that exist in a particular society.

2. Theoretical overview

Given that we cannot directly measure preferences for public good, when we analyze public goods (such as the environment), we have to use indirect methods such as contingent valuation methods (CVM henceforth). In CVM people are asked how much money they would spend on a certain public good. The method is called contingent because individuals’ valuations are contingent upon the particular hypothetical market described to them (Mitchell & Carson 1989). It was first used in 1947 (by Ciriacy-Wantrup) and after that it has been broadly used (Carson 1994; Jones 2009; Jacobsen 2009) as well as criticized (Diamond & Hausman 1994). Scott summed up his distrust in CVM by pointing out that whenever you “ask a hypothetical question [...] you get a hypothetical answer” (Boyle et al 1994: 65). Nevertheless, some studies have shown that differences between stated and real preferences concerning public goods are not big enough to discard CVM (Johannesson et al 1997). Moreover, when some authors find relevant differences in this regard they claim that “although biased, hypothetical valuation convey useful information about individual’s real willingness to pay” (Botelho & Costa 2002: 995). One of the most widespread critiques of CVM is the so called embedding effect (Diamond & Hausmann 1994), i.e. a scope effect that violates a basic assumption of classic economics: the effect of non-satiated utility so that willingness to pay (henceforth WTP) should be higher for a higher number of that good. The WTP for a lake should be proportionally higher when we take into consideration two lakes and so on. Carson and Mitchell (1993) point out that the embedding effect is not inherent to CVM itself but may be due to flaws in survey design leading to amenity misspecification bias. Carson (1994) reviewed 27 papers and found statistically significant scope effects on WTP in 25 of them, as other authors did before with larger samples (Walsh et al 1992)3. Hanemann argues that some important studies that found embedding effects to be outstanding aren’t fully reliable (Hanemann 1994). As Hanemann puts it, WTP preferences are a stable construct “comparable to the most

3 Hanemann even argues that the embedding effect in WTP is “a myth” (Hanemann 1994: 34). 3 stable social attitudes such as political party identification” (Hanemann 1994: 28) and as such are useful as objects of study. Willingness to pay for the environment has been extensively studied from diverse perspectives. The main approaches identified in the literature may be classified into three categories: the structuralist view, the altruistic approach and the basic economic model. A great deal of the studies belonging to the first group is carried out by sociologists. The structuralist perspective focuses on collective action and attempts to explain WTP as the result of changes in values in modern societies or by the influence of social institutions on social actors. Changes in values regarding environment can be explained by some authors as a reaction to the rise of the environmental damage that took place since the 1950’s in industrial societies (Dunlap et al 1993). Other authors (Inglehart 1997) claim that this cultural shift is the consequence of a change in the priorities order in societies where quality of life and connected issues (such as environmental care) are more valued than more elemental matters (like work or housing). Dunlap (1991), Ivanova and Tranter (2004), or (Jones, 2009) follow this perspective in recent studies. The altruistic approach includes the studies on WTP that highlight the ethical motivation as the main explanation of preferences for public goods. Unlike the structuralist view this approach is individualistic by nature. The explanations of the WTP for the environment are based on choices where individuals do not only care for selfish goals but also for others’ wellbeing. This perspective is found in Normative Economics and Environmental Psychology. The altruistic approach not only deals with warm-glow effects (known as impure altruism) as Aldred (1994) argues. In fact, Johansson (1998) differentiates between seven altruistic alternative motivations for WTP, namely pure altruism, paternalistic (environment-focused) altruism, impure altruism, genuine altruism, altruism towards non-human creatures, commitments, and social norms. Some empirical studies within this approach are Liebe et al (2011), Guagnano et al (1994) or Kahneman and Knetsch (1992). The basic economic model of rational choice is individualistic and considers individual’s choices to be rational (although bounded by individual’s goals and contexts). Jones (2009) identifies three main groups of factors influencing individual preferences in WTP4. 1) Demographic data such as gender, age, level of education, or

4 Jones also includes other aspects like political factors (like involvement of the state in the provision of environmental goods), or issues of collective action (social capital for instance) (Jones 2009: 512). 4 political orientation; 2) Factors which refer to individuals’ attitudes towards the environmental good being valued; and finally, 3) economic factors like income, profession, or employment status. Income has been one of the most important variables in WTP studies (Liebe et al 2011) and it has been broadly used as an explanatory factor (Israel & Levinson 2004; Jones 2009; Jacobsen 2009). Although for several authors income is a poor predictor (Ivanova & Tranter 2004; Israel & Levinson 2004) or some studies don’t find it to be statistically significant (Bulte et al 2005; Hanley 2008) most of the works including income show a significant relation between income and WTP for environment (Witzke & Urfei, 2001; Popp 2001; Jones 2009). In his recent and exhaustive meta-study on the relation of income and WTP for environment Jacobsen states that “we are able to show that, across countries and habitats, there seems to be a significant effect of income on WTP for species and habitat conservation, and that this effect is as well-measured using GDP per capita as self-reported income” (Jacobsen 2009: 150). We can identify several reasons to explain the influence of income on WTP for environment. Probably the most obvious one is budget’s availability. At first sight it makes sense to think that since WTP involves spending money, those who have higher incomes will be more willing to pay (Liebe et al 2011). Veisten et al (2004) add also the substitution effects. “[D]iscretionary budgets are much less than household wealth and income, since many kinds of expenditures are fixed in the short run. This may lead to de facto substitution between different types of goods, since one (hypothetical) purchase can strongly diminish or even eliminate the budgets that were available after covering fixed expenditures. Thus, constrained optimization may explain that some respondents will not pay for, e.g., c after holding b” (Veisten et al 2004). Nevertheless it seems a rather tautological statement explaining positive WTP just by saying that richer people can pay more; this doesn’t mean necessarily that they are more willing to do it. Other authors focus on the nature of the good itself. They show that nature is a normal good (Franzen 2003; Torgler & Garcia 2005; Popp 2001) and we know that “economic theory suggests that if environmental quality is a normal good, all else constant, higher-income households will be more willing to pay for environmental protection than lower-income households” (Ivanova & Tranter 2004 : 8). The nature of the environment as a public good is yet controversial. Some authors argue that environment is a luxury good (Dunlap et al 1993; McFadden & Leonard 1992). This idea is particularly popular among the papers regarding EKC (Auci 2006). Although

5 most of the studies suggest that environment is rather a normal good than a luxury good (Kristrom & Riera 1996) the debate is still unsettled5. Nevertheless, there is consensus in the literature that environment is not an inferior good and it is at least a normal good (Kristrom & Riera 1996: 47), so we can expect a positive relation between WTP for the environment and income.

3. Distributive conflict and environment

Drawing on the previous pieces of literature, the relation between WTP for the environment and income can be explained by means of a redistributive conflict where rich and poor people hold different interests regarding environmental taxation. Rich people would be more willing to pay taxes for environment rather than redistributive taxes because they are net losers from redistributive policies. Poor people, on the other hand, would prefer redistributive taxes for the opposite reasons. This perspective that has been neglected so far help us to explain the relation between income and WTP. In the literature on welfare policies, several studies suggest that potential beneficiaries of redistributive programs are more supportive of taxation policies (Linos 2003). This is why poor people would prefer redistributive taxes rather than environmental ones. In addition, “members of the workforce might fear a rise in unemployment rather than hoping for new jobs being created due to environmental policies” (Witzke & Urfei : 2001). This is a new form of the old rivalry between “reds” and “greens” where the former want development and employment and the others prefer quality of life (whether human or not). We can think of some other reasons that might deepen this cleavage. Some authors argue that working class can perceive environmental policies (such as environmental taxation) as elitist (Morrison & Dunlap 1986). From this perspective, some environmental policies could be interpreted as privileging wealthy residential areas and protecting certain outdoor recreational activities, which are mostly enjoyed by upper class citizens. This approach argue that environmental policies not only favors the rich but also derive costs especially to the least privileged (Morrison & Dunlap 1986: 581). Working class can perceive this distributional impact as regressive (whether being true or not) and distrust environmental taxes. In fact, we can find many examples in

5 Interestingly enough Costa (1997) found that elasticity has been decreasing since XIX century (using data for USA) until reach a punctuation barely above one nowadays. 6 history where environmental policies can be plainly explained as a restriction to crematistic activities of the poor in order to protect recreational activities of the rich (Thomas 1983). Nevertheless, the WTP is not always income elastic. Substitution goods make an important part here. Hence, we can find income elasticity below one in the WTP for particular natural spots rather than environment as a whole (Kristrom & Riera 1996: 52). Sometimes taking care of local environment can be considered a survival issue because. For instance, if drinking water depends on environment protection, or if local jobs in fishery depend on the good quality of water6. In these cases, poor people could prefer environmental taxes rather than redistributive ones. In addition, rich people might have a better chance to escape from local pollution by gaining access to natural resources elsewhere. For instance, poor people may defend the local beach more than richer people who can afford a flight to some expensive resort abroad. Literature belonging to the structuralist perspective supports this fact, pointing out that local environmental interest correlates with materialism (Göksen et al 2001) and that low class correlates with materialism as well (Inglehart 1997). All in all, we should expect a positive relationship between income and the willingness to pay for environmental taxes, while the opposite would be true for redistributive taxes, since the rich are net losers from the game of redistribution. As previously argued, there should be a redistributive conflict about the distribution of taxes. While the rich would prefer environmental taxes the poor would prefer redistributive taxes, as the gain from direct redistribution should be higher than the gains from a better environment. Nevertheless, distributive conflicts are shaped by the particular history of each country and cross-class coalitions that give rise to different policy constellations. For this reason, we select a sample of countries according to the classification of welfare regimes (Esping-Andersen, 1990) in order to test whether the distributive conflicts about environmental and redistributive policies varies across countries. Our sample includes one country from the social-democrat regime (Sweden), one the conservative regime (Germany), one from the liberal regime (United States) and one from the Mediterranean regime (Spain) as depicted by Moreno (1998) and Ferrara (1998). We also include Netherlands as a baseline country in which the willingness to

6 This is the basis of the so called “ecologism of the poor” (Martínez-Alier 2009). 7 pay for environmental taxes is particularly high as compared to other Western. From the previous theoretical overview we derive the following hypotheses: H.1. The willingness to pay taxes for the environment will increase with socio-economic status. H.2. The willingness to support redistribution will decrease with socio-economic status. H.3. The redistributive conflict will be stronger in the social-democrat an conservative regime H.4. The environmental conflict will be stronger in countries where the environmental awareness is stronger.

4. Data and methods

Data and variables

We use two dependent variables from the 2000 Environment II Module of the International Social Survey Programme (ISSP) in order to measure preferences for redistributive and environmental taxes. The first variable was referred to the willingness to pay taxes to protect the environment. The question reads: “And how willing would you be to pay much higher taxes in order to protect the environment?” The available responses were: (1) Very willing; (2) Fairly willing; (3) Neither willing nor unwilling; (4) Fairly unwilling; and (5) Very unwilling. The second variable measures state’s responsibility to redistribute income: “Government should redistribute income from the better-off to those who are less well-off”. The possible responses were: (1) Strongly agree; (2) Agree; (3) Neither agree nor disagree; (4) Disagree; and (5) Strongly disagree. We coded these two variables as dichotomous variables, taking values 1 and 2 as 1 (indicating willingness to pay for the environment and redistribution, respectively). The rest of the values were coded as 0 (indicating unwillingness to support either environmental taxes or redistribution). We include seven independent variables from the same source, which have been used in several studies on environmental economics (Jacobsen 2009; Ivannova 2004; Israel & Levinson 2004; Torgler & García 2005). Our variable of interest is the International Socio-Economic Index of occupational status (ISEI). This index is derived from the International Standard Classification of Occupations (ISCO), and it captures the socio-economic status as a combination of education and income. In this vein, this

8 variable improves the isolated effects of income (for methodological considerations about the computation of this variable, see Ganzeboom et al. 1992). The rest of the variables acting as controls are: gender (1=female; 0=male), age and quadratic age, educational level (number of schooling years), political party affiliation (left-right) and having children (1=yes; 0=no).

Statistical methodology

We assume that willingness to pay taxes for the environment and redistribution

* of individual j can be defined by two latent variables yij , which are a function of two vectors of individual characteristics xj and zj:

* y1j= x jb + e 1 j (4a)

* y2j= z jl + e 2 j (4b)

* * We do not observe yij , but two variables yij taking value 1 if yij > 0 and 0 otherwise. Since, we expect that both the willingness to pay for the environment and redistribution are correlated, we should estimate the two equations (4a) and (4b) simultaneously. We further assume that error terms follow a normal bivariate distribution with mean 0 and:

E(e1) = E( e 2 ) = 0

Var(e1) = Var( e 2 ) = 0

Cov(e1 , e 2 ) = r

The vectors of coefficients (betas and lambdas) are estimated simultaneously by a bivariate probit regression, which takes into account the correlation between error terms in equations (4a) and (4b). Furthermore, this approach allows us to compute simulated probabilities for the willingness to pay for each tax for different values of the explanatory variables. In Figures 1 to 5, we depict these probabilities for each country in the analysis for different levels of socio-economic status holding the rest of the continuous variables at their averages and the dichotomous variables at 0.

9 5. Findings and discussion

In general terms, the willingness to pay taxes to protect the environment is substantially lower than the willingness to support income redistribution by taxes. In Table 2 only 26.5% of the whole sample is willing to pay taxes for environment while 37.6% of individuals think that government should not reduce the differences in incomes. Since the predisposition to pay taxes to reduce inequality is higher that the willingness to pay taxes for the environment, it seems plausible to assume that the willingness to pay for environment is associated to second-order needs. In terms of ecological attitudes, Finland is the country showing the lowest willingness to pay taxes to protect the environment. The percentage of people in favor of paying taxes for the environment is 12.0%. On the contrary, Netherlands shows the highest predisposition to pay for the environment. Indeed, almost half of the individuals in the Dutch sample are in favor of paying taxes for the environment (47.2%). If we compare the countries in the ISSP sample, it emerges that usually the richest countries are those in which the willingness to pay taxes to preserve the environment is higher (Great Britain, United States, Netherlands, Japan…). Nevertheless, this is not a perfect rule, so we can find some exceptions (e.g. Mexico). In this case, we should consider other specific factors, such as cultural influences, ecological risks, previous experiences of ecological disasters, or exposure to environmental degradation. Regarding attitudes towards redistribution, Slovenia is the country with the higher predisposition to support income redistribution by taxes (86.5% of the population in the Slovenian sample thinks that government should redistribute). This country is closely followed by others from Southern European or Mediterranean welfare state regimes like Portugal (83.6%) and Spain (80.4%). On the contrary, Netherlands is the country where redistribution gets the lowest support. Only 29.9% of individuals from Holland think that it is the responsibility of the government to reduce the differences between people with high and low incomes. Finally in the USA, 33.1% of the population is in favor of redistribution.

[TABLE 2 ABOUT HERE]

10 Despite the differences between countries, results are in line with the literature on environmental issues (Israel & Levinson 2004; Ivanova & Tranter 2004; Torgler & Garcia 2005; Jacobsen 2009; Liebe et al. 2011). Once we have controlled for the effect of other variables (i.e. gender, age, education, ideology, and having kids), we can identify different models depending on the disposition to pay for redistributive or environmental taxes that characterize each country. In Netherlands there is a clear environmental conflict. In this country, individuals at the top of the social ladder are willing to pay taxes to protect the environment, while they do not want to pay for redistribution. West Germany is characterized by a distributive conflict about income taxation. Socio-economic status produces statistically significant differences in the willingness to pay redistributive taxes, but not in the case of environmental taxes. Sweden illustrates an analogous pattern, but presenting a higher predisposition to pay redistributive taxes. In Spain, we cannot find evidence of a redistributive conflict about environmental and redistributive taxes, since the socio-economic status does not produce a significant difference in the willingness to pay neither redistributive nor environmental taxes and the probabilities of supporting both environmental and redistributive taxes are relatively similar for individuals from diverse social positions. Finally, the USA is characterized by an environmental conflict. In this country, as in Netherlands, people from high socioeconomic position are the ones who want to pay taxes for the environmental protection. We now analyze each country in more detail. The effect of the socio-economic status on the willingness to pay environmental and redistributive taxes is highly significant in Netherlands (p≤0.05). We can observe a positive slope of the ISEI in the case of paying environmental taxes (0.016), so we can argue the probability to pay taxes for environment increases with income. On the other hand, we can observe the negative effect of the ISEI on the willingness to pay for redistribution. These results are in line the high environmental awareness of Dutch people as highlighted by previous studies (Franzen 2003; Torgler & Garcia 2005). The probabilities of paying for both environmental and redistributive taxes are relatively low (about 0.14) and constant along the socio-economic status ladder. On the other hand, the probability of paying taxes to protect the environment increases with the socioeconomic status. While the probability of paying taxes for the environment is 0.11 for an individual from the lowest socioeconomic status, the probability rises to 0.65 for ISEI 91. Regarding the willingness to support redistribution we observe the opposite trend. Thus whereas a substantial share of the people from low socioeconomic status

11 think that government should reduce the income differences (0.38), the probability decreases to 0.03 for people at the top of the social ladder (ISEI=91). Finally the proportion of people who do not want to pay neither environmental nor redistributive taxes is about 0.40 for lower and middle statuses, falling to 0.21 for the individuals from the highest status.

[FIGURE ABOUT 1 HERE]

In Germany it is possible to find significant statistical differences in the willingness to pay redistributive taxes and depending on the socio-economic status (p≤0.05), but this effect is not significant for environmental taxes (p>0.05). On the other hand, although we do not find significant statistical differences in the willingness to pay for the environment depending on the socio-economic status, the sign of the coefficient is positive. Again the probabilities of paying both redistributive and environmental taxes are below 0.12, falling to 0.07 for individuals from the highest statuses. In addition, the blue line that depicts the association between paying no taxes and socio- economic status, we observe the opposite trend (growing linearly from 0.30 to 0.56). Unlike Netherlands, the willingness to pay for environmental taxes does not show relevant differences by status, though it tends to increase smoothly. However there is a clear cleavage around redistribution. Germans from low socioeconomic statuses are more willing to consider that it is the responsibility of the government to reduce income differences. Hence, in contrast to Netherlands, we can conclude that Germany shows a lower predisposition to protect the environmental resources, while showing stronger differences in the willingness to support redistribution.

[FIGURE 2 ABOUT HERE]

Sweden is a country where people want to pay redistributive taxes to reduce the income differences between persons with lower and higher incomes, while there is a low willingness to pay environmental taxes. We have found significant statistical differences in paying for redistribution (p≤0.05), but not in paying environmental taxes. Although probabilities of paying taxes for the environment increase with status, these differences are too small to be statistically significant. On the other hand, the coefficient for supporting redistribution is significant, which produces a sharp decline in the

12 willingness to redistribute as status increases. The probability of supporting redistribution falls from 0.67 for the lowest status to 0.34 for the highest socio- economic position. At the same time, the willingness to pay no taxes shows the inverse tendency, going from 0.13 to 0.48. Hence we can conclude that Swedes from the highest socio-economic statuses do not want to pay taxes neither to reduce income differences nor to preserve the environmental resources.

As we previously mentioned, in Spain there is not sign of a real conflict between environmental and redistributive taxes. Thus we can say that there is broad agreement about the necessity to reduce income differences while there is cross-class consensus against environmental taxes. In Figure 4 we can see that the willingness to pay for environmental taxes only grows from 0.05 to 0.13 from the bottom to the top of the social ladder, while the willingness to support redistribution decreases from 0.63 to 0.42. Hence, only Sweden can be compared with Spain in terms of preferences for redistribution. On the other hand, the willingness to pay no taxes is moderately low as compared to Netherlands and Sweden, while the predisposition to pay for both environmental and redistributive taxes is higher even form people from high socio- economic positions.

In the United States, the relationship between the socio-economic status and the willingness to pay for environmental is slightly statistically significant (p<0.10), but not in the case of the willingness to pay for redistribution. Here we can find a positive effect of the socio-economic status on the willingness to pay taxes to protect the environment. In general, Americans do not want to pay taxes, neither environmental nor redistributive. The probability of the willingness to paying no taxes is about 0.50, going from 0.53 to 0.46 from the top to the bottom of the social ladder. In addition, the probability of willingness to pay for both reasons is very low. We can compare these results with some European countries to understand how big the differences are. While in countries like Sweden or Spain the probability of supporting redistribution is about 0.60 (0.40 in Netherland) for an individual from the lowest socio-economic status, in

13 the USA this probability is 0.25. On the other hand, the probability to pay for environmental taxes goes from 0.12 to 0.28 from the bottom to the top of social ladder.

6. Conclusions

According to several studies there is a positive relation between affluence and willingness to pay for the environment (Bateman & Langford, 1997; Roe et al, 2001; Witzke & Urfei, 2001; Jones et al, 2009). Some researchers explain this relation considering the Environmental Kuznets Curve that explains how poor countries tend to trade worse environmental quality for more income (Israel et al, 2004; Auci, 2006). As they become richer and more polluted, individuals living in poor countries become more willing to trade income for environmental improvements. Other studies suggest that if environmental quality is a normal good, higher-income people would be more willing to pay for environmental protection than lower-income people (Bateman and Langford, 1997; Witzke & Urfei, 2001). We rather explain the positive relation between willingness to pay for the environment and income as the result of a conflict of redistribution. Rich individuals dislike redistributive taxes given that they are net losers from the redistribution game, while they may support higher environmental taxes because the environment is a public good. Using a bivariate probit analysis, we have found that the probability of the willingness to support redistribution decreases as socio-economic status increases in almost every country. At the same time, the probability of the willingness to pay taxes for the environment decreases as status increases but its effect is only significant for some countries. As Torgler & García (2005) point out “individuals with a higher income have less pressing economic problems and are therefore more willing and able to reduce their standard of living to spend more money on global environmental problems”. Hence, we can confirm hypotheses H1 and H2. Regarding the nature distributive conflicts cross countries we can conclude that the redistributive conflict is deeper in the social-democrat and the conservative regimes, as exemplified by Sweden and Germany in our study. This is because class conflicts that give rise to big welfare states in these countries overcome the salience of environmental conflicts. On the other hand, the environmental conflict seems to be

14 strong in countries where there is a high environmental awareness, such as Netherlands. Interestingly, we have found two rather consensual situations in two different welfare regimes: the liberal and the Mediterranean, as exemplified by the United States and Spain, in which social inequality is relatively high as compared to other Western countries. In the first case, there is a strong consensus against taxes either for environmental or for redistributive purposes because inequality is perceived as a product of fair economic outcomes. In the later case, there is consensus in favor of redistribution, since inequality is perceived as an unfair economic output. Nevertheless, more in-depth research is needed to understand the nature and origins of the particular distributive conflicts that shapes the history of countries with different socio-political structures.

References

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17 TABLES AND FIGURES

Table 1: Descriptive statistics of the variables used in the analysis

Variables Obs. Mean Std. Dev. Min. Max. WTP Taxes 29,260 0.265 0.441 0 1 Equal 29,030 0.624 0.484 0 1 ISEI 20,839 43.009 16.53 16 90 Gender 31,028 0.550 0.498 0 1 Age (Linear) 30,922 45.796 17.089 15 96 Age (Quadratic) 30,922 2389.322 1672.750 225 9.216 Educ. Years 27,772 11.560 3.802 1 70 Ideology 15,807 2.887 0.994 1 5 Kids 26,786 0.396 0.489 0 1

Table 2: Willingness to pay for environmental and redistributive taxes (by country).

Environmental taxes Redistributive taxes Government Government Unwillling to Willing to should NOT should pay pay Country redistribute redistribute West Germany 79,2 20,8 53,0 47,0 East Germany 86,5 13,5 26,5 73,5 Great Britain 67,8 32,2 37,1 62,9 Northern Ireland 79,2 20,8 35,7 64,3 United States 68,4 31,6 66,9 33,1 Austria 80,8 19,2 35,6 64,4 Ireland 65,7 34,3 32,2 67,8 Netherlands 52,8 47,2 70,1 29,9 Norway 77,2 22,8 33,0 67,0 Sweden 80,5 19,5 33,5 66,5 Czech Republic 82,8 17,2 43,8 56,2 Slovenia 67,7 32,3 13,5 86,5 Bulgaria 83,5 16,5 28,0 72,0 Russia 70,1 29,9 25,1 74,9 New Zealand 68,9 31,1 56,9 43,1 Canada 75,9 24,1 48,7 51,3 Philippines 72,5 27,5 50,4 49,6 Israel 70,7 29,3 24,2 75,8 Japan 62,8 37,2 57,7 42,3 Spain 77,8 22,2 19,6 80,4 Latvia 82,8 17,2 36,4 63,6 Portugal 82,9 17,1 16,4 83,6 Chile 70,9 29,1 25,1 74,9 Denmark 72,9 27,1 44,6 55,4 Switzerland 66,5 33,5 41,7 58,3 Finland 88,0 12,0 23,1 76,9 Mexico 65,3 34,7 29,5 70,5 Total % 73,5 26,5 37,6 62,4 International Social Survey Programme 2000: Environment II

18 Table 3: Results of the bivariate probit regression

West United Netherlands Sweden Spain Germany States WTP Environmental taxes ISEI 0.004 0.016*** −0.001 0.007 0.006* (0.006) (0.004) (0.005) (0.007) (0.003) Female −0.087 0.111 0.035 −0.044 −0.151* (0.145) (0.103) (0.134) (0.200) (0.090) Age (Linear) 0.018 0.010 −0.051* 0.089 −0.001 (0.041) (0.024) (0.028) (0.073) (0.015) Age (Quadratic) <−0.001 <0.001 0.001* −0.001 −0.000 (0.000) (0.000) (0.000) (0.001) (0.000) Educ. Years 0.048* 0.023 0.064*** 0.0751** 0.031 (0.028) (0.015) (0.023) (0.030) (0.019) Ideology −0.186** −0.146*** −0.241*** −0.032 −0.202*** (0.085) (0.049) (0.073) (0.118) (0.059) Kids 0.230 −0.017 −0.162 −0.440* −0.091 (0.154) (0.120) (0.160) (0.226) (0.102) Constant −1.575* −1.190* 0.091 −3.702** −0.311*** (0.922) (0.631) (0.708) (1.500) (0.443) WTP Redistributive taxes ISEI −0.013** −0.012*** −0.014*** −0.002 −0.003 (0.006) (0.004) (0.004) (0.007) (0.003) Female −0.174 −0.401*** 0.105 0.302 0.132 (0.133) (0.112) (0.127) (0.208) (0.092) Age (Linear) 0.002 −0.009 −0.028 0.049 −0.028* (0.037) (0.025) (0.028) (0.081) (0.015) Age (Quadratic) −0.000 0.000 0.000 −0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) Educ. Years −0.008 −0.004 0.005 −0.040 −0.019 (0.027) (0.016) (0.021) (0.031) (0.019) Ideology −0.051 0.074 −0.458*** −0.208* −0.375*** (0.079) (0.052) (0.068) (0.121) (0.061) Kids 0.098 −0.057 0.103 −0.514** −0.125 (0.142) (0.132) (0.147) (0.237) (0.102) 0.564 −0.292 2.478*** 0.475 1.824*** Constant (0.812) (0.669) (0.692) (1.573) (0.451) No. Obs. 397 628 480 199 903 0.039 0.082 0.315*** −0.080 0.179*** athrho (0.089) (0.070) (0.098) (0.138) (0.059) 0.0395 0.0815 0.305 −0.080 0.177 rho (0.089) (0.069) (0.088) (0.137) (0.057) Log likelihood −471.923 −763.983 −494.350 −216.975 −1075.598 Notes: ***, **, and * indicate significance level at 1%, 5%, and 10%, respectively. Standard errors in brackets. Source: ISSP, Environment II (2000).

19 Figure 1: Willingness to pay taxes in Netherlands

nl-netherlands 6 . y 4 t . i l i b a b o r P 2 . 0

0 20 40 60 80 100 ISEI

None Redistritution Environment Both

Figure 2: Willingness to pay taxes in Germany

d-w-germany-west 6 . 4 . y t i l i b a b o r P 2 . 0

0 20 40 60 80 100 ISEI

20 Figure 3: Willingness to pay taxes in Sweden

s-sweden 8 . 6 . y t i l i b 4 a . b o r P 2 . 0

0 20 40 60 80 100 ISEI

Figure 4: Willingness to pay taxes in Spain

e-spain 6 . 4 y . t i l i b a b o r P 2 . 0

0 20 40 60 80 100 ISEI

21 Figure 5: Willingness to pay taxes in United States

usa-united states 5 . 4 . y t i l i b a 3 b . o r P 2 . 1 .

0 20 40 60 80 100 ISEI