The Climate Change Confidence Gap Aspirations for Fighting Climate Change and Institutional Trust in Europe

Paul Tromp, ANR 821755 Tilburg University, The Netherlands

First Year Paper Research Master in Social and Behavioral Sciences

Submitted on 28 July 2015 Supervised by prof. dr. Peter Achterberg 8,014 words (excluding abstract, footnotes, tables, figures and reference list)

Abstract: This study examined to what extent a climate change confidence gap was present among the European public (i.e. high aspirations for fighting climate change on the one hand, and low trust in institutions tackling this problem on the other), and if this gap could be explained with theory on anomie, reflexive-modernization, post-materialism, and educational differences. Following anomie theory, it was expected that lower-educated and high anomic individuals had a larger gap than their higher-educated and low anomic counterparts. Following reflexive modernization theory and the post-materialism thesis, the opposite was expected with regard to education. It was also anticipated that individuals with ample institutional knowledge had a larger gap than individuals with little institutional knowledge. In all scenarios, it was expected that this gap came about in a highly modernized context. Data from the Eurobarometer 72.1 (2009) were used, and the final multilevel analyses were conducted on 24,766 respondents from 27 European countries. The results indicated that the gap could not be explained unambiguously with anomie theory. Furthermore, the institutional knowledge hypothesis was rejected. Finally, the findings with regard to education were in favor of reflexive modernization theory and the post-materialism thesis, and simultaneously against theorizing on the role of anomie. Introduction: Between September 2013 and November 2014, the Intergovernmental Panel on Climate Change (IPCC) released the four parts of the Fifth Assessment Report (AR5), currently “the most comprehensive assessment of scientific knowledge on climate change” (IPCC, 2015). Comprising of approximately 5,000 pages, AR5 was reduced to a 30-page summary for policymakers with 21 key assessment findings (IPCC, 2014). The message is loud and clear: economic and population growth since the pre-industrial epoch resulted in “atmospheric concentrations of carbon dioxide, methane and nitrous oxide that are unprecedented in at least the last 800,000 years”, and these emissions are “extremely likely to have been the dominant cause of the observed warming” since the 1950s (IPCC, 2014, pp. 4, emphasis in original). Consequently, “the atmosphere and ocean have warmed, the amounts of snow and ice have diminished, and sea level has risen” (IPCC, 2014, pp. 2). Additionally, cold and warm temperature extremes have decreased and increased, respectively, and heavy precipitation events occurred more frequently in numerous regions (IPCC, 2014, pp. 7). A continuation of emitting greenhouse gases will intensify prevailing risks, give rise to new risks, and will increase the probability of “severe, pervasive and irreversible impacts for people and ecosystems”. Unsurprisingly, substantial reductions in emissions over the next few decades, on the other hand, can restrict the risks of climate change (IPCC, 2014, pp. 8; 13; 17). Implementing such reductions effectively gives rise to considerable technological, institutional, economic and social challenges, and depends on policies and collaboration at all scales: (inter)national, sub-national and regional. Consequently, enabling adaptation and mitigation responses to climate change requires “effective institutions and governance, innovation and investments in environmentally sound technologies and infrastructure, sustainable livelihoods and behavioral and lifestyle choices” (IPCC, 2014, pp. 20; 26; 29). In June 2015, during the G7 Summit in Germany, the leaders of America, Japan, Germany, France, Britain, Canada and Italy responded to IPCC’s AR5 by giving their word to reduce greenhouse gas emissions with 40-70% by 2050 compared to 2010, as recommended by the IPCC. Subsequently, in December 2015, during the Conference of Parties (COP21) in Paris, the G7 is determined to adopt a new global climate protocol (G7 Summit, 2015, pp. 12). Christiana Figueres, executive secretary of the UNFCCC1, however, recently highlighted some

1 United Nations Framework Convention on Climate Change. key issues with regard to the Paris agreement. Two of those key issues entail “whether to include long-range goals in the treaty and how much money will be available to poor countries to combat climate change” (The Economist, 2015; The Carbon Brief, 2015). Over two decades ago, during the UNCED2 in June 1992, the Rio Declaration on Environment and Development was presented. At that time, the 172 participating governments were informed by the IPCC’s First Assessment Report, completed in 1990. Among the 27 principles stated in the Rio Declaration, states would collaborate globally in order to “conserve, protect and restore the health and integrity of the Earth's ecosystem” and “reduce and eliminate unsustainable patterns of production and consumption and promote appropriate demographic policies” (United Nations, 1992a, pp. 2). In addition, also the UNFCCC agreement was signed with one ultimate objective: “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system” (United Nations, 1992b, pp. 4). Thomas Stocker, co-chair of IPCC’s WGI, however, pointed out that in spite of these good intentions, carbon dioxide emissions increased with 57% ever since (Stocker, 2013). In short, for two-and-a-half decades, the IPCC is informing national governments around the world about the potential risks and impacts of human-induced climate change, and provides possibilities for adaptation and mitigation (IPCC, 1998, pp. 1). National governments, on their turn, pledged ever since to fight climate change collectively, but were not able to live up to their promises as pointed out by Stocker in 2013. The preceding events have led to the research question whether the general European public also has high aspirations for fighting climate change, like the IPCC, but is simultaneously convicted that institutions are currently not doing enough to tackle this problem3. In other words, does a climate change confidence gap exist among the European public, and, if so, how can this gap be explained? Exploring such a gap is not entirely new. At least three similar gaps have been investigated in the past, for instance by Norris (2011), Achterberg, Houtman and Derks (2011) and Achterberg (2015). First of all, Norris (2011) scrutinized the democratic deficit, which is a gap between democratic aspirations on the one hand, and democratic satisfaction on the other. The former is “measured by how much people value democratic ideals and reject autocratic alternatives”, while the latter is “monitored by public satisfaction with the democratic

2 United Nations Conference on Environment and Development, or informally the Earth Summit 1992. 3 i.e. they lack trust in institutions fighting climate change. performance of their own country” (Norris, 2011, pp. 5). Subsequently, the deficit results from subtracting aspirations from satisfaction, and this gap was particularly prevalent among the better-educated. Second, Achterberg et al. (2011, pp. 754) found a similar gap with regard to welfare institutions. Specifically, they demonstrated that individuals who suffer from anomie, most often the less well-educated (Srole, 1956; Roberts & Rokeach, 1956; McDill, 1961; Achterberg & Houtman, 2009; Achterberg et al., 2011), support economic egalitarian policies on the one hand (i.e. aspirations), while they reject welfare institutions on the other (i.e. distrust). Consequently, the less well-educated are possibly inclined “to vote for anti-institutionalist neo- right-wing parties attacking the welfare state” in spite of “their preference for economic redistributive policies” (Achterberg et al., 2011, pp. 754). Finally and more recently, Achterberg (2015) examined the science confidence gap, which is a gap that results from subtracting trust in scientific institutions from scientific aspirations. Achterberg (2015) demonstrated that this gap was larger among the less well-educated, and he tested two theoretical perspectives (i.e. anomie and reflexive-modernization) in order to explain these educational differences. In accordance with the welfare state confidence gap (Achterberg et al., 2011), the less well-educated suffer more often from anomie, which not only gives rise to distrust in “scientists and the organizations in which they are embedded”, but simultaneously strengthens “support for abstract scientific principles and the scientific method” (Achterberg, 2015, pp. 2-3). If a gap exists among the European public between aspirations for fighting climate change on the one hand, and trust in institutions tackling this problem on the other, the preceding three studies about the democratic deficit, the welfare state confidence gap, and the science confidence gap are very likely to be rich sources of information to derive theories from. At first sight, it seems that educational differences might play an important role in explaining the climate change confidence gap. Likewise, the aforementioned theoretical perspectives, anomie and reflexive-modernization, might provide additional explanations for the existence of such a gap. In the following paragraphs, both theoretical frameworks will be clarified and connected to level of education. Thereafter, various hypotheses will be derived from these reasons, as well as from related theories such as Inglehart’s post-materialism thesis (Inglehart, 1995). These hypotheses are subsequently tested using data from the Eurobarometer 72.1 (Aug-Sept 2009).

Anomie: The term anomie was first coined by Durkheim (1951 [1897]), conceptualizing it as a form of malaise (Elchardus & De Keere, 2013, pp. 101) and consisting of a pair of opposing Greek expressions: eunomia and anomia. The former indicated “a well ordered condition in a society or state, the latter its opposite”. Together they form a continuum of social integration with a sense of “self-to-others belongingness” on one side, and “self-to-others distance/ alienation” on the other (Srole, 1956, pp. 710-711). Additionally, Durkheim defined anomie as “the feeling of alienation caused by the absence of familiar social norms” (Erickson & Murphy, 2013), or alternatively, as MacIver (1950, pp. 84) has proposed, “the breakdown of the individual’s sense of attachment to society”. “In a word, modern man appeared to be suffering from psychic isolation. He felt alone, cut off, unwanted, unloved, unvalued" (Lasswell, 1952). He feels “threatened by the complexities of the contemporary social and cultural order” (Achterberg, 2015, pp. 7-8) and he perceives this order as “essentially fickle and unpredictable, i.e. orderless, inducing the sense that under such conditions he can accomplish little toward realizing future life goals”. From his point of view, “he and people like him are retrogressing from the goals they have already reached” (Srole, 1956, pp. 712-713). In the literature, anomie is also expressed as a ‘malady of modernity’. According to Zijderveld (2000, pp. 16; 198-201), it is the result of insufficient institutional control and excessive individuality, and it occurs in “abstract, over-bureaucratized, rationalized and formalized” societies in which traditional institutions are no longer able to guide the public with norms, values and meaning. But at the same time, it is exactly this coherence and direction in life where the public yearns for in a complex and rapidly changing world that is difficult to understand and hard to grasp. Furthermore, the emphasis on competitive success in modern capitalistic societies, measured by the purely extrinsic standard of making money, is also a powerful force towards this ‘disease of modern democracy’ (MacIver, 1950, pp. 86-91). Empirical research carried out in Argentina by Muratori, Delfino and Zubieta (2013) has demonstrated that anomie and institutional trust are negatively correlated4. In addition, Burianek (1998) observed in Czech society that a stable trust in government institutions go hand in hand with relatively low levels of anomie. Zijderveld’s (2000) explanation for this coherency is that anomic individuals feel threatened by modern institutions due to their inability to grasp and

4 r = -.282. influence these impersonal, meaningless social forces. Or in Gauchat’s (2011, pp. 755) words, they experience an incapability to shape and control these influential yet abstract bureaucratic systems and experts, causing institutional alienation. Eschatology and apocalypticism are, according to Zijderveld (2000, pp. 17-19), eventual outcomes of this anti-institutional mood. Individuals with eschatological and apocalyptic thoughts and feelings are “preaching the end of time” and “belief in an impending cosmic doom”. This apocalyptic doom is exacerbated by gloomy messages such as: “mankind is destroying its own living conditions”, and we are currently facing “complex and nearly insolvable problems affecting our environment” (Scheepers & Nelissen, 1989, pp. 199). Climate change and its negative corollaries5 can be added to this list of dreary messages. Just as anomie itself, climate change can also be seen as a negative side effect of modernity, because it is largely driven by industrialization, economic growth, and population growth (IPCC, 2014, pp. 4). And just as with modern institutions, anomic individuals might feel threatened by climate change due to its complexity and unpredictably on the one hand, and their perceived inability to grasp and influence this abstract process on the other hand. Consequently, the preceding arguments lead to the expectation that high anomic individuals within the most modernized countries have a larger climate change confidence gap6 than low anomic individuals within these nations. Previous research demonstrated that particularly the less well-educated suffer from anomie. Roberts and Rokeach (1956, pp. 357) and McDill (1961, pp. 241) for example, found a strong negative relationship between anomie and education7. Srole (1956, pp. 715) originally found a correlation in the same direction, albeit slightly weaker, between his anomie scale and a respondent’s SES8. More recently, Achterberg and Houtman (2009, pp. 1661-1662) encountered a nearly identical negative relationship between their anomie scale and education9. Therefore, it is also expected that lower educated individuals within the most modernized countries have a larger climate change confidence gap than higher educated individuals within these nations.

5 Atmospheric and oceanic warming, melting snow and ice, rising sea levels, extreme weather (IPCC, 2014, pp. 2-7) 6 Aspirations for fighting climate change exceed trust in institutions fighting climate change. 7 Srole’s (1956) anomie scale (5 items), education in years of schooling, r = -.51, and r = -.56, respectively. 8 Socio-economic status (SES): equally weighted composite score of respondent’s education and occupation of head of household, r = -.30 9 Srole’s (1956) anomie scale without the first item about the usefulness of writing public officials. Educational level was measured using the highest level attained, r = -.27. Reflexive modernization: The stage of reflexive modernization is defined by Beck (1994, pp. 2-5) as the possibility that progress can turn into self-destruction (i.e. the destruction of the era of industrial society by the victory of Western modernization itself). In this stage, one type of modernity undermines and changes another (i.e. industrial social forms are initially disembedded and subsequently re- embedded by a new type of modernity). These transitions come about stealthily, unwished and unscheduled, and result in the appearance of a risk society. In this phase, institutions become increasingly incapable of overseeing risks10 and keeping society from harm. In other words, they produce and legitimate effects and threats they cannot control. Eventually, when threats such as ecological hazards become problematic in political and social ways, they start to dominate private, public and political conflicts and debates, and will ultimately destroy the foundations of industrial society. Therefore, the notion of reflexive modernization can be understood as a process of self-confrontation. The preceding theory of reflexive modernization provides explanations for why the better educated within the most modernized countries have a larger climate change confidence gap11 than their less well-educated counterparts. First, well-developed cognitive skills are required in order to perceive modernity-induced threats such as climate change since these risks and their potential consequences are profoundly complex and unspecific (De Keere, 2010, pp. 31). In addition, due to the intangibility of these threats, individuals can only become aware of these risks as a result of scientized thought, and not as a consequence of first-hand experience. Therefore, “those groups that tend to be afflicted are better educated and actively inform themselves” (Beck, 1992, pp. 52-53). The explanation12 by Inglehart and Welzel (2005, pp. 32) is in line with the preceding argument. Furthermore, reflexive-modern individuals question the world and circumstances they live in (De Keere, 2010, pp. 29). Again, they are “better educated” and “more knowledgeable than ever” (Beck, Bonss & Lau, 2003, pp. 23). Norris (2011, pp. 130- 132) complements this line of reasoning by stating that due to their well-developed cognitive skills, the better-educated experience less difficulties in absorbing, organizing, and processing

10 i.e. economic and political risks, as well as social and individual risks. 11 i.e. high aspirations for fighting climate change, but simultaneously convicted that institutions are currently “not doing enough” to tackle this problem. 12 “The risks of postindustrial society […] are abstract. They are not based on firsthand experience but require cognitive insight” (Inglehart & Welzel, 2005, pp. 32). political information. In addition, higher education also strengthens political knowledge (including information about the governmental structure), and encourages a more critical stance towards the governance of democracies. Summarized, the better-educated are expected to have a higher level of institutional knowledge than their less well-educated counterparts (Norris, 2011; Beier and Ackerman, 2003; Ackerman, 2000). This simultaneously implies that higher-educated individuals with their higher level of institutional knowledge13, and their more critical stance towards the governance of democracies, become increasingly aware of the incompetence of institutions to monitor and protect industrial society from risks such as ecological effects and hazards (Beck, 1994, pp. 5). Consequently, this will lead to higher levels of institutional distrust among the better-educated. Dalton (2004) already provided preliminary evidence for the preceding statement. He found that over time the better-educated in a range of post-industrial countries have become slightly less trusting of politicians. In addition, Norris (2011, pp. 140) demonstrated that education was positively associated with democratic aspirations, while simultaneously negatively related to democratic satisfaction. Consequently, the effect of education enlarged the democratic deficit.

Post-materialism: An additional explanation for why the better educated would perceive climate change as a serious problem currently facing the world as a whole is derived from Inglehart’s post- materialism thesis (Inglehart, 1995). He states that when nations become wealthier, their inhabitants become less preoccupied with materialistic values14 and more focused on post- materialistic values15. Besides contextual-level wealth, Abramson and Inglehart (1995, pp. 75- 87) demonstrated that individual-level education is also positively associated with post- materialistic value orientations. Specifically, they observed “a consistent tendency for Europeans16 with higher levels of education to be less likely to be Materialists and more likely to be Post-materialists than those with lower educational levels” (Abramson & Inglehart, 1995, pp.

13 e.g. Achterberg (2015, pp. 32) found a positive relationship between level of education and institutional knowledge, r = .42, p < .001. A similar but slightly weaker relationship was found in the present study, r = .153, p < .01. Institutional knowledge, however, was not measured in the same way in the preceding two studies. 14 i.e. economic and physical security 15 e.g. freedom of speech, political freedom, self-expression/fulfillment, quality of life, citizen participation and environmental protection. 16 i.e. Germany, Britain, The Netherlands, France, Belgium, Italy, Denmark, and Ireland (Eurobarometer 1980-1989) 77). Individuals with post-materialistic values are far more likely to (1) highly prioritize environmental protection, (2) exhibit environmental consciousness, and (3) be actively involved in environmental movements, than people with materialistic values (Inglehart, 1995, pp. 57-62). Consequently, aspirations for fighting climate change seem to fit relatively well in the enumeration of post-materialistic goals. Thus, in addition to the cognitive skills that are required to perceive, and acquire information about, modernity-induced threats such as climate change, the better educated are also much more apt to be concerned about environmental problems due to their post-materialistic value orientations, than their less well-educated counterparts. In conjunction with higher levels of institutional knowledge and institutional distrust, it is anticipated that individuals with high institutional knowledge, or a high educational level, within the most modernized countries have a larger climate change confidence gap than individuals with low institutional knowledge, or a low educational level, within these nations.

Hypotheses: In conclusion, there are two opposing theoretical frameworks, anomie on the one hand, and reflexive modernization and post-materialism on the other, from which four contrasting hypotheses can be derived. In all scenarios, aspirations for fighting climate change exceed trust in institutions tackling this problem, resulting in a climate change confidence gap. In addition, both theoretical perspectives presume that this gap comes about in a highly modernized context. On the one hand, following the argument of anomie, it seems plausible that the less well- educated, who suffer most often from anomie, have a larger climate change confidence gap than their well-educated counterparts (Hypothesis 1). Therefore, it is also expected that high anomic individuals have a larger climate change confidence gap than individuals with a low level of anomie (Hypothesis 2). On the other hand, following the perspective of reflexive modernization and post-materialism, it seems reasonable to expect that the well-educated, with their well- developed cognitive skills, high level of institutional knowledge, and post-materialistic values, have a larger climate change confidence gap than their less well-educated counterparts (Hypothesis 3). Therefore, it is also anticipated that individuals with high institutional knowledge have a larger climate change confidence gap than individuals with a low level of institutional knowledge (Hypothesis 4). Data and operationalization: In order to test the hypotheses formulated above, data from the Eurobarometer 72.1 “Poverty and Social Exclusion, Social Services, Climate Change, and the National Economic Situation and Statistics” (Aug-Sept 2009) were used (European Commission, 2009a). For this survey, a multi-stage, random (probability) sampling design was used, and 26,719 respondents (15+ years) from 29 European countries/regions were interviewed. Approximately 1,000 individuals were interviewed in each country/region, except for Luxembourg, Cyprus and Malta (N=500). Also, since no separate contextual-level data were available for Great Britain (N=1000), Northern Ireland (N=300), West Germany (N=1000) and East Germany (N=500), the former two were both recoded into the UK, and the latter two were both recoded into Germany (GESIS, 2012a). The data were gathered through face-to-face interviews in the national language and in the respondent’s residency. Respondents that did not have scores on all the variables below were excluded from the analyses using listwise deletion. However, for the variables that made up the dependent variable, an appropriate multiple imputation technique was performed17, because listwise deletion would have resulted in a valid N=19,783 (74% of the original sample). The final analyses were conducted on 24,766 respondents from 27 European countries which is 92.7% of the original sample. Included countries were: Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, The Netherlands, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, and the United Kingdom.

Dependent variable: Aspirations for fighting climate change were measured with three questions. The first question or variable indicates whether climate change was “mentioned” or “not mentioned” by the respondent as one of the four most serious problems currently facing the world as a whole

17 Imputations = 5, fully conditional specification (MCMC), max. 10 iterations since the patterns of missing values were non-monotone. One aspiration item served as a predictor only because it had no missings at all, while the other seven variables were being predicted and served as predictors at the same time. Individuals who answered “doing too much” or “don’t know” on the trust items received a new valid score (i.e. “trust” or “no trust”) for these items.

(GESIS, 2012a, pp. 734). This variable actually summarizes responses to: “In your opinion, which of the following do you consider to be the most serious problem currently facing the world as a whole? Firstly?” (1 answer only) and “Any others?” (max. 3 answers). Besides climate change, there were nine other valid answer possibilities. The second question, “And how serious a problem do you think climate change is at this moment?” had a scale from 1 “Not at all a serious problem” to 10 “A problem extremely serious” (GESIS, 2012a, pp. 756). The third question indicates whether the respondent believes that “the seriousness of climate change has been exaggerated” (GESIS, 2012a, pp. 773). The four valid answer categories ranged from 1 “totally agree” to 4 “totally disagree”. The highest possible aspirations were found among those individuals with the highest possible scores on these three items. Trust in institutions was measured by asking respondents whether the national government, the European Union, citizens themselves, regional and local authorities, and corporations and industry, are currently “doing too much”, “doing about the right amount”, or “not doing enough” to fight climate change (GESIS, 2012a, pp. 761-769). “Doing about the right amount” could be interpreted as trust, and “not doing enough” as no trust in institutions fighting climate change. “Doing too much” could not be categorized into this dichotomy and was therefore declared missing18. The highest possible trust was found among those individuals with the highest possible scores on these five items. Initially, an exploratory factor analysis was conducted on the eight items above19. Two components with an Eigenvalue > 1 were extracted (Eigenvalue1 = 3.365, 42.1% of variance;

Eigenvalue2 = 1.431, 17.9% of variance). While the trust variables all had high and positive loadings on factor 1 and low and negative loadings on factor 2, the items tapping aspirations all had low and negative loadings on component 1 and high and positive loadings on component 2 (see Table 1). The same simple structure was shown in subsequent post-imputation factor analyses with complete data. For the original, as well as for each imputed dataset, factor scores were saved as variables using the regression method. At this point, only 74% of the respondents received factor scores for the original dataset due to listwise deletion. For the five imputed datasets, however, all respondents received scores for both factors. Subsequently, for each

18 On average, only 1.9% of the respondents indicated that an institution was “doing too much” to fight climate change, so not many cases were lost as a consequence of this recoding. 19 Principal components extraction, Varimax rotation, KMO = .829, Bartlett’s Test, p < .001 Table 1 Factor Loadings for Exploratory Factor Analysis With Varimax Rotation of the 8 Items Constituting the CCCG Items Trust Aspirations Most serious problem currently facing the world as a whole in total: climate change -.028 .731 And how serious a problem do you think climate change is at this moment? -.178 .804 The seriousness of climate change has been exaggerated -.182 .737 Is each of the following currently doing about the right amount, or not doing enough to fight climate change? The national government .837 -.099 The European Union .745 -.121 Citizens themselves .678 -.130 Regional and local authorities .826 -.105 Corporations and industry .731 -.157 Note. Factor loadings > .400 are in boldface. CCCG = Climate Change Confidence Gap

respondent, a mean factor score was computed for each component using the factor scores of the five imputed datasets. Finally, the climate change confidence gap was computed by subtracting the mean factor score of a respondent’s trust in institutions fighting climate change from his or her mean factor score on aspirations for fighting climate change. This new gap variable with a mean of 0 and a SD of 1.39 was then again standardized to become a Z-score with a mean of 0 and a SD of 1. The result of this is that individuals with the highest possible aspirations, but the lowest possible trust, have the highest possible gap (1.48), and respondents with the lowest possible aspirations, but the highest possible trust, have the lowest possible gap (-2.84).

Individual-level independent variables: The individual-level independent variables that were selected for this study are: education and two items measuring anomie. The control variables that were also measured on an individual level are: affluence, age, gender, institutional knowledge and type of community. All the former items were grand-mean centered (i.e. the grand mean was subtracted from all the values of the variable) so that the sample means of the predictor variables were rescaled to zero. Education was measured with “age when finished full-time education” (GESIS, 2012a, pp. 861). The valid answer categories ranged from “up to 14 years” to “22 years and older”. ”Still studying” and “no full-time education” were also valid answer categories. All individuals in the former category (N=2161; 8.1%) were added to the category of their current age, and all individuals in the latter category (N=261; 1%) were added to the first category, “up to 14 years”. The values of the education variable were recoded in a way that they corresponded exactly to its labels. Now, a higher score on this item indicated a higher level of education. Missings due to the “refusal” (0.3%) and “don’t know” (1.2%) categories were quite low for this variable. The first anomie item included the following statement: “You are optimistic about the future” (GESIS, 2012a, pp. 417). The four valid answer categories ranged from 1 “totally agree” to 4 “totally disagree”. A higher score on this item indicated a higher level of anomie (pessimism). This statement was also present in a slightly altered way in previous studies using anomie or societal discontent scales (e.g. Achterberg, 2015; De Keere, 2010). Regarding the second anomie item, the following statement was presented to the interviewees: “You feel left out of society” (GESIS, 2012a, pp. 419). Again, the four valid answer categories ranged from 1 “totally agree” to 4 “totally disagree”. For this item, a lower score indicated a higher level of anomie (left out). Therefore, the answer categories were mirrored, so that a higher score on this item also indicated a higher level of anomie (left out). The correlation between the two anomie items was .277, and the results of a factor analysis demonstrated that both variables had high loadings on the same component. However, a reliability analysis pointed out that it was not possible to compute a sum score due to a Cronbach’s α of .433. Therefore, the two anomie items were taken as separate predictors in the subsequent analyses. Finally, missings due to the “don’t know” category were quite low for both variables (2.1% and 1.7%, respectively). Affluence was measured by asking respondents to describe the situation of their household on a scale from 1 “very poor” to 10 “very wealthy” (GESIS, 2012a, pp. 542). Evidently, a higher score on this variable indicated a higher level of affluence. While wealth related questions are often experienced as confidential information, the proportion of missings due to “refusal” (1.8%) or “don’t know” (1.1%) was still quite low for this sensitive question. The exact age of the respondent was measured with the question: “How old are you?” (GESIS, 2012a, pp. 865). The actual number was coded so that the value equaled the label. All respondents happened to know their age, so there were no missings on this variable. Gender of the respondent was registered as 1 “male” and 2 “female” (GESIS, 2012a, pp. 864), but was recoded into a dummy with 0 “male” and 1 “female”. Institutional knowledge was measured with a variable summarizing the number of correct answers to three economy figures (GESIS, 2012a, pp. 843). Consequently, this variable ranged from 0 to 3 correct answers. First, the respondents were asked to provide the official GDP growth rate of their country’s economy in 2008 from a -5% to +10% range. Second, they were asked to provide the official inflation rate of their country’s economy in 2008 from a -5% to +20% range. Third, the respondents were asked to provide the official unemployment rate of their country in 2008 from a 0% to +20% range (GESIS, 2012a, pp. 820-838). Because only 0.2% of all respondents were able to provide 3 correct answers, this category was merged with the preceding 2 correct answers category. Still, a higher score on this item indicated a higher level of institutional knowledge. All respondents had a valid score on this summary variable. Admittedly, these three questions measure institutional knowledge more generally and economically than specific knowledge on institutions fighting climate change. Ackerman (2000, pp. 78-79), however, shows that knowledge about economics, the American government, and Western civilization are all positively and significantly related to educational level and intelligence, and together with knowledge about American history, and geography, have high loadings on the same civics factor. Beier and Ackerman (2003, pp. 444) also demonstrated that both education and intelligence are positively and significantly correlated with a variety of knowledge scales such as health, current events, and technology. Type of community was measured by asking respondents whether they live in a “rural area or village”, a “small or middle sized town”, or a “large town” (GESIS, 2012a, pp. 870). Subsequently, this variable was dichotomized into 0 “rural area or village”, and 1 “small/middle/ large town” in order to distinguish between a rural and an urban community. Only 0.1% of the respondents did not know in what type of community they resided.

Contextual-level independent variables: The contextual-level independent variables that were selected for this study are: GNI per capita (PPP), mean education, moral relativism, secularization, urbanization and CO2 emissions per capita. Higher scores on these variables indicated a higher level of modernization. Data were collected for the year 2009 unless stated otherwise. The wealth of nations was measured with gross national income (GNI) per capita based on purchasing power parity (PPP) in current international dollars (World Bank, 2015a). Mean education is the aggregated version of “How old were you when you stopped full- time education?” (GESIS, 2012a, pp. 860). This time, the actual age was coded. “No full-time education” was treated as a valid response of zero years of full-time education. Missings due to the “refusal” (0.3%) and “don’t know” (1.2%) categories were quite low for this variable. The final range of this item was 0 to 66 years with which country means were computed and ascribed to each respondent from that particular country with the use of the aggregate function.

Table 2 Factor Loadings for Exploratory Factor Analysis of the 7 Items Constituting the Moral Relativism Scale Items Moral Relativism It is alright to live together without getting married .590 For each of the following statements, do you think it can always/never be justified, or something in between. Homosexuality .773 Abortion .792 Divorce .787 Euthanasia .736 Suicide .665 Prostitution .671 Note. Factor loadings > .400 are in boldface.

A moral relativism scale was constructed with the use of the 2008 European Values Study (EVS, 2011). The seven variables that made up this scale were identical to the seven items that made up the moral relativism scale used by De Keere (2010). Respondents were asked whether or not they justified: abortion, homosexuality, divorce, prostitution, euthanasia and suicide (GESIS, 2010, pp. 32-36). These items had a scale from 1 “never justified” to 10 “always justified”. Higher scores on these variables indicated higher levels of moral relativism. Justification of unmarried parents was measured with the statement: “It is alright to live together without getting married” (GESIS, 2010). The five valid answer categories ranged from 1 “agree strongly” to 5 “disagree strongly”. Answer categories were mirrored so that a higher score on this item indicated a higher level of moral relativism. The results of a factor analysis confirmed 20 that all seven variables loaded high on the same component (Eigenvalue1 = 3.626, 51.8% of variance) (see Table 2), and a reliability analysis with the standardized variables pointed out that

20 Principal components extraction, no rotation, KMO = .877, Bartlett’s Test, p < .001 it was possible to compute a sum score of the seven standardized items (Cronbach’s α = .842). Computing an ordinary sum score for Italy was not possible due to no valid cases for justification of homosexuality. Therefore, the minimum number of valid arguments required was set to six. Eventually, a mean for each country was computed. Secularization was not measured in the Eurobarometer 72.1. Therefore, data from the Eurobarometer 71.2 (May-Jun 2009) were used (European Commission, 2009b). Respondents were asked whether they considered themselves to be a “Catholic”, “Orthodox”, “Protestant”, “Other Christian”, “Jewish”, “Muslim”, “Sikh”, “Buddhist”, “Hindu”, “Atheist”, or “Non believer/Agnostic” (GESIS, 2012b, pp. 695). The first nine categories were recoded into 0 “religious”, and the last two into 1 “non-religious”. “Other (SPONTANEOUS)” (1.4%) and “don’t know” (1.8%) could not be categorized unequivocally and were therefore treated as missings. Finally, a mean for each country was computed. Urbanization referred to the percentage of the total population that lived in urban areas in a country (World Bank, 2015b). Carbon dioxide (CO2) emissions in metric tons per capita are those emissions that mainly stem from the burning of fossil fuels (World Bank, 2015c).

Table 3 Factor Loadings for Exploratory Factor Analysis of the 6 Items Constituting the Modernization Scale Items Modernization GNI per capita based on PPP in current international dollars .835 CO2 emissions in metric tons per capita .578 How old were you when you stopped full-time education? (aggregated) .607 Moral relativism scale .883 Secularization (aggregated) .651 Urbanization (the percentage of the total population that lived in urban areas in a country) .752 Note. Factor loadings > .400 are in boldface. GNI = Gross National Income; PPP = Purchasing Power Parity; CO2 = Carbon Dioxide

The results of a factor analysis confirmed that all six contextual-level variables loaded 21 high on the same component (Eigenvalue1 = 3.170, 52.8% of variance) (see Table 3), and a reliability analysis with the standardized variables pointed out that it was possible to compute a sum score of the six standardized contextual-level variables (Cronbach’s α = .814).

21 Principal components extraction, no rotation, KMO = .620, Bartlett’s Test, p < .001 The descriptive statistics of the climate change confidence gap, all individual-level independent variables, and the modernization scale can be found in Table 4.

Table 4 Descriptive Statistics Variables N MIN MAX M SD Dependent Variable Climate change confidence gap 26.719 -2.84 1.48 0 1.00 Contextual-level Variables Modernization scale 26.719 -7.25 9.47 0 4.32 Individual-level Variables Affluence 25.944 -4.45 4.55 0 1.61 Age 26.719 -33.12 49.88 0 18.52 Anomie: You are optimistic about the future 26.165 -1.21 1.79 0 .87 Anomie: You feel left out of society 26.275 -.61 2.39 0 .83 Age when finished full-time education 26.306 -4.13 3.87 0 2.75 Female 26.719 -.55 .45 0 .50 Institutional knowledge 26.719 -.29 1.71 0 .53 Urban community 26.681 -.65 .35 0 .48 Valid N (listwise) 24.766 Note. All variables are grand-mean centered.

Correlations: At first, correlations were computed between the variables of interest in order to compare these relationships with those found in previous empirical research, and those expected from the theory. In accordance with preceding empirical studies (Srole, 1956; Roberts & Rokeach, 1956; McDill, 1961; Achterberg & Houtman, 2009), the significant correlations in the present study between education and the two items tapping anomie indicated a similar negative relationship22. Also partially in line with theoretical explanations (Zijderveld, 2000; Gauchat, 2011), and previous empirical work (Burianek, 1998; Muratori et al., 2013), one negative correlation23 was found between the factor score of a respondent’s trust in institutions fighting climate change and the two items measuring anomie, partially corroborating the negative relationship between

22 r = -.18 and r = -.15 23 r = -.131, p < .01 and r = -.006, n.s. institutional trust and anomie. Furthermore, between the factor score of a respondent’s aspirations for fighting climate change and the two items tapping anomie, also one negative correlation was found24. These relationships were not in line with the proposition that people who suffer from anomie feel more threatened by climate change than non-anomic individuals. In accordance with previous empirical research (Ackerman, 2000; Beier and Ackerman, 2003; Norris, 2011), a positive correlation25 between education and institutional knowledge was found. A small negative association26 between education and the factor score of a respondent’s trust in institutions fighting climate change was also obtained, a finding that is in line with the work by Beck (1994), Dalton (2004), and Norris (2011). The latter author also demonstrated that education was positively associated with democratic aspirations. In the present study, a small positive correlation27 was also found between education and aspirations for fighting climate change, an outcome that was also expected from Inglehart’s (1995) work. Finally, in Achterberg’s (2015) study, the effects of institutional knowledge on scientific aspirations and trust in scientific institutions were both positive and approximately of the same size28. Also in the present study, small positive correlations29 were found between institutional knowledge and both components of the climate change confidence gap, trust and aspirations, respectively.

Method: Subsequently, multilevel analyses were conducted since the purpose of this study was testing hypotheses that included cross-level interactions. Initially, a one-way ANOVA was performed “to examine the extent to which variation in a Level 1 outcome exists within Level 2 units relative to its variation between Level 2 units” (Heck, Thomas & Tabata, 2013, pp. 10). The ANOVA results provided information about the existence of significant variance in the climate change confidence gap across countries. It appeared that the variance between countries was relatively low (5.8% of the total variance), but nevertheless highly significant30.

24 r = -.008, n.s. and r = -.084, p < .01 25 r = .153, p < .01 26 r = -.014, p < .05 27 r = .082, p < .01 28 b = 1.46, p < .001 and b = 1.57, p < .001 29 r = .022, p < .01 and r = .028, p < .01 30 p = <.001 Subsequently, four successive models were built as suggested by Hox (1995, pp. 15-22). First, a null-model with a random intercept was constructed31 (i.e. climate change confidence gap means vary across countries). Second, all eight lower level explanatory variables were added fixed32. Third, random slopes for individual-level education, institutional knowledge, anomie (pessimistic) and anomie (left out) were included33. Fourth, the contextual-level variable modernization, and four cross-level interactions between modernization and individual-level education, institutional knowledge, anomie (pessimistic) and anomie (left out), were introduced to the model, respectively34. This final model can be summarized with the following equation:

CCC gapij = γ00 + γ10(affluence)ij + γ20(age)ij + γ30(anomie[pessimistic])ij + γ40(anomie[left out])ij

+ γ50(education)ij + γ60(female)ij + γ70(institutional knowledge)ij + γ80(urban community)ij +

γ01(modernization)j + γ31(modernizationj* anomie[pessimistic]ij) + γ41(modernizationj* anomie[left out]ij) + γ51(modernizationj*educationij) + γ71(modernizationj* institutional knowledgeij) + u3j(anomie[pessimistic])ij + u4j(anomie[left out])ij + u5j(education)ij + u7j(institutional knowledge)ij + u0j + εij

Results: From the results presented in Table 5, three important lessons can be learned. First, -2LL was used as an information criterion to examine “the improvement of model fit when comparing two successive (or nested) models” (Heck et al., 2013, pp. 78). In each successive model after the null model, the -2LL reduction was highly significant, indicating model fit improvement each time additional variables were added. Second, in each successive model after the null model, all individual-level variables were significantly related to the gap with the exception of institutional knowledge. While anomie (pessimistic), education, female, and urban community were positively related to the gap, the effects of affluence, age and anomie (left out) were in the opposite direction. Particularly striking was the observed contrast between the two anomie items. Third, all cross-level interaction effects were significant. This implies that the relationship between the

31 Variance components (VC) as covariance type, and Maximum Likelihood (ML) as estimation method, df = 3 32 VC, ML, df = 11 33 VC, ML, df = 15 34 VC, ML, df = 20 level 1 predictors and the climate change confidence gap is contingent upon the level of moder- nization within a country. These results can best be interpreted in conjunction with Figure 1 to 4.

Table 5 Fixed Effects Est. (Top) and Variance-Covariance Est. (Bottom) for Models of the Predictors of the CCCG Level 1 Random Level 2 + Parameter Null Model Model Slopes (VC) Interactions Fixed effects Intercept 0.007729 0.00876 0.005196 0.004992 (-0.046095) (.045206) (.045601) (.044452) Level 1 (individual) Affluence -.014053** -.013405** -.013266** (.004374) (.004379) (.004382)

Age -.001926*** -.001786*** -.001780*** (.000352) (.000353) (.000353) Anomie (pessimistic) .098225*** .101138*** .101149*** (.007865) (.015053) (.013988)

Anomie (left out) -.085606*** -.084603*** -.084828*** (.008188) (.019146) (.017931) Education .031174*** .031048*** .030747*** (.002564) (.003798) (.003501) Female .093015*** .092610*** .092004*** (.012444) (.012412) (.012411) Institutional knowledge 0.000644 0.003604 0.005518 (.011841) (.020351) (.019185) Urban community .036352** .037988** .038632** (.013250) (.013259) (.013264) Level 2 (country) Modernization -.011971 (.009885) Cross-level interactions Anomie (pessimistic) x Modernization .005867† (.003136) Anomie (left out) x Modernization .007128† (.004013) Institutional knowledge x Modernization -.009150* (.004347) Education x Modernization .001836* (.000763) Random parameters Level 2 (country) Intercept .056357*** .054091*** .054844*** .052044*** (.015597) (.015003) (.015256) (.014483) Level 1 (individual) Residual .942417*** .930301*** .919838*** .919842*** (.008158) (.008365) (.008289) (.008289) Anomie (pessimistic) .004348** .003518** (.001637) (.001406) Anomie (left out) .007945** .006734** (.002643) (.002346) Institutional knowledge .006987* .005760* (.003235) (.002825) Education .000202* .000144* (.000095) (.000080) ICC 0.056 0.055 0.056 0.054 R2 within countries 0.013 0.024 0.024 R2 between countries 0.040 0.027 0.077 -2LL 74,350.5 68,600.7 68,454.2 68,437.6 χ2 change 5,749.8*** 146.5*** 16.6** df change 8 4 5 Note. Standard errors are in parentheses. Est. = Estimates; CCCG = Climate Change Confidence Gap; VC = Variance Components; ICC = Intraclass correlation; -2LL = -2*log likelihood; df = degrees of freedom. *** p < .001 ** p < .01 * p < .05 † p < .10 (fixed effects & random parameters). *** p < .005 ** p <.01 (χ2 change).

Figure 1 (above) clearly provides support for the second hypothesis: high anomic individuals within the most modernized countries have a larger climate change confidence gap than low anomic individuals within the most modernized countries. Inhabitants of the least modernized nation, however, always have a higher gap than individuals living in more modernized countries, regardless of how anomic they are. In particular, when the level of anomie is low, there is a large difference in the gap between the least and the most modernized nation, but when the level of anomie is high, the gap is also high, regardless of how modernized a country is.

Figure 2 (above), however, only partially supports the second hypothesis. High anomic people within the most modernized countries do not have a larger climate change confidence gap than low anomic individuals within the most modernized countries. In fact, when the level of anomie is high, the gap is even slightly more negative than when the level of anomie is low. However, when an individual is highly anomic, the gap does become less negative when the nation in which the respondent resides, turns out to be more modernized. Nevertheless, the largest gap can still be found among low anomic individuals within the least modernized countries.

Figure 3 (above) clearly rejects the fourth hypothesis. Individuals with high institutional knowledge within the most modernized countries do not have a larger climate change confidence gap than individuals with low institutional knowledge within the most modernized countries. In fact, when the level of institutional knowledge is high, the gap is even more negative than when the level of institutional knowledge is low. Furthermore, inhabitants of the least modernized nation always have a higher gap than individuals living in more modernized countries, regardless of their level of institutional knowledge. However, the difference in the gap between the least and the most modernized nation is particularly large when the level of institutional knowledge is high. Finally, individuals with high institutional knowledge within the least modernized countries turn out to have the largest climate change confidence gap.

To conclude, Figure 4 (above) is almost identical to Figure 1, and clearly provides support for the third hypothesis: higher educated individuals within the most modernized countries have a larger climate change confidence gap than lower educated individuals within the most modernized countries. This finding simultaneously rejects the first hypothesis. Inhabitants of the least modernized nation, however, always have a higher gap than individuals living in more modernized countries, regardless of their level of education. In particular, when the level of education is low, there is a large difference in the gap between the least and the most modernized nation. On the other hand, when the level of education is high, the gap is always positive, regardless of how modernized a country is, and the difference in the gap between the least and the most modernized nation is much smaller than when the level of education is low. Conclusion and discussion: This study examined whether a climate change confidence gap was present among the European public, i.e. high aspirations for fighting climate change on the one hand, and low trust in institutions tackling this problem on the other. Subsequently, literature on anomie, reflexive- modernization, post-materialism, and educational differences was consulted in an attempt to explain this gap. Following the argument of anomie, it was expected that the lower-educated, who suffer most often from anomie, had a larger gap than the higher-educated. Therefore, it was also anticipated that high anomic individuals had a larger gap than low anomic individuals. Following the perspective of reflexive modernization and post-materialism, the opposite was expected with regard to education, that the higher-educated, with their well-developed cognitive skills, high level of institutional knowledge, and post-materialistic values, had a larger gap than the lower-educated. Therefore, it was also anticipated that individuals with ample institutional knowledge had a larger gap than individuals with little institutional knowledge. Additionally, in all scenarios, it was expected that this gap came about in a highly modernized context. For this study, data from the Eurobarometer 72.1 (Aug-Sept 2009) were used, and the final multilevel analyses were conducted on 24,766 respondents from 27 European countries. In fact, for 55.5% of the original sample, aspirations for fighting climate change exceeded trust in institutions tackling this problem, resulting in a climate change confidence gap. Subsequently, this gap could not be explained unambiguously with theorizing on the role of anomie. While individuals who were pessimistic about the future within the most modernized countries indeed had a larger gap than optimistic people, this was not the case for individuals who felt left out of society. However, for both measures of anomie, a similar pattern was observed: when individuals were optimistic or felt included, there was a large difference in the gap between the least and the most modernized nation, but when people were pessimistic or felt left out, differences in the gap became quite small, implying that when individuals suffer from anomie, the extent to which a country is modernized no longer plays an important role for the size of their gap. The results also indicated that the gap could not be explained unequivocally with reflexive modernization theory either. While the better-educated within the most modernized countries indeed had a larger gap than their less well-educated counterparts, the gap for individuals with ample institutional knowledge within the most modernized nations was in fact even more negative than for people with little institutional knowledge. In contrast with the other three interactions, when individuals lacked institutional knowledge, there was a relatively small difference in the gap between the least and the most modernized nation, but when people had ample institutional knowledge, differences in the gap became quite large, implying that when one has a lot of institutional knowledge, the extent to which a country is modernized suddenly plays a major role for the size of one’s gap, with people residing in the least modernized nation having the largest gap. Finally, while the effect of education provided support for reflexive modernization theory and post- materialism, it did not corroborate the expectation derived from theorizing on the role of anomie. At least three intriguing questions for future research can be asked. First, why do inhabitants of the least modernized countries, in general35, always have a higher climate change confidence gap than individuals living in more modernized nations, regardless of their level of anomie, institutional knowledge or education? Second, why are the interaction effects for the two items tapping anomie not in accordance with each other? In other words, why does the gap indeed become larger as soon as individuals become more pessimistic about the future, but is the gap closing as soon as people feel more excluded from society? Third, why does the gap for people living in the least modernized nation become larger as soon as individuals acquire more institutional knowledge, while the gap for people living in the most modernized country in fact diminishes as soon as individuals become more knowledgeable about institutions? In other words, why do the lines for the least and the most modernized nation in Figure 3 diverge? Finally, while the Eurobarometer 72.1 contained appropriate questions to measure aspirations for fighting climate change and trust in institutions tackling this problem, two separate anomie items had to be used due to unavailability of the 5-item anomie scale originally proposed by Srole (1956), and more recently reduced to 4 items by Achterberg and Houtman (2009). Also, while a moral relativism scale was constructed with EVS 2008 data, subsequently aggregated to the country level, and then adopted in the modernization scale, it would have been superior for this study when this scale could have been constructed with the Eurobarometer 72.1 itself, in order to be able to also measure individual-level “late-modern reflexivity” (De Keere, 2010, pp. 38). Similarly, future researchers could also consider to make use of surveys in which post-materialistic values are measured directly, or in which institutional knowledge is gauged with questions that focus specifically on what institutions currently do to fight climate change.

35 Only individuals who felt completely left out of society had a slightly more negative gap than people from more modernized countries. A final suggestion for research that lies ahead is to investigate the development of the climate change confidence gap over time. It might be a challenge, however, to find successive surveys that contain all the relevant variables that are needed to conduct such a longitudinal study. During the Conference of Parties to be held in Paris by the end of this year, the G7 is determined to adopt a new global climate protocol (G7 Summit, 2015). Similar agreements were made during the UNCED in June 1992, but in spite of these good intentions, carbon dioxide emissions increased with 57% ever since (Stocker, 2013). This implies that institutions have given the impression to the general public to have high aspirations for fighting climate change, but were simultaneously, and to the present day, not able to live up to their promises. This gap was experienced particularly by Europeans who were either highly educated, or pessimistic about the future, regardless of their country of residence, but also by socially integrated, or institutionally knowledgeable individuals from the least modernized European nations.

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