Insurance, prevention or just wait and see? Public preferences for water management strategies in the context of climate change

Ecological Economics 69 (2010) 2279–2291

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Ecological Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e c o l e c o n

Analysis

Insurance, prevention or just wait and see? Public preferences for water management strategies in the context of climate change Klaus Glenk ⁎, Anke Fischer Socio-Economic Research Group, Macaulay Land Use Research Institute, Craigiebuckler, AB158QH Aberdeen, UK

a r t i c l e

i n f o

Article history: Received 9 November 2009 Received in revised form 22 June 2010 Accepted 23 June 2010 Available online 19 July 2010 Keywords: Adaptation to climate change Flooding Governance Protection motivation theory Random card sorting Willingness to pay

a b s t r a c t Policies in the context of global change involve a high degree of uncertainty, as knowledge about future changes and the effectiveness of potential measures is insufficient. Our study set out to investigate how members of the public evaluate policy options that aim at adaptation to climate change, and more specifically, to reduce the risk from flooding and low flows. We explored how hierarchically structured networks of values and beliefs shape public preferences and attitudes towards two different policies, insurance and a sustainable flood management scheme. In particular, we assessed the role of governancerelated values such as efficiency, solidarity and sustainability that allow individuals to evaluate a policy option even if its outcomes are highly uncertain. To this end, we conducted a survey among members of the Scottish public (n = 1033). Findings from spike models and structural equation modelling suggested that there was general support for both policy measures, with a preference for the sustainable flood management approach. In particular, we found perceived severity of change, trust in government, governance-related values and fundamental values to inform attitudes and willingness to pay (WTP) for policy measures. More specific constructs, such as attitudes, were embedded in contexts of more abstract and situationtranscendent values. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Climate change is predicted to cause major changes in precipitation patterns all over the world (IPCC, 2007). Over the next decades, this will heavily influence riverine water flows and availability of water resources in general; and due to an increasing frequency and severity of extreme events the likelihood of both flooding and low flows will rise even in countries that might be seen as relatively resilient. River flows in the UK are projected to drop significantly in the next decades (Diaz-Nieto and Wilby, 2005; Fowler and Kilsby, 2007; Johnson et al., 2009) with consequences such as hosepipe bans and restrictions on water use, especially in areas that rely on reservoirs and rivers for their water supply. For 2050, flood frequency and flood peaks are predicted to increase in many catchments across the UK, although hydrological responses vary significantly across catchments (Kay et al., 2006). Recent flood events in both England (summer 2007) and Scotland (January 2005) caused serious damage. According to the Environment Agency (2009) the annual cost from flooding in England is estimated at more than £1 billion.

⁎ Corresponding author. Present address: Scottish Agricultural College, Land Economy and Environment Research Group, West Mains Road, Edinburgh, EH9 3JG, UK. Tel.: +44 131 535 4176; fax: +44 131 535 4345. E-mail addresses: [email protected] (K. Glenk), a.fi[email protected] (A. Fischer). 0921-8009/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolecon.2010.06.022

For Scotland, scientists project more extreme high flows in winter and spring especially in the Western part of the country, and higher likelihoods of low flows in summer, especially in the East (Black and Burns, 2002; CRU, 2008; Werrity, 2002). This is predicted to result in an increased flood risk and potential water shortages. Scientists' concerns about changes to rainfall and river flows are mirrored by recent policies such as the Flood Risk Management (Scotland) Act; and similar observations and worries are also expressed in the public discourse as we found in our own qualitative research preceding this study (see Section 3.1). As a consequence, while mitigation of climate change is still being negotiated at international, national and local levels, policymakers and scientists have directed their attention to the adaptation to those changes that seem unavoidable, despite the uncertainties associated with the projections for future climate and its impact on water regimes. In addition, many of the potential adaptation strategies, such as Sustainable Flood Management (SFM; Vis et al., 2003) or non-structural measures (Kundzewicz, 2002), involve further uncertainties, especially with regard to their concrete outcomes (Johnson, 2007) and their costs and benefits. Where the outcomes of policy options are uncertain but there is a strong need for action, the principles underpinning these options might become more important as a basis for decision than their concrete outcomes. For example, in the absence of (or in addition to) specific information on the effects of a policy measure, decision makers might support a particular option because they believe it to be safer, more

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sustainable, or more efficient than the alternative. Indeed, recent research suggests that people endorse (or object to) policies not only because of their anticipated outcomes, but also because of the processes and governance structures involved (Attari et al., 2009; Fischer, 2010). Decisions over policy options tend to include a myriad of aspects that go beyond the quality and quantity of the environmental good in question, and that might include (implicit) evaluations of likelihoods of success (Burghart et al., 2007), perceived efficiency, ethical aspects such as perceived fairness and solidarity (Rodríguez and León, 2004), and the agents and instruments used to achieve outcomes (Johnston and Duke, 2007). However, such attributes of policy options are hardly ever given attention in environmental economic research, and while some stated preference surveys touch upon procedural aspects of policies (Qin et al., 2009) or allow attributes of the policy process to influence utility (Horne, 2009; Johnston and Duke, 2007), only very few explicitly analyse their respondents' perceptions and interpretations of the policy options at stake.1 However, knowledge of these could be useful for policy development as it facilitates a better understanding of the factors that lead respondents to prefer certain options over others. Our study set out to investigate public preferences for two different policy options that aimed to address the same goal, namely to reduce risk from flooding and low flows in the context of climate change. We draw on the idea of cognitive hierarchies (Fulton et al., 1996; Homer and Kahle, 1988) that posits that preferences and attitudes towards concrete behavioural options are embedded in and informed by a hierarchically structured network of cognitions, i.e., beliefs and values. Such networks include cognitions ranging from the abstract (e.g., fundamental values) to the intermediate (e.g., values specific to topic areas; generalized attitudes and value orientations) to the concrete (e.g., behavioural intentions). According to this idea, situation-specific preferences are ultimately informed by a limited number of fundamental, situationtranscendent and relatively stable values and beliefs. These relationships are mediated by cognitions at intermediate levels, such as applied values that address human-environment interactions (Fulton et al., 1996), or social aspects of human life (Fischer, 2010). Social psychological models such as the Theory of Planned Behaviour (Ajzen, 1988) or the Value-Belief-Norm Model (Stern et al., 1999) can essentially be interpreted as cognitive hierarchies. Within this generic framework of cognitive hierarchies, we test the idea that preferences for concrete policy options are informed by more general values. We thus combine psychological constructs reflecting different degrees of abstraction, such as fundamental values (Schwartz, 1996), governance-specific values, and threat and coping appraisal from Protection Motivation Theory (Rogers and Prentice-Dunn, 1997) to improve our understanding of public attitudes towards and preferences expressed as willingness to pay (WTP) for policies to reduce the risk from flooding and low flows in Scotland. These constructs and their interrelationships are analysed using two complementary methods. Spike models (Kristrøm, 1997) are now an established method to estimate WTP distributions in environmental economics. These models allow the analysis of factors that determine both general WTP and the WTP amount; however, they cannot handle information on relations between explanatory variables. Structural equation modelling (SEM), in contrast, has become increasingly popular as a tool to explicitly analyse complex relationships between explanatory factors, as it includes elements of path analysis. With SEM, it is therefore possible to give structure to an explanatory model, and unlike in conventional regression analysis, structures can be made explicit and testable. Studies that used SEM to assess relationships with WTP or preferences for policy options are, so far, relatively rare. Winter and

1 Research on the so-called payment vehicle bias (Mitchell and Carson, 1989) might be considered an exception in this respect: participants in stated preference surveys alter their willingness to pay (WTP) not only dependent on the description of the environmental good, but also in relation to procedural aspects of its provision (e.g., Morrison et al., 2000; Bateman et al., 1996).

Lockwood (2005) applied a SEM to examine relationships between intrinsic, non-use, use and recreational values for natural areas and preferences for the future management of natural areas. Sasaki (2005) analysed the influence of consumers' awareness of food safety and the environment on the evaluation of agri-environmental payment programs. Hidano and co-authors (2005) investigated the effects of “fringe benefits” of participation in contingent valuation mail surveys on the consistency of WTP responses, and Sauer and Fischer (in press) explore the relationships between fundamental values, generalized environmental attitudes and WTP for agri-environmental payment schemes. In contrast, SEM is relatively widespread in environmental psychology (e.g., Fulton et al., 1996; Dietz et al., 2007; Fischer, 2010). Our analysis differs conceptually and methodologically from previous studies. We combine both methods—spike models and structural equation modelling—to obtain precise measures of WTP as well as an understanding of the cognitive hierarchies that underpin WTP. In doing so, we aim to produce a better understanding of public preferences for two different policy options in the context of climate change-related increase in flooding and low flows. Instead of trying to test an exhaustive model that includes a wide range of potentially relevant factors (such as Dietz et al., 2007), we focus on governancerelated values and their embedding in cognitive hierarchies, as perceptions of and values implicit to governance approaches seem to be a highly relevant but under-researched area in (environmental) economics and psychology (Jost, 2006; Fischer, 2010). The cognitive hierarchies addressed in our study include constructs that have been found relevant in previous studies on public support for flood- and climate change-related policies. In the remainder of this article, we first introduce the conceptual framework of our study, including a brief overview of the relevant literature. We then describe our methods and hypotheses, present results obtained through two different, but complementary modelling techniques, and discuss the implications. 2. Attitudes Towards Adaptation to Climate Change and Flooding There is a growing body of literature that addresses public views on and preferences for strategies to reduce flood risk and flood damage (e.g., Kenyon, 2007; Siegrist and Gutscher, 2006). Only recently have such studies started to consider potential influences of climate change on the flood risk itself, but also on public views on such strategies (Botzen et al., 2009), and very little work has been done on policies addressing low river flows and water shortages in non-semiarid countries (Van Vugt and Samuelson, 1999). Using the idea of cognitive hierarchies as a flexible framework, we can now explore the role of a range of factors that have been found to influence situationspecific attitudes and behaviour at different levels of abstraction: beliefs about relatively concrete situations, guiding principles and relatively abstract fundamental values. 2.1. Beliefs: Protection Motivation Theory Constructs from Protection Motivation Theory (Rogers and PrenticeDunn, 1997) and similar models (Laska, 1990) have repeatedly been used to understand behavioural adaptation to flood risk. Protection Motivation Theory was originally developed to investigate how information on threats to personal health can shape individual healthrelated behaviour. As its core, the Protection Motivation Theory includes two constructs, namely (i) threat appraisal, i.e., risk perception, and (ii) coping appraisal, i.e., the perceived efficacy of coping options. Threat is usually assessed as a combination of perceived probability and perceived severity of a hazard. Coping appraisal includes factors such as the perceived efficacy of the response (Rogers and Prentice-Dunn, 1997). In their model of private proactive adaptation to climate change, Grothmann and Patt (2005) argue that risk appraisal and perceived adaptive capacity (coping appraisal) can be important determinants of

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private responses to climate change-related threats. Grothmann and Reusswig (2006) explored the effects of threat appraisal and coping appraisal on adaptive behaviour of tenants and homeowners in a floodprone area in Cologne, Germany. Contrary to expectations, these constructs have often little impact on individuals' adaptive or protective behaviour (Miceli et al., 2008). This might be due to the dominant influence of so-called ‘non-protective’ or maladaptive responses, i.e., avoidance and wishful thinking (Grothmann and Reusswig, 2006; Grothmann and Patt, 2005), or to the lack of emotional components in traditional measures of risk perception: Miceli et al. (2008) found the degree of worry about flooding consequences to be more closely related to an index of protective behaviour than the perceived likelihood of these consequences. Such appraisals are essentially beliefs about relatively concrete situations that are likely to vary between individuals. For example, while some individuals might hold positive beliefs about the efficacy of publicly provided flood protection (Grothmann and Reusswig, 2006), others might not. In our study, we examine how generic, less situationspecific views on basic guiding principles for policy-making influence policy preferences, and how these effects are mediated through coping and threat appraisal. 2.2. Guiding Principles for Policy Making Guiding principles can be seen as values held by individuals and groups that provide normative information about the ‘right’ and the ‘good’, applied to generic areas of human life such as human–nature interaction, public policy, or family life. In the cognitive hierarchy, they can be conceptualised as located between very concrete preferences and beliefs, and very fundamental and abstract values (Fulton et al., 1996). For example, Fulton and co-authors (1996) introduce the concept of two main dimensions of wildlife value orientations, namely utilitarianism and mutualism, which are rooted in fundamental values and shape concrete beliefs and behaviours. In their research about public attitudes towards biodiversity management options, Fischer and van der Wal (2007) identified ‘striving for a balance in nature’ and ‘naturalness’, i.e., interfering with nature as little as possible as principles that guided people's preferences for management options. Baron (2006) mentions similar principles with regard to public views on climate policy, for example, the idea that ‘natural’ changes are more acceptable than anthropogenic ones, and that humans have the responsibility for anthropogenic changes and should act accordingly. However, Baron (2006) dismisses these principles (e.g., ‘the polluter pays’ principle) as ‘biases’. In contrast, we argue that we need to take such guiding principles seriously and understand the roles that they play in the worldviews of decision makers, their scientific advisors and constituencies alike, if we are to understand how policy options are created, and how they are supported (or not) by the general public. In particular, there is a need to understand how people make sense of and value different approaches to governance, i.e., the processes and mechanisms implied in policies rather than merely the intended outcomes (Banducci et al., 1999; Fischer, 2010). Little empirical work has been done on this so far. The governance-related values of our study are thus derived from our own qualitative pre-studies (see Section 3.1). 2.3. Fundamental Values Fundamental values are often seen as the most abstract, basic and enduring levels of cognitive hierarchies, providing direction—whether implicitly or explicitly—for more concrete values, beliefs and attitudes, and ultimately choices (Homer and Kahle, 1988). Such values are often operationalised following Schwartz's (1996) postulate of two key dimensions of values that are orthogonal to each other, namely (i) self-enhancement as opposed to self-transcendence, and (ii) openness to change as opposed to the desire to conserve the current situation. The values encompassed by the idea of self-transcendence, such as

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benevolence and universalism, reflect concern for the welfare and interests of others. In contrast, those values representing self-enhancement, such as power and achievement, emphasise personal success and the enhancement of one's own social position, and are seen to be diametrically opposed to values of self-transcendence (Schwartz, 1996). Dietz and co-authors (2007) explored the links between such values and support for eight different climate change mitigation policies, predominantly the introduction of new taxes. They found that respondents who scored high on values of the self-transcendence cluster were significantly more likely to hold environmentalist beliefs, trust in environmental organisations, and express an ‘awareness of bad consequences’ of climate change. In contrast, higher scores for self-enhancement values correlated positively with higher trust in the industry and government agencies. However, while Dietz et al. (2007) tested a wide range of potentially relevant variables that link outcome-related values and views on climate change to support for policy options, we learn very little about how these policy options were perceived by the general public. This seems to be a general deficit in much of the literature on policy preferences: While many studies aim to explain variation in public support for policy options (Togridou et al., 2006; Bernath and Roschewitz, 2008; Spash et al., 2009), they do not necessarily contribute to a better understanding of the reasons why some policy options are supported, while others are not. The present study aims to address this question, and thus explores both people's policy ideals and their beliefs about concrete policy options in relation to these ideals. 3. Methods 3.1. Study Design: Adaptation Options to Changes in River Flows The process of survey instrument development was informed by eight focus group discussions on issues of water management, held in 2007 across Scotland with randomly selected members of the general public. Two key insights were gained from these discussions: First, it was striking how participants emphasised the role of governance in water management. Second, there was a widespread concern about the future of water management in the context of climate change. Our study addresses both of these concerns. Early versions of the scenario description were developed based on peer-reviewed and grey literature and expert advice, and discussed in two additional focus groups. A draft questionnaire was then qualitatively pre-tested with respondents from a range of different backgrounds. A quantitative pilot study (n = 106) with a random sample of the general public led to further refinement of the survey design, for example with respect to the wording of questions and the payment range offered in the contingent valuation exercise. The aim of the study was to investigate public preferences for policies that facilitate adaptation to changes in river water flows induced by a changing climate. Survey participants were thus given information on projections of future river flows in Scotland and their potential consequences, focusing on increased seasonal risks of both flooding and low flows (see Appendix). In addition to a ‘do-nothing’ option, two policy options were presented to address these increased risks, proposing a public ‘water and climate change fund’ that could be used to support (i) a soft engineering scheme and/or (ii) an insurance scheme for councils. The soft engineering option reflected recent policy developments in Scotland, such as the Flood Risk Management (Scotland) Act, which appears to be moving towards supporting a greater role for Sustainable Flood Management (SFM). SFM tools include soft engineering solutions such as creating wetlands and restoration of forest areas upstream. Soft engineering can have positive impacts on river flows in both wet and dry periods by enhancing the absorptive capacity of a landscape. While policy and public (Kenyon, 2007) support for such measures seems to be strong, there is little evidence available that clearly demonstrates the

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effectiveness of such measures to control or mitigate flooding. Furthermore, time lags between the installation of soft engineering measures and their effect on water flows can be considerable. In combination with the uncertainty of future climate, uncertainties regarding the outcomes of soft engineering approaches are therefore substantial. This makes it impossible to be spatially explicit about the need for and the potential impacts of soft engineering across Scotland. Hence, this option was described as a two-stage process that includes canvassing the need for such measures in river catchments across Scotland and the subsequent instalment of measures in 15 priority catchments. The second option, a council insurance scheme, represented a fundamentally different approach to adapting to changing river flows. In contrast to soft engineering approaches that aim at pre-damage avoidance of flooding, a ‘council insurance’ is concerned with improved post-damage assistance (Scottish Executive, 2004). Using Crichton's risk triangle terminology (Crichton, 1999), soft engineering reduces flood risk by reducing the hazard; a council insurance, by contrast, reduces vulnerability. To implement an insurance scheme, a superfund would be created that provides guaranteed and direct access to funds for councils to restore any damage to public infrastructure and public facilities such as schools, hospitals, roads and bridges. It would cover both damages from floods and low flows, and all Scottish residents would pay into such a fund. Thereby, the burden for those councils heavily affected by floods or water shortages would be limited. Because home insurance covers flood risk for most private and business property in Scotland, respondents were reminded that the council insurance would not cover damage to private property. 3.2. The Sample We employed a two-stage random sampling process to arrive at a sample of Scottish residents age 18 and over. The first stage involved a random draw of 88 from the census output areas in Scotland.2 Within these output areas, starting addresses were randomly drawn. Interviewers of an independent market research company were instructed to follow a random route approach from the starting point (List, 2005) until 12 interviews were completed. Out of a total of 7419 addresses contacted, 3457 replied and 1055 interviews were achieved. The interviews were conducted face to face at people's homes and lasted for approximately 30 min. Overall, our final sample matched the sociodemographic characteristics of the sampled population well. Notable differences are a slightly higher proportion of females (57.5% in the sample versus 52%, Scottish Government, 2008) and people aged 60–74 (27.7% versus 22%). 3.3. Questionnaire Design The questionnaire included constructs from five different levels of a potential cognitive hierarchy (Fig. 1), namely (i) fundamental values, (ii) governance-related values and beliefs, (iii) threat and coping appraisal, (iv) attitudes towards the two policy options and (v) willingness to pay (WTP). We hypothesised the more concrete constructs to be embedded in a cognitive hierarchy of constructs of different degrees of abstraction that inform each other as indicated in Fig. 1. While there is evidence that causal relationships can also run in the opposed direction, for example, when behaviour informs attitudes (Festinger, 1957), we test here, in line with the cognitive hierarchies literature (Homer and Kahle, 1988; Fulton et al., 1996) only influences of the relatively more abstract cognitions on relatively more concrete ones. Direct relationships between all variables are tested; however, for graphical simplicity, Fig. 1 only shows those between neighbouring variables. 2

http://www.statistics.gov.uk/geography/census_geog.asp#ukc.

Fundamental values were assessed by means of the new version of the Schwartz Value Survey (ESS, 2008) and captured all four types of values: openness to change, conservation, self-transcendence and self-enhancement. In a Confirmatory Factor Analysis (CFA) that included all 16 items, self-transcendence and conservation showed a strong covariance. We thus decided to model the two value types as one: five indicator variables covering both value types were included in subsequent modelling steps (Table 1). This latent variable did not only consist of typical self-transcendence values such as the desire to help and to be loyal, but also of values that represented the importance of tradition, safety and conformity. As these values are psychologically closely related (Schwartz, 1996), it is not surprising that these values formed a consistent latent variable. Two indicators, namely power and success, were used to represent self-enhancement. The items on governance-related values were designed to capture support for general guiding principles for policy making (Table 1). They were derived from our qualitative pre-studies where participants had discussed their views on (good) governance, politicians' and public authorities' behaviour at great length. Five principles, each represented by two items, were rated on a scale from 0 (unimportant) to 10 (absolutely essential). In addition, we asked respondents to identify the two principles they considered most and least important. In line with the findings of Dietz et al. (2007) and Dreezens et al. (2005) who found that self-transcendence and self-enhancement were related to more concrete values, beliefs and preferences in a plausible way, we hypothesised the latent variable that included self-transcendence and conservation to be positively related to the perceived importance of safety, sustainability, solidarity and naturalness, whereas self-enhancement was hypothesised to relate negatively to support for solidarity, but positively to efficiency (Fig. 1). To get a clearer picture of how policy options were perceived by the respondents, we then asked to which degree each of these principles were, in the respondent's view, met by each of the two policy options. Thereby, we obtained scores from 1 (strongly disagree) to 5 (strongly agree) that captured beliefs about the two schemes with regard to each of the five governance-related values. In line with Miceli et al.'s findings (2008), we operationalised threat appraisal as the perceived severity (rather than the likelihood) of a hazard. We used two items each to capture perceived severity of flooding and water shortages (for own person and society, respectively). Despite a strong covariation, perceived severity of floods and water shortages were best modelled as two separate, but interconnected factors in a CFA. As the inclusion of both would lead to multicollinearity, we draw in our models only on perceived severity of future flooding (Table 1). Coping appraisal, i.e., perceived efficacy of a coping option (Rogers and Prentice-Dunn, 1997), was operationalised as trust in government to make wise use of the suggested ‘water and climate change fund’—whether using it for the soft engineering or the council insurance scheme. Attitudes towards policy options were elicited as ratings of perceived usefulness; preferences as willingness to pay (WTP). We hypothesised WTP for either of the schemes to be influenced by perceived severity of future flooding (Miceli et al., 2008) and trust in the local councils (Rogers and Prentice-Dunn, 1997), with higher WTP being related to higher perceived flood severity and trust in councils. Our hypotheses on the role of governance-related values were based on the idea that such intermediate-level should inform related, more concrete cognitions (Fulton et al., 1996): We expected WTP for the soft engineering scheme to be informed by a high perceived usefulness of the measure, and direct and indirect effects (mediated through its perceived usefulness) of the importance of naturalness, solidarity, safety, efficiency and sustainability as governance principles. Of the latter, we expected sustainability and naturalness to play a particularly strong positive role as these were specific characteristics of the soft engineering scheme, while high importance of efficiency could be

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Fig. 1. Theoretical model of hypothesised relationships between fundamental values, governance-related values, threat and coping appraisal, attitudes and preferences for soft engineering and council insurance. Although included in our model, direct paths from the more abstract constructs (left hand side) to the more concrete ones (right hand side) are not all shown here. Signs indicate the sign of the hypothesised relationship.

hypothesised to have a negative impact on support for soft engineering, as its effectiveness can be seen as uncertain to date. Similar relationships were expected for the council insurance, with a particularly strong role of solidarity, as one of the fundamental characteristics of the scheme was solidarity between councils. Additionally, information on a number of standard socio-demographic variables such as age, gender, income and education was collected. The procedure to elicit WTP included the following steps:

monthly payments, to allow respondents to draw comparisons with payments for public services such as the UK council tax. In the remainder of this paper, we refer to WTP estimates derived from the card sorting as ‘WTP-RCS’, and to the explicitly stated maximum WTP elicited after the card sorting as ‘Point-WTP’. The product of Point-WTP and the share of WTP allocated to each scheme were used to arrive at indicative estimates of WTP for each policy option.

1. Respondents were asked whether they were willing to pay in principle (yes/no). Those respondents not willing to contribute financially were asked for their reasons in an open-ended question. 2. If generally willing to pay, they were given the possibility to divide their contribution up between the two options (any proportion possible), or to allocate the entire amount to one single scheme. 3. A contingent valuation (CV) methodology—a modification of the randomised card sorting procedure (RCS; first applied by Carthy et al., 1999)—was used to elicit willingness-to-pay amounts. 4. After the card sorting procedure, respondents were asked in an open-ended question for their maximum WTP, i.e. a point estimate of their WTP.

3.4. Data Analysis

In randomised card sorting, respondents are usually asked to sort shuffled (i.e. ‘randomised’) cards showing amounts of money on stacks that are labelled, for example, “certain to pay”, “certain not to pay” or “unsure” (as in the present study). This allows respondents to express uncertainty about their WTP and produces interval data in contrast to binary (e.g. dichotomous choice) or point (open-ended formats) WTP elicitation methods. RCS has been regarded a promising alternative (Bateman et al., 2002: 384) to the widely applied payment card approach, but applications to date are limited (Covey et al., 2007; Chilton et al., 2004; Smith, 2004 as quoted in Covey et al., 2007). Amounts on the set of 12 cards used in our study ranged from £1 to £300, and intervals between amounts increased with increasing value.3 Values on cards reflected recurring payments into the water and climate change fund over the next 10 years that would be levied together with council tax. To reduce strategic behaviour, it was stated that every Scottish citizen would have to contribute. On the cards, amounts were presented as both annual and 3 Amounts shown on the card were [1,6,12,24,36,48,60,90,120,180,240,300], all in £ year− 1.

The constructs of our cognitive hierarchy model (Fig. 1) and their interrelationships were analysed using two different methods. WTP distributions from interval data as generated by card sorting are often modelled using parametric estimation, for example following the approach taken by Cameron and Huppert (1989). This approach can be extended to explicitly allow modelling both general WTP (yes/no) and WTP amounts in so-called spike models. However, relationships between the determining factors and indirect influences remain veiled, and there is limited scope for these models to deepen our understanding about why respondents preferred one option over another. In this respect, structural equation modelling (SEM) is complementary to models of WTP distributions. SEM has become increasingly popular as a tool to explicitly analyse complex relationships between factors. Here, we make use of the complementary nature of these two approaches to investigate the potential benefits such a ‘dual approach’ to modelling public preferences. This is, to our knowledge, a novel addition to the growing body of environmental valuation literature. 3.4.1. Parametric Estimation of WTP—Spike Model Spike models represent WTP distributions better than conventional methods in cases where distributions are asymmetric and contain a large proportion of zero WTP responses, as they can explicitly model zero responses (Kristrøm, 1997). Spike models are a special case of mixture models that involve a mixture of distributions; in our simple spike model a point mass at zero (‘spike’) and a continuous and increasing function of the logistic type if WTPN 0. Applications of a simple spike approach to CVM data include Hu (2006), Reiser and Shechter (1999), Powe and Bateman (2004) and Yoo and Kwak (2002). We are not aware of any previous applications of a spike model to data from a card sorting procedure. The

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Table 1 Latent variables, their operationalisations, and descriptive results (n = 1033). Construct

Cronbach's α

Self-transcendence/ 1 (very much like me)–6 (not like me at all) conservationa

Please choose the option that shows how much these people are or are not like you. ▪ It is important to them to live in safe and secure surroundings. ▪ It is important to them to be loyal to their friends or family. They want to dedicate themselves to people close to them. ▪ Tradition is important to them. They try to follow the customs handed down by their family or culture. ▪ It's very important to them to help the people around them. They want to care for their well-being. ▪ It is important to them always to behave properly. They want to avoid doing anything people would say is wrong.

n/a

Self enhancementa

▪ Being very successful is important to them. They hope people will recognise their achievements. ▪ It is important to them that people listen to them. They want people to do what they say.

n/a

▪ The major priority of such policies should be to ensure that people are absolutely safe from natural hazards. ▪ The main aim should be to eliminate every risk for the people living in Scotland.

0.772

1 (unimportant)–10 (absolutely essential)

Governance value: solidarity

▪ The major guiding principle for such policies should be solidarity: people should always jointly cope with problems that might affect only a few. 0.822 ▪ Although some problems might affect only a few people, such policies should oblige us all to do our bit to solve them.

Governance value: efficiency

▪ The major guiding principle for such policies should be that they are cost-effective, so that absolutely no money is spent unnecessarily. ▪ Such policies should only be put in place if they represent best value for money.

0.729

Governance value: sustainability

▪ The most important principle for such policies is to find solutions that will benefit future generations as well as ours. ▪ The most important principle for such policies is to have a long-term perspective: solutions have to work not only now, but also in the future.

0.662

Governance value: naturalness

▪ It is most important that such policies (e.g., flood management policies) work with nature, rather than imposing man-made solutions. ▪ It is most important that such policies do not interfere with nature, and that they are as unintrusive as possible.

0.753

Threat appraisal

Perceived severity of future flooding 1 (strongly disagree)–5 (strongly agree)

▪ More frequent flooding in Scotland would have serious negative consequences for Scottish society in general. ▪ More frequent flooding in Scotland would have serious negative consequences for me personally.

0.487

Coping appraisal

Trust in government 1 (strongly disagree)–5 (strongly agree)

▪ I trust that the local councils and the Scottish Government will do the right thing with the money of the water and climate change fund. ▪ I think the local councils and the Scottish Government will be competent and effective in implementing a soft engineering or insurance scheme.

0.818

Attitudes towards policy options

Usefulness of policy option 0 (completely useless)– Overall, how useful are these two options for Scottish society compared to the do-nothing option, in your view? 10 (extremely useful) ▪ Soft engineering ▪ Council insurance

a

ESS (2008).

n/a

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Items

Governance value: safety

Definition/response options

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Table 2 Perceptions of policy options: mean and median scores of WTP and beliefs (n = 1033). Point-WTP refers to explicitly stated maximum and includes zero bids. Variable

Mean

Std dev.

Median

Stated Point-WTP (£ hh−1 year−1)

35.22

57.05

1

Stated Point-WTP allocated (£ hh−1 year−1)

Soft engineering Council insurance

22.65 11.50

39.48 24.43

0 0

Usefulness (0–10)

Soft engineering Council insurance

7.26 4.81

2.0 2.5

8 5

Beliefs: safety (1–5)

Soft engineering Council insurance

3.89 2.65

0.9 1.15

4 3

Beliefs: sustainability

Soft engineering Council insurance

3.90 2.89

0.99 1.2

4 3

Beliefs: efficiency

Soft engineering Council insurance

3.72 2.70

0.95 1.03

4 3

Beliefs: solidarity

Soft engineering Council insurance Soft engineering

3.76 3.21 4.06

0.95 1.16 0.88

4 3 4

Safety Sustainability Efficiency Solidarity Naturalness

Trust in government, index from 2 items

8.16 8.75 7.87 7.32 8.17 2.93

1.9 1.5 1.9 2.1 1.7 1.12

8.5 9 8.5 7.5 8.5 3.0

Severity of flooding, index from 2 items

3.42

0.95

3.5

Beliefs: naturalness Governance values/principles (0–10), index from 2 items

log-likelihood function for the WTP distribution was estimated using the maximum likelihood routines available in LIMDEP. In our spike model, psychological constructs and socio-demographic variables can be introduced into both payment principle (WTP yes/no) and RCS (WTP amount) response components of the log-likelihood function. Because covariates can but need not be the same between the two parts, the model allows explanation of variation in both parts simultaneously (Reiser and Shechter, 1999; Hu, 2006). Inclusion of covariates into both functions can be guided by theoretical expectation, overall explanatory power of the model while considering parsimony of the model, and parameter significance. The number of covariates that are theoretically expected to be relevant to the understanding of the variation in stated preferences for an environmental good can be large, and covariates are not necessarily uncorrelated. Consequently, this approach to modelling preferences allows only for incomplete and partial assessments of the overall cognitive structure that is expected to underpin preferences. For this reason, we ran several models that incorporated different levels of the theoretical model shown in Fig. 1. We expected that models with covariates representing less abstract constructs such as attitudes towards policy options contribute more explanatory power to the models than, for example, fundamental values. However, to uncover the full structure of relationships between constructs a more flexible approach to modelling interactions between independent and dependent variables was required.

3.4.2. Structural Equation Model For this reason, we also analysed the data by means of Structural Equation Modelling (SEM), using AMOS 7.0. Structural Equation Modelling combines confirmatory factor analysis with path analysis, and thus allows the modelling of latent (unobservable) variables and their direct and indirect relationships with each other. While we had specific hypotheses for each of the constructs involved, we tested all direct relationships between variables and retained only those in the model that turned out to be significant. As measures of model fit, we considered not only χ2 and its respective significance, which should ideally be greater than 0.05 to

indicate an acceptable model fit,4 but also indices that take model parsimony and sample size (such as RMSEA; Root Mean Square Error of Approximation; values b 0.06 indicate good model fit) or sample size (CFI; Comparative Fit Index, values N 0.95 indicate good model fit; Hu and Bentler, 1999) into account. All standardised regression weights of individual items in relation to their respective latent variables were higher than the threshold of 0.4 used by Thøgersen and Ölander (2006) (Appendix B). Sample sizes used for analysis are n = 1033 for summary statistics presented and the SEM, and n = 983 for the spike WTP models.5 4. Results 4.1. Soft Engineering, Council Insurance and Do-Nothing: Values, Beliefs and WTP Overall, sustainability was on average rated the most important guiding principle for public policies that dealt with adaptation to climate change, followed by naturalness and safety, efficiency, and ultimately solidarity, which was still rated slightly above ‘to be respected as much as possible’ (Table 2; all differences significant p b 0.001, except difference between naturalness and safety; t-tests for paired samples). This prioritisation coincided with the outcomes of an additional ranking exercise: while 46% of the sample ranked sustainability as the most important policy principle, only 7% ranked solidarity highest. In line with this, solidarity was the principle seen by the biggest percentage as least important (38% of the sample). Interestingly, only 14% felt that 4 However, with large samples almost all models produce p-values below 0.05 as already minor divergences between data and model become significant. We thus chose to concentrate here on measure of model fit that take sample size into account (Barrett, 2007). An additional indication of model fit is the ratio between χ2 and df (normed χ2) which should be 2:1 to 5:1 for an acceptable model (Marsh and Hocevar, 1985). 5 For the SEM, missing values were not replaced, but the respective cases were excluded from the sample, reducing the sample size to n = 1033. In addition, inconsistent and implausible responses to the card sorting procedure (e.g. certain to pay higher values when certain not to pay lower ones) were omitted for the spike WTP models, resulting in a sample size for analysis of n = 983.

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Table 3 ‘Spike’ models of WTP distributions for different model specifications reflecting a simple model without covariates (Model 1), different levels of the ‘cognitive hierarchy’ (Model 2– Model 5). Number of observations n = 983. Mean WTP and spike estimated as in Kristrøm (1997). Standard errors of the mean WTP estimates and the spike were obtained using the Delta method (Greene 2008); Significance levels: *** = p b 0.001; ** = p b 0.01; and * = p b 0.05. Model 1 WTP in principle Self-transcendence Self-enhancement Sustainability Solidarity Efficiency Flood severity Trust Usefulness SE Usefulness CI Intercept (participation) RCS response Self-transcendence Self-enhancement Sustainability Solidarity Efficiency Flood severity Trust Usefulness SE Usefulness CI Intercept (WTP equation) Card amount Log-likelihood Degrees of freedom Mean WTP-RCS (£ hh− 1 year− 1) Spike

Model 2

Model 3

Model 4

Model 5

− 0.18 (0.14) 0.03 (0.08) 0.11 (0.11) 0.57*** (0.08) − 0.04 (0.08) 0.62*** (0.08) 0.35*** (0.06)

0.03 (0.06)

0.11 (0.09)

− 2.4*** (0.42)

− 3.09*** (0.32)

0.38*** (0.04) 0.27*** (0.03) − 3.99*** (0.34)

− 0.03 (0.16) 0.05 (0.09) 0.04 (0.15) 0.25* (0.10) − 0.17 (0.11) 0.29*** (0.09) 0.11 (0.07)

2.05*** (0.16) 2.45*** (0.1) 1707.93 3 44.97*** (2.11) 0.492*** (0.016)

2.03*** (0.18) 2.45*** (0.1) 1706.92 7 44.99*** (2.12) 0.492*** (0.016)

efficiency was the most important principle (and 26% ranked it as least important), despite the growing media coverage of the financial crisis at the time of the interviews. On average, the soft engineering scheme was seen as significantly safer, more useful, efficient, sustainable and enhancing solidarity than the council insurance (Wilcoxon's signed-rank test for related samples, pb 0.001), although differences between the two options were probably lowest with regard to the perceived solidarity, where the council insurance was rated relatively highly (Table 2). In line with these beliefs, Point-WTP per household and year allocated to the two policies was significantly higher for the soft engineering scheme, supporting the argument often raised in pre-tests that active ‘prevention’ was preferable over ‘cure’. While the soft engineering scheme received clearly more support, only 12.4% of all respondents (24% of those willing to pay) allocated all the money to one of the options (n=16 to the council insurance; n=113 to soft engineering). Responses to an open-ended question suggested that some participants felt that in an uncertain environment, “hedging one's bets” was the best strategy: “Because then we know that both ways are covered”. Many respondents also argued that they needed to be “fair” to both propositions, and that they wanted to strike a “balance” between both options: “give both a chance”. Among those 49% of the sample that were not willing to contribute to the water and climate change fund, only relatively few expressed ‘protest’ reasons that did not necessarily imply a lack of demand for the good in question (Bateman et al., 2002). For example, only 18% of those not willing to pay stated in response to an open-ended question (multiple responses possible) that they believed that the government could not be trusted in its use of the funds. Responses that alluded to a low perceived value of the fund (and can thus be considered ‘true’ zero WTP responses), such as ‘I don't have any money spare’ (42%) or ‘extra cost is too much’ (28%), were much more prevalent. 4.2. Spike Models Results for different spike model specifications are reported in Table 3. Model 1 is the basic model without covariates, models 2–5

1.58*** (0.55) 2.47*** (0.1) 1659.60 9 43.5*** (2.2) 0.496*** (0.017)

0.66 (0.41) 2.48*** (0.1) 1642.15 7 42.97*** (2.21) 0.493*** (0.017)

0.18*** (0.05) 0.01 (0.03) 0.61 (0.43) 2.49*** (0.1) 1607.44 7 42.69*** (2.27) 0.493*** (0.018)

include variables of different levels of abstraction as illustrated in Fig. 1.6 For all models, the spike was calculated consistently in the range of 0.493–0.496, which corresponded well with the observed fraction of respondents not willing to pay (0.492, i.e., 49.2 %). Mean WTP-RCS (£ household− 1year− 1) varied from £41.4 to £45 per household and year. As expected, effects of covariates varied between the different models (Table 3). Fundamental values (self-transcendence/conservation and self-enhancement) did not have any significant influence on either WTP in principle and RCS amount (Model 2). Due to high multicollinearity, Model 3 included only three of the five governance values, as safety and naturalness tended to be too closely related to each other and to the remaining values.7 In the model that contained solidarity, efficiency and sustainability, only solidarity played a significant role: the more important solidarity was perceived as a policy principle, the higher the likelihood of a positive WTP in principle, and the higher the WTP amount. Threat appraisal (severity of flooding) and coping appraisal (trust in government) were used as covariates in Model 4. All variables had a significant influence on general WTP (yes/no). This was different for the RCS response equation: only flood severity was a significant determinant of WTP amounts. For both equations, the signs were positive as hypothesised: the higher the perceived severity and trust in government authorities to cope with the threat, the higher the likelihood that respondents were willing to pay in principle, and the higher the amounts they were prepared to pay. 6 As suggested by an anonymous reviewer, we tested whether explanatory variables can be treated as interval-scaled (as opposed to ordinal) by applying the Terza (1987) method to the flood severity and trust variables in Model 4. Results were almost identical to those reported in Table 3, suggesting that it is appropriate to treat explanatory variables as interval-scaled in our case. 7 We calculated a spike model that included only safety or naturalness as explanatory variables. None of the variables had an impact on WTP amounts, and only naturalness had an impact on WTP in principle (yes/no), with higher perceived importance of naturalness resulting in a greater likelihood of non-zero WTP.

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Usefulness ratings reflecting attitudes towards policy options (Model 5) were highly significant for both policy options to explain WTP in principle, with higher usefulness resulting in an increased likelihood of expressing non-zero WTP. Interestingly, only usefulness of the soft engineering scheme was a significant factor in explaining RCS response, with higher ratings related to a tendency for a higher WTP. We then assessed if moving from the more abstract to the more concrete in the spike model specifications resulted in overall ‘better’ models according to objective critieria of model fit. One would expect abstract-level covariates to contribute less explanatory power than covariates that are conceptually closer to WTP (Fig. 1). Table 4 summarises the information relevant for such a comparison. Decreasing Akaike (1973) Information Criterion (AIC) values suggested that models that included concrete, conceptually closely related variables (right side of Table 4) were preferable over those that included more abstract and conceptually remote ones (left side of Table 4). We used the Vuong (1989) test to investigate whether these improvements were statistically significant. Moving to more concrete levels in the hierarchy resulted in statistically significant (pb 0.1) improvements. 4.3. A Structural Model of Preferences and Values We then explored the hierarchical structure of these relationships by means of SEM. All constructs in the theoretical model (Fig. 1), namely fundamental values, governance-related values, threat appraisal, trust in government and perceived usefulness of the policy options, were represented in the structural model; however, their exact operationalisation had to be adapted to take multicollinearity into account (Section 3.4.2). The constructs included in the final model and their relationships are summarised in Table 5 and Appendix B. The model had an acceptable model fit (χ 2 = 396.388; DF = 164; p = 0.000, RMSEA= 0.037; GFI= 0.964; CFI= 0.964; see Section 3.4.2) and can thus be considered a useful basis for further analysis. Situation-transcendent, fundamental values, namely self-enhancement and self-transcendence/conservation were, as hypothesised, closely related to governance-related values, but also to threat appraisal and the perceived usefulness of soft engineering (but not of the council insurance) (Table 5, lines 1–8). They had no direct influence on WTP. For example, in line with our hypotheses (Fig. 1), respondents who rated self-transcendence/conservation as particularly important tended to value sustainability and solidarity more, and efficiency less (Table 5, lines 1–3). They were also more likely to consider the soft engineering scheme as useful (line 5). In contrast, those respondents who considered self-enhancement as important showed the opposite tendency and were more likely to consider efficiency as more and sustainability as less important (lines 6, 7). Surprisingly, those respondents who found self-transcendence/ conservation important tended to rate the severity of future flooding incidents as rather low (line 4). This finding is somewhat counterintuitive, but might be due to the fact that this latent variable was not only consisting of typical self-transcendence values such as the desire to help

Table 4 Model selection tests for the spike models n = 983; AIC (Akaike Information Criterion) calculated as described by Genius and Strazzera (2002) divided by the number of observations; Vuong test statistic calculated using a Bayesian Information Criterion (BIC) correction factor as described in Clarke and Signorino (2006); * indicates rejection of the null in favour of the model to the right (negative sign) in each comparison (e.g. Model 3 for a comparison of Model 2 and Model 3) with p b 0.1, ** with p b 0.05.

LogL Df AIC Vuong test statistic BIC corrected

Model 2

Model 3

Model 4

Model 5

1706.92 7 3.49 − 4.22**

1659.60 9 3.39

1642.15 7 3.35 − 2.25**

1607.44 7 3.28

−1.95*

2287

and to be loyal, but also by values that represented the importance of tradition, safety and conformity. Participants for whom self-enhancement was important, in contrast, were more likely to regard the consequences of future floods as severe. The three governance-related values included in the model, i.e., sustainability, solidarity and efficiency, were closely related to each other (Table 5, lines 11, 12, 16), yet clearly discriminant in their relationships with other constructs. For example, respondents who rated efficiency as important tended to distrust the government (line 17), while the opposite was true for respondents who rated solidarity as important (line 13). The latter also ascribed a higher severity to the consequences of future floods. Most interestingly, respondents who valued efficiency highly tended to consider soft engineering as less useful, whereas those who valued sustainability highly tended to consider this option as more useful. As hypothesised (Fig. 1), those who valued solidarity highly were more likely to find the council insurance particularly useful (Table 5, line 15). In addition to the three governance-related values, the two constructs adopted from Protection Motivation Theory, i.e., trust in government as a proxy for coping appraisal, and perceived severity of flooding as a proxy for threat appraisal, were useful to understand attitudes towards the two policy options. The more severe the consequences of future floods were seen, the more useful both policy options were considered. The more trust in government was expressed, the more useful the council insurance was regarded, and to a limited degree also the soft engineering scheme. The usefulness scores for the two policy options were not correlated, indicating that respondents clearly discriminated between them. WTP for both policy options was, finally, directly informed by perceived usefulness of the option, and the perceived severity of future flooding events. The high correlation between the two WTP amounts (standardised estimate= 0.47, Table 5, line 28) did not seem to be due to a person's available budget, as adding an income variable as a direct predictor of the WTP amounts reduced this effect only to 0.45. Overall, relatively little variation in WTP was explained by the variables in the cognitive hierarchy (r2 for WTP council insurance: 0.12; r2 for WTP soft engineering excluding effects from other WTP variable: 0.17). R-square was slightly higher for the usefulness ratings (soft engineering: 0.21; council insurance: 0.17), but it seems that on the whole, the values included in the model were more useful to understand views on the soft engineering scheme than on the council insurance, maybe because soft engineering was easier for the respondents to imagine. 5. Discussion This study set out to investigate how members of the public evaluate policy options that are inherently characterised by high uncertainty, and that differ with regard to their governance approaches. Our findings suggest that there is significant support for investments into measures to adapt to floods and droughts in Scotland, both in terms of the perceived usefulness and WTP. Overall, the soft engineering scheme proposed was preferred over a council insurance scheme. This clear preference might be due to the fact that the soft engineering option affects both public and private goods, while the insurance option was described as covering only damage to public property, as private property is usually covered by the obligatory home insurance. Beliefs that the government would self-insure itself against flood risks may also have contributed to a lower WTP for the council insurance scheme. However, a large part of the respondents opted for financing some of both policy options. These findings, together with the high scores for sustainability as a policy principle are supportive of the increasingly sustainability-oriented direction of Scottish flood management policy. The tendency to support both options instead of expressing lexicographic preferences for only one of them might be due to the inherent uncertainties regarding climate change and the effectiveness of the measures. Facing these uncertainties, investing in a portfolio of options is

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Table 5 Results from structural equation model: paths estimated with standardised estimates (shown as regression weights). Significance values: *** = p b 0.001; ** = p b 0.01; and * = p b 0.05. The model includes all significant relationships between variables. Covariation between two endogenous variables on the same level (e.g., WTP) is modelled through directional paths, but direction is arbitrary. Path from

to

Standardised estimate

p

1 2 3 4 5

Self-transcendence/conservation

Sustainability Efficiency Solidarity Severity flood Soft engineering useful

−0.379 0.107 −0.148 0.236 −0.145

*** ** *** *** ***

6 7 8

Self-enhancement

Sustainability Efficiency Severity flood

0.309 − 0.243 − 0.260

*** *** ***

9 10 11 12 13 14 15

Sustainability

Soft engineering useful Council insurance WTP Sustainability Efficiency Trust government Severity flood Council insurance useful

0.381 0.106 0.349 0.542 0.305 0.482 0.142

*** ** *** *** *** *** ***

16 17 18

Efficiency

Sustainability Trust government Soft engineering useful

0.451 − 0.256 − 0.308

*** *** ***

19 20 21 22 23

Severity flood

Trust government Soft engineering useful Council insurance useful Soft engineering WTP Council insurance WTP

0.140 0.142 0.174 0.222 0.210

* *** *** *** ***

24 25

Trust government

Soft engineering useful Council insurance useful

0.069 0.241

* ***

26

Council insurance useful

Council insurance WTP

0.210

***

27 28

Soft engineering useful Council insurance WTP

Soft engineering WTP Soft engineering WTP

0.230 0.469

*** ***

29

Covariance Self-transcendence/conservation

Self-enhancement

0.266

***

Solidarity

in line with modern economic theory on managing risk in the context of flooding (Aerts et al., 2008). However, in response to an open-ended question participants also gave a range of other reasons for their choices, among them the perceived balance that needed to be struck between two complementary policy options. We argue that such reasons can be considered as guiding principles for policy making (or governance-related values) that people explicitly or implicitly use to evaluate policy options. We explored the role that five of these values, namely safety, naturalness, efficiency, solidarity and sustainability played within cognitive hierarchies in shaping respondents' attitudes and WTP for the two policy options proposed. Our models suggest a clear relationship between three of these values, attitudes and WTP. We therefore hypothesise that, if the actual outcomes of a proposed investment are uncertain, values related to governance approaches and policies might become more important determinants of individual decision making. More research is needed to specifically test this hypothesis. Neo-classical economics and psychology have taken different approaches to analysing preferences. The neo-classical economists' interest is limited to observed choice that would reveal stable and given preferences with no or little reference to the decision process and hence the underlying determinants of behaviour. Psychologists, on the other hand, aim to understand the values and motivations behind choices, not least because preferences are inherently context dependent. In recent years, efforts to apply the insights from psychology to economic theory

have significantly increased. Our study is a contribution to these efforts by combining insights from both disciplines for an improved understanding of people's preferences in the specific context of climate change adaptation. In our study, the idea of cognitive hierarchies provided useful insights into the relationships of fundamental and governance-related values underlying people's attitudes and preferences. Levels in the cognitive hierarchy can be considered to reflect not only a lesser or greater degree of abstraction, but also a gradient of stability of constructs subject to external influences over time. Preferences and attitudes are concretely defined, narrowly linked to the context of the choice at hand and thus most susceptible to external influence and change. Governance-related values are immediately applicable to a specific domain, namely policy options, but reflect more abstract, stable and situation-transcendent principles of decision making. We found that these domain-specific values were embedded in respondents' fundamental values. These are basic guiding principles in people's lives, widely applicable and are said to be least volatile. An extension to our model of cognitive hierarchy would be to analyse how emotions and cognitive engagement with the survey question moderate responses at various levels of the hierarchy (Lienhoop and Fischer, 2009). Knowledge on beliefs and values underlying respondents' preferences is useful for at least two reasons. First, decision makers tend to be interested in concrete statements of policy support, for example in terms

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of WTP or attitudes; however, these are relatively unstable constructs (Whitehead and Hoban, 1999). Responses to our survey might have been influenced by the emerging financial crisis and the heavy flood events that affected England in 2007.8 Repeated surveys and opinion polls are one, albeit costly, option to capture such changes in a descriptive manner. However, we argue that it might be more useful to collect information on more stable beliefs and values to better understand why respondents prefer certain options over others. This knowledge can help to dissect context-related influences from basic principles that are less susceptible to change. Second, an improved understanding of the reasons underlying behavioural statements can also inform the development and assessment of modifications to policy proposals. Such modifications can arise due to technological and scientific progress, but can also be related to politically motivated changes. Methodologically, we used two complementary methods, SEM and spike models. As discussed above, results tended to coincide. This is an encouraging result that suggests the presence of some mutual validation of models. Notable differences between the two models arose due to their complementary nature. SEM allowed the analysis of WTP for the two options separately. It also showed indirect effects and relationships between different constructs of the cognitive hierarchy. The relevance of both value types for the formation of attitudes and preferences would have been completely overlooked had we only used spike models. In contrast, spike models can be used for predictive purposes and cater for the standard requirement to model WTP distributions including uncertainty. Spike models are useful tools to investigate the “if” and “how much” of the willingness to pay for environmental change. As to “why” people are willing to pay, and the structures underlying direct motivations, a more comprehensive model such as SEM is needed. 6. Concluding Remarks The findings of our study are supportive of the sustainabilityoriented direction of Scottish flood management policy. Most respondents opted to allocate some of the funds to both policy options. In our view, policy makers should interpret this as a signal to develop a diversified strategy to respond to expected changes in river flows. Beyond gauging the extent of support for policy options, we aimed to understand better why respondents preferred certain policy options over others. Guiding principles for policy making (or governancerelated values) such as sustainability, solidarity and efficiency played an important role in informing our respondents' choices. Such principles are less susceptible to change over time than more concrete attitudes or expressions of WTP for particular policy options. This is especially relevant for policies that require a long-term approach and might therefore undergo modifications over time, such as those responding to climate change-related increase in risks of flooding and water shortages. Acknowledgments We would like to thank all respondents and all those who contributed to the development of the survey. We are particularly grateful for the ideas and comments on scenario design we received

8 At the time of our survey, two events were heavily covered in the media that may have influenced the survey response: the emerging financial crisis in 2008, and flood events that affected England in 2007. The financial crisis may have impacted on WTP statements, both in principle and regarding WTP amounts. Limited ability to pay was the most frequently mentioned reason for not being willing to contribute financially to either option. We cannot gauge the influence of informational recency related to the flood events in England in 2007. It is conceivable that the rate of those not being willing to pay in principle could have been even higher without recent news on floods, particularly if we consider that only a small proportion of the sample population lived in areas of significant flood risk.

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from Nikki Baggaley, Kirsty Blackstock, Simon Langan and Andy Vinten, and for Manuel Lago's, Wendy Kenyon's and two anonymous reviewers' comments on earlier versions of this manuscript. Bengt Kristrøm and Jackie Potts kindly advised us on spike models. This project was funded by the Scottish Government Rural and Environment Research and Analysis Directorate (RERAD). Appendix A. Scenario description used in the survey

Box A1 Scenario description used in the survey Because of climate change, many researchers expect that in the future winter and spring will become wetter in Scotland. Some areas of the country are likely to become drier in summer The weather might also become much more unpredictable, with more extreme events happening more often. This means that the risk of flooding increases in winter and spring. At the same time, there might be temporary water shortages in summer, particularly if more and more water is being used by agriculture, industries and in households. If we believe that these projections become reality, and that both the risk of flooding and the risk of water shortages will increase in the next 10 or 20 years, there are three ways of dealing with this now: a) risks could be reduced through so-called soft engineering of water flows b) alternatively, local councils could insure themselves against damages from flood and water shortages c) third, Scottish society could decide to do nothing. How could these options work? The Convention of Scottish Local Authorities and the Scottish Government would together implement a ring-fenced ‘Water and Climate Change’ fund. All Scottish residents who pay council tax would contribute, and the money could be used to finance either the soft engineering, or the council insurance, or both. Let's talk about the three options in more detail and start with the soft engineering scheme. Water researchers have suggested to increase the areas of: ▪ woodlands upstream ▪ floodplains along the river, and ▪ wetlands close to the river. In towns and cities, certain measures could improve the control over water runoff. Such soft engineering techniques could serve as a sponge, soaking up excess water and releasing it later. They therefore help to reduce the risk of both flooding and water shortage. A programme would be set up that identifies the need for such buffering measures all across Scotland. Soft engineering measures would then be distributed along those 15 river areas in Scotland with the highest priority. Such measures would be additional to already existing hard engineering solutions such as dams and floodwalls. Given that it is impossible to say exactly how the future climate will look like, it is not possible to quantify the exact reduction of risks at this stage. Let's now turn our attention to the second option, the council insurance. This option consists of the creation of a new ‘superfund’ that would act as insurance for local councils. Such an insurance would provide guaranteed and direct access to funds for councils to restore any damage to public infrastructure and public facilities such as schools, hospitals, roads and bridges. It would cover both damages from floods and low flows.

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• Without this insurance, such costs would have to be borne by the local councils and would be passed on through the council tax only to the inhabitants of those councils affected. • With this insurance, the costs of damages would be spread across all Scottish residents. As home insurances in Scotland do cover flooding damages to private homes, and as businesses are insured separately, this council insurance would cover only damages to public property, and home insurance would still be necessary. Finally, there could be no action taken to address this. Doing nothing would mean that there would be no additional cost to the taxpayer now. Society would have to bear any (potential) cost of an increased risk of flooding and water shortages in the future. This means that taxes might rise, or that money is taken from other sectors such as education and health in order to restore damaged public property. Let's assume that such a water and climate change fund will be created. As we've said, the money from such a fund could be used for; ▪ either the soft engineering scheme; ▪ or the council insurance. ▪ The money could also be divided up so that both options could get funding. Later, we'll ask you specifically how you would like to see the money being spent.

Appendix B. Confirmatory factor analysis within the structural equation model

Table B1 Results from confirmatory factor analysis within the structural equation model (Table 5). Item wording see Table 1. Significance values: *** = p b 0.001; ** = p b 0.01; and * = p b 0.05. Path from 1 2 3 4 5 6 7 9 10 11 12 16 17 19

to

Self-transcendence/ Safety Conservation Loyalty Tradition Helping Conformity Self-enhancement Power Success Sustainability Item 1 Item 2 Solidarity Item 1 Item 2 Efficiency Item 1 Item 2 Severity flood Consequences for Scottish society in general 20 Consequences for me personally 24 Trust government Councils and government will do the right thing 25 Councils and government will be competent

Standardised p estimate 0.624 0.738 0.604 0.679 0.670 0.546 0.818 0.839 0.858 0.784 0.892 0.791 0.723 0.660

*** *** *** *** *** *** *** *** *** *** *** *** *** ***

0.507 0.828

*** ***

0.839

***

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