Social capital and willingness-to-pay for coastal defences in south-east England

Ecological Economics 119 (2015) 74–82

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Ecological Economics journal homepage: www.elsevier.com/locate/ecolecon

Surveys

Social capital and willingness-to-pay for coastal defences in south-east England Nikoleta Jones a,⁎, Julian R.A. Clark a, Chrisovaladis Malesios b a b

School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom Department of Agricultural Development, Democritus University of Thrace, Pantazidou 193, Orestiada 68200, Greece

a r t i c l e

i n f o

Article history: Received 16 April 2014 Received in revised form 29 May 2015 Accepted 19 July 2015 Available online xxxx Keywords: Trust Networks Flooding Coastal defences WTP

a b s t r a c t Globally, it is widely acknowledged that constructing hard engineered coastal defences is both financially and environmentally unsustainable. Here we seek to investigate the willingness of residents in rapidly eroding coastal zones to contribute towards the costs of constructing and maintaining such structures. The originality of this paper is that it provides one of the first analyses of the influence of social capital parameters (social trust, institutional trust, social reciprocity and social networks) on respondents' willingness to pay (WTP). Fieldwork for the study was conducted in Romney Marsh, a low-lying coastal area of south-east England. The findings have substantive public policy implications for coastal management. First is that we demonstrate that while social and institutional trust exerts a positive influence on WTP, the presence of social networks militates against WTP. Secondly while the study found 45.6% of respondents were willing to pay an average monthly premium of £3.53, a high level of refusal to pay was evident among respondents. Thirdly even among those respondents willing to pay, disagreement was expressed over the political–administrative level at which a ‘coastal defence tax’ should be collected. © 2015 Elsevier B.V. All rights reserved.

1. Introduction: the role of social capital in willingness to pay for coastal defences Globally, existing practice for coastal management has been to build new or to raise existing hard engineered defences to protect local communities from sea level rise and erosion. In England, hard engineered defences are mainly funded by central government through indirect taxation. However, despite significant recent real-term increases in public expenditure on flood and coastal defences, and the announcement of a new programme of capital works to be completed during 2015–2021 in England and Wales, many central and local authorities cannot find the necessary funds to maintain existing coastal defences needed to protect local communities from flooding and erosion (O'Connor et al., 2010; Schmidt et al., 2013). Annual flooding costs in England are in the region of £1.1 billion; these could rise to as much as £27 billion by 2080 for the UK as a whole (Environment Agency, 2013). Indeed, it has been estimated that just to maintain current levels of flood defence would require spending to increase to over £1 billion per year by 2035 (Environment Agency, 2013).

⁎ Corresponding author at: Faculty of Science and Technology, Anglia Ruskin University, East Road, Cambridge, CB1 1PT, United Kingdom. E-mail address: [email protected] (N. Jones).

http://dx.doi.org/10.1016/j.ecolecon.2015.07.023 0921-8009/© 2015 Elsevier B.V. All rights reserved.

One possible solution could be a hypothecated tax which would fund maintenance and construction of coastal defences, paid by residents of affected communities to supplement national spending on coastal defence infrastructure. This is already under discussion in west Norfolk, although so far no action has been taken (Borough Council of King's Lynn and West Norfolk, 2011). Although local taxes or levies may become increasingly important in future, this topic is significantly under-researched. A few studies for example have sought to evaluate citizens' willingness to pay in relation to climate mitigation and adaptation measures (Longo et al., 2012; Solomon and Johnson, 2009; Zhai and Suzuki, 2009), or to reduce risks from climate change (Veronesi et al., 2014). Furthermore, only one study so far has attempted to gauge how much residents would be willing to pay in order to maintain or reinstate coastal defences in rapidly eroding areas (Landry et al's., 2011 study in the U.S.). To address this significant gap in research, the first question we address here is: how much are citizens in coastal communities willing to pay in order to maintain coastal defences? We consider this question to be extremely timely given the increasing impacts globally of climate change at the coast, and the difficulties facing public authorities in funding the maintenance and enhancement of coastal defences. A second question the paper examines concerns the factors that affect residents' WTP. There is a vast literature focusing on different issues that may affect WTP for natural resource management (see for example Mitchell and Carson, 1989; Yao et al., 2014; Breffle et al., 2015). Recently however, increasing emphasis has been placed on the

N. Jones et al. / Ecological Economics 119 (2015) 74–82

role of social capital in shaping local adaptation and mitigation strategies for climate change in particular (Jones and Clark, 2013; Wolf et al., 2010; Lorenzoni et al., 2007). Building on this work, here we analyse for the first time how social capital influences individuals' WTP for maintaining coastal defences as a means of addressing adverse effects of climate change. Before analysing the links between social capital and WTP, it is important to briefly outline the wider context in which ‘social capital’ has become so popular. Social capital was initially conceptualised by Bourdieu as having significant impacts for individuals' economic and cultural capital (Bourdieu, 1986). Putnam et al. (1993), Coleman (1990) and Portes (1998, 2000) took this work further and analysed how social capital can have multiple benefits at individual and collective level, while also entailing risks, especially when it is developed in closed social groups. Social capital can characterize a community as a whole (Putnam et al., 1993) and can be developed collectively, thereby influencing individual social capital (Coleman, 1990). In this paper we focus on social capital at this individual level, but our analysis also considers the fact that certain parameters of social capital can influence interpersonal relationships and collective activities across whole communities (Putnam et al., 1993; Coleman, 1990; Gui and Sugden, 2005). We focus here on four social capital parameters: social trust, institutional trust, social networks and social reciprocity (Putnam, 2000; Jones et al., 2011; Woolcock and Narayan, 2000). It is proposed that higher levels of social capital lead to greater community resilience to extreme natural events (Munasinghe, 2007), and moreover that social capital has a significant impact on communities' responsiveness to environmental policies (Jones and Clark, 2013). Related research has established relationships between social capital and WTP for environmental policy initiatives, based on the level of citizens' monetary contributions (Halkos and Jones, 2012; Jones et al., 2011). When looking at each social capital parameter, social trust refers to trust towards other people (Uslaner and Conley, 2003). It has been related to natural resource management because of the positive effect it may have on individuals' perceptions of the environmental capacities of fellow citizens (Wagner and Fernandez-Gimenez, 2008). Thus, it is expected that individuals with higher levels of social trust will view more positively the principle of paying for an environmental policy goal due to their belief that other community members will also act collectively, and will similarly be prepared in practice to pay towards the costs of the proposed policy (Jones et al., 2011; Polyzou et al., 2011; Wiser, 2007). Likewise, in communities where a sense of reciprocity is well developed among individuals, it is more likely that community members will act together for ‘the common good’ (Pretty, 2003). Consequently, a positive influence on WTP can be expected in communities where strong social reciprocity that is supportive of environmental values is promoted (Halkos and Jones, 2012; Polyzou et al., 2011). Trust in public institutions is also expected to have a significant impact on WTP. Existing studies demonstrate that both the intention and WTP of individuals are significantly determined by the level of trust in the proposed management body, or the public authority that will manage the payment vehicle (Krystallis and Chryssohoidis, 2005; Meyerhoff and Liebe, 2006; Whitehead and Cherry, 2007). Consequently institutional trust has been positively related with the financial contribution of individuals to climate change policies (Glenk and Fischer, 2010). So it is expected that in communities with individuals who trust public institutions, there will be a greater willingness to pay due to a shared community belief that the management body will be effective, and will use monies prudently and appropriately. Finally, there are different types of networks that have a significant impact on the wider socio-economic sphere both at an interpersonal and at a community level (Gui and Sugden, 2005). Thus it has been suggested that under certain circumstances ‘mobilization’ around collective issues can be increased (Uhlaner, 1989). A number of

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studies now confirm that greater networked interaction leads to increased environmental awareness among individuals, making communities more responsive to natural resource management issues (Wakefield et al., 2006; Cramb, 2005). Recent studies (Yao et al., 2014) have shown that people who are members of environmental NGOs are also more willing to pay for natural resource management measures. This is because environmental NGOs tend to raise awareness of headline issues, such as climate change impacts, and this increased environmental awareness can lead to a higher WTP contribution (Polyzou et al., 2011). Nonetheless, although the majority of studies focus on the positive impacts of social capital, there are cases where the influence of social capital is negligible or can even be negative under certain conditions (Portes, 2000; Levi, 1996). In environmental issues, for example, there may be communities where established social norms do not promote collective action at individual level (Jones et al., 2011). Moreover the influence of networks will significantly depend on the type of social interaction developed locally, and whether information circulated pertains to and is beneficial for natural resources management (Jones and Clark, 2013; Wolf et al., 2010). Consequently individual social capital should always be analysed in relation to its collective social and cultural setting. 2. Methods 2.1. The study area The research was based on a survey conducted via structured questionnaire of coastal communities in Romney Marsh in south-east England in 2012. Romney Marsh covers 260 km2 and is sparsely populated, with approximately 22,000 households in the coastal zone. The main reason for selecting the Romney area was because it already experiences climate change impacts which are expected to increase significantly in future (Shoreline Management Plan, South Foreland to Beachy Head, 2006). The Marsh is reclaimed from the sea with the majority of land being below sea level. Consequently a flooding incident anywhere along the coast could potentially result in widespread inundation of the area. For this reason, extensive coastal defences have been built. The current management plan proposes to continue maintaining these defences. However, in order to underwrite the cost of their maintenance and to provide a contingency reserve to construct new defences in the future, there is now a requirement to find alternative means of funding. 2.2. Distribution of questionnaires The study's total sampling frame was calculated after including all communities which were in the ‘high risk flooding zone’ proposed by the Environment Agency. The local postal code index was used and a sample of 1,000 households was selected during May–June 2012, with a random sampling technique (every 22nd household in the total sampling frame was selected). Questionnaires were sent by post, with participant households receiving a covering letter explaining the aims of the study, the structured questionnaire and a pre-paid envelope. The covering letter invited one household member to fill in the questionnaire (respondents needed to be aged 18 years or over). The response rate was 16% which although low is comparable with similar studies (e.g., Whitmarsh, 2011). We therefore considered the survey results to give a clear indication of residents' attitudes regarding the two research questions. Table 1 shows the main demographic characteristics of the sample. 2.3. Description of questionnaire The questionnaire was designed to elicit respondents' perceptions of climate change projections, their opinion of coastal

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N. Jones et al. / Ecological Economics 119 (2015) 74–82

Table 1 Demographic characteristics of the sample. Gender Income (£)

Male Female Up to 12,000 12,000–30,000 30,000–70,000 Over 70,000

Age (mean) Years of education (mean) Distance of the house from the coast (miles) (mean)

52.9% 47.1% 16.8% 23.6% 14.1% 5.5% 54 15 1.26

studies (Myatt-Bell et al., 2002; Ledoux et al., 2005) and also through considering the case study area's specific situation through discussions with local stakeholders. Finally, four main parameters of social capital were investigated which are commonly explored in the literature: a) institutional trust, b) social trust, c) participation in social networks and d) social reciprocity (Woolcock and Narayan, 2000; Jones et al., 2011; van Oorschot et al., 2006; Sapienza et al., 2007; Grootaert et al., 2004).

2.4. Data analysis management policy scenarios, and their level of social capital. Questions used are presented in Appendix A. Respondents were asked initially to state their level of concern regarding specific climate change impacts (both globally and locally). They were then asked to estimate the level of risk they perceived from climate change impacts set out on a list of possible hazards derived from existing studies (Arnell, 1999; Bouwer et al., 2010; Heltberg et al., 2008; Iglesias et al., 2007), and from local observations made by the research team in the case study area. Next a coastal management scenario was presented that was identical to the strategy currently applied by local authorities, with the exception that respondents were asked to contribute to its funding through a local precept (tax). They were then presented with a hypothetical scenario concerning increased local flooding and erosion risk in future and a WTP question, based on the guidelines of the Contingent Valuation Method (CVM) (Mitchell and Carson, 1989). This scenario asked respondents to imagine that as a community they had the option to maintain the current coastal defences and construct new ones wherever necessary in order to minimize the impacts from climate change, on the condition that these new defences would be partly funded by a new precept raised locally and which would apply to them. The WTP question was presented as follows: Suppose that a new governmental tax was created in order to fund coastal defence construction and maintenance. This tax would be paid monthly by every household in your area. Would you be willing to pay an amount per month as a household through this tax? Respondents were first asked to state whether they would be willing to pay (yes/no). Those that refused were then asked to justify the reasons through an open-ended question; this allowed us to distinguish protest responses from ‘true’ zeroes. Protest responses refer to zero evaluations due to a disagreement with a specific part of the hypothetical scenario and/or the payment vehicle (Meyerhoff and Liebe, 2010). For those respondents who replied positively, a payment card with four options was presented (£1, £3, £5, £7), which is widely regarded in the literature as an efficient technique to elicit reliable estimations in CVM (Blaine et al., 2005; Solomon and Johnson, 2009). An open-ended choice was also available to respondents in case they wanted to state a different amount from the ones proposed. The final amounts presented in the payment card were selected after discussing the potential tax with local stakeholders. Based on proposals from other coastal areas of the UK, the amounts presented in our study were very close to those set out for regions of Norfolk, a fact that underlines the appropriateness of the suggested amounts on the payment cards (Borough Council of King's Lynn and West Norfolk, 2011). Respondents were also asked to state whether they are aware of the proposed Shoreline Management Plan (SMP) and if they thought that maintaining and building new sea defences would protect them from flooding in the long-term. Perception on benefits and disadvantages were also explored. These were selected based on previous

Data were analysed using SPSS 21.0 software (IBM Corp. Released, 2012). The estimated (through a linear function) WTP amount was based on three different samples: the first included all WTP responses (n = 160); the second excluded those answers regarded as ‘protest responses’ (n = 69), leaving the ‘true zeroes’ (n = 19) and the positive responses (n = 72) in the final sample. Specifically, respondents who refused to pay due to financial constraints or due to low personal valuation were considered ‘true zeroes’ (e.g., protection from flooding was not important to them) (Afroz et al., 2009). All other rationales, such as objection to the policy or payment vehicle, were considered as protest responses. A third evaluation of WTP was based on a sample including only the positive responses on WTP. In order to explore the influence of factors on WTP, we conducted an exploratory factor analysis (EFA) (Bryant and Yarnold, 1995) to reduce dimensionality of certain predictor variables in the questionnaire whose influence on WTP was to be tested. EFA reduced the initial independents to a total of seven latent constructs: combining risk perceptions (RISK, Cronbach's a: 0.934), benefits of the proposed policy (BENEFITS, a: 0.743), disadvantages of the proposed policy (DISADVANTAGES, a: 0.716), trust in institutions (INST TRUST, a: 0.777), trust in other people (SOCIAL TRUST, a: 0.859), participation in social networks (NETWORKS, a: 0.682) and two questions on social reciprocity (SOCIAL RECIPROCITY, a: 0.884). The seven extracted factors were added to the rest of the observed items including: demographic characteristics (gender, age, educational level, income level, owner of property in the area), respondents' concern over climate change (CONCERN), how concerned were the respondents for global and local climate change impacts (GLOBAL and LOCAL respectively), their level of awareness of the SMP (AWARE), and whether they thought existing coastal management approaches would protect them by reducing the risk of flooding (PROTECT) (see Table A1 in Appendix A for a detailed description of the variables used for subsequent analysis and their values). These factors were all entered as predictors for the WTP estimation. Specifically, three general linear regression models (GLMs) were used for the estimation of WTP based on the three samples already described, namely a GLM where all WTP responses were included, a GLM analysis including only positive responses and the ‘true zeros’, and a GLM including only positive WTP responses. GLM analysis is highly appropriate since it provided us with the advantage of simultaneously including as independents both continuous and categorical variables. The analysis conducted by segregating the WTP answers according to protest responses and true zeroes provided us with more information and accurate estimations of the explanatory factors. Finally, for the selection of the statistical significant variables included in the three GLM models we resorted to backward selection as the method for identifying the optimal set of independent variables. This also enabled the elimination of the closely correlated predictors. In this way, we identified the largest possible number of independents with the strongest statistically significant dependencies on the dependent variable, so avoiding over-fitting and multicollinearity issues.

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3. Results

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Table 3 Reasons for refusal.

3.1. Descriptive analysis of the data 3.1.1. Perceptions for climate change and risks The preliminary analysis of the selected sample yielded a mean score of 3.4 (maximum value: 5, standard deviation (sd): 1.25) on the level of respondents' concern for climate change. Respondents were found to be moderately more concerned about the likely impacts of climate change in Romney Marsh (mean: 3.9, sd: 1.18) than the impacts globally (mean: 3.42, sd: 1.18). Regarding risk perceptions, ‘water shortage’ and ‘deterioration in water quality’ were the two most important for respondents. The least important risks were considered to be ‘rising temperatures’ and ‘soil erosion’ (Table 2). 3.1.2. Perceptions of proposed coastal management policy 51.9% of the sample claimed they were aware of the current SMP which was proposed for their area at the time the survey was implemented. Exactly the same percentage stated they believed that the sea defences would protect them from flooding in the future. On a 5 point Likert scale, respondents presented a mean score of 3.6 (sd: 0.93) as their level of agreement for building new sea defences and maintaining existing ones. The most important benefits of the SMP for respondents were connected with ‘protection of property/ houses’ (mean: 4.49, sd: 0.78) and ‘protection of agricultural land’ (mean: 4.33, sd: 0.95). Lower scores were evidenced for ‘Protecting biodiversity’ (mean: 3.9, sd: 1.10), ‘retaining public access to beach’ (mean: 3.56, sd:1.12) and ‘maintenance of recreation activities’ (mean: 3.3, sd: 1.23). Turning to disadvantages, there was no difference between respondents' evaluations, which all yielded a similar mean score (‘tax burden on citizens’: mean 3.55, sd: 1.36; ‘high maintenance cost’: mean: 3.66, sd 1.23; ‘possible biodiversity loss’, mean: 3.63, sd: 1.15). 3.1.3. Social capital The highest level of institutional trust in coastal management was vested by respondents in the Environment Agency (mean: 5.94, sd: 2.71), followed by Natural England (mean: 4.66, sd: 2.77), and then Local Authorities (mean: 4.59, sd: 2.6). Lower scores were presented for DEFRA (mean: 4.43, sd: 2.44), local NGOs (mean: 3.75, sd: 2.26), national government (mean: 3.38, sd: 2.21), and the European Union (mean: 2.19, sd: 1.64). Generalised trust yielded a mean score of 4.63 (sd: 2.28) among respondents. By contrast particularized trust was much higher, for example towards neighbours (mean: 5.79, sd: 2.65) and people within respondents' local communities (mean: 5.67, sd: 2.15). When the level of trust towards the local community for managing coastal management issues was raised, a mean score of 4.4 (sd: 2.54) resulted, while on fairness, the mean score for the sample was 4.99 (sd: 2.42).

Table 2 Risk perceptions (5 point Likert scale, 5: the highest level of concern).

Water shortage Deterioration in water quality Sea level rise Flooding of homes Loss of biodiversity Flooding of agricultural land Flooding of other property/infrastructure Increased crop diseases and pests Changing climate Soil erosion Rising temperatures

Mean

Std. deviation

4.38 4.11 3.81 3.73 3.62 3.6 3.57 3.41 3.41 3.39 3.07

0.90 1.08 1.27 1.28 1.26 1.27 1.27 1.25 1.30 1.13 1.23

Can't afford it Already pay enough Climate change is natural Everyone should pay (national responsibility) Government should pay Live on hill Low trust on management authorities Nuclear power station Objection to suggested policy/payment vehicle Other things are more important

Frequency

Valid percent

13 15 1 14 4 2 3 2 6 1

21.3 24.6 1.6 23.0 6.6 3.3 4.9 3.3 9.8 1.6

On social networks, 31% of the sample declared that they were members of at least one NGO, and of these 18.4% stated their membership was with an environmental NGO. Furthermore, 9.6% stated that they volunteered with at least one NGO and of these 8.9% volunteered with an environmental NGO. 17.1% declared that they have participated in local community groups, while only 4.4% had participated in coastal defence action groups in their area. Lastly, regarding social reciprocity, 82.3% of the respondents declared their belief that their neighbours would help them if their home was in danger of flooding. This percentage increased when applied to family and close friends (88.5%). 3.1.4. Willingness to pay 3.1.4.1. Intention to pay. On the WTP question, respondents were asked whether they would be willing to pay an amount for the construction and maintenance of defences through a local tax which would be paid monthly by households in their area. 53.1% of the sample responded negatively, with 45.6% stating their willingness to pay. 3.1.4.2. Reasons for refusing to pay and protest responses. This was investigated through an open-ended question, with several reasons adduced by respondents (Table 3). The most common was respondents' belief that they already paid enough through local taxes. Another common reason given was that financing coastal management should be a national responsibility, and not just for those directly affected. Protest responses were distinguished from ‘true’ zeroes if they mentioned the following: they couldn't afford to pay; they regarded climate change as a natural process; they lived on a hill and so were not directly affected; that other issues were more important; and that due to the presence of Dungeness nuclear power station they did not think payments by local residents would be necessary, as the state would fund all coastal defence expenditure. 3.1.4.3. Willingness to pay. Willingness to pay was estimated in three different ways: first for all respondents, including all zero responses. A second estimation included all responses excluding protest responses. In a final estimation we calculated only those who declared a positive answer. In the first case where all responses were included, the mean WTP was approximately £2/month (Table 4). By excluding protest responses, this amount increases to £3.53. Finally

Table 4 Willingness to pay.

All responses Positive and true zeroes responses Only positive responses

N

Minimum

Maximum

Mean

Std. deviation

160 91

0 0

10.00 10.00

2.01 3.53

2.69 2.71

1.00

10.00

4.46

2.26

72

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N. Jones et al. / Ecological Economics 119 (2015) 74–82

when estimating WTP only from positive responses, this rose to £4.46 (Table 4). 3.2. Econometric analysis: factors influencing WTP through GLM regression analysis We conducted a regression analysis to explore the potential factors influencing WTP. Our main focus was on social factors and also

on variables measuring perceptions for coastal management issues. We estimated WTP based on three samples according to responses on WTP (GLM1: All responses, GLM2: excluding protest responses and GLM3: only positive responses). The estimated coefficient parameters for each independent variable of the three GLM derived models are shown in Table 5 along with the associated significance (p-values). Estimates for the non-statistically significant explanatory variables are not discussed here due to word limitations. Before

Table 5 Parameter estimates for the three GLM models. Predictor

GLM 1 All responses

GLM 2 True zeros

GLM 3 Positive responses

Parameter estimate

p-value

Parameter estimate

p-value

Parameter estimate

p-value

Constant INST TRUST SOCIAL TRUST NETWORKS RECIPROCITY BENEFITS DISADVANTAGES RISKS

4.624 1.513 1.351 −1.184 −21.728 – – −0.903

n.s. 0.002⁎⁎⁎ 0.024⁎⁎ 0.002⁎⁎⁎ 0.054⁎

n.s. 0.001⁎⁎⁎ 0.019⁎⁎ 0.075⁎

– – 0.085⁎

2.388 1.651 1.151 −0.835 – – – −1.395

– – – 0.032⁎⁎

−2.934 – – – −49.966 – – −2.371

n.s. – – – 0.003⁎⁎⁎ – – 0.037⁎⁎

CONCERN Reference category: very Not at all 2 3 4

– – – –

– – – –

7.155 1.822 1.224 1.562

0.083⁎ n.s. n.s. n.s.

– – – –

– – – –

GLOBAL Reference category: very Not at all 2 3 4

−2.293 −6.619 −1.048 −2.077

n.s. 0.012⁎⁎ n.s. n.s.

−10.603 −10.809 −3.942 −3.184

0.031⁎⁎ 0.003⁎⁎⁎ 0.042⁎⁎ 0.033⁎⁎

−8.076 −5.854 −4.602 −2.053

0.006⁎⁎⁎ n.s. 0.008⁎⁎⁎ n.s.

LOCAL Reference category: very Not at all 2 3 4

−0.326 1.338 −5.337 −4.1

n.s. n.s. 0.003⁎⁎⁎ 0.008⁎⁎⁎

3.453 5.823 −1.816 −2.979

n.s. 0.002⁎⁎⁎ 0.098⁎ 0.014⁎⁎

– – – –

– – – –

AWARE Reference category: yes No

–

–

1.891

0.018⁎⁎

2.603

0.005⁎⁎⁎

PROTECT Reference category: yes No

–

–

–

–

−2.737

0.057⁎

AGREEMENT Reference category: totally agree Disagree −3.468 Neither agree nor disagree −0.399 Agree −0.855

0.018⁎⁎ n.s. n.s.

– – –

– – –

– – –

– – –

OWNER Reference category: yes No

–

–

–

–

6.908

0.017⁎⁎

EDUCATION

–

–

–

–

−0.144

0.095⁎

AGE

–

–

0.063

0.049⁎⁎

–

–

INCOME Reference category: N£70,000 ≤£12,000 £12,001–£30,000 £30,001–£70,000 R2

0.381 −0.005 −3.987 0.785

n.s. n.s. 0.037⁎⁎ (R2 adjusted: 0.564)

−2.563 −1.665 −5.022 0.954

n.s. n.s. 0.001⁎⁎⁎ (R2 adjusted: 0.843)

−5.723 −3.411 −6.035 0.977

0.035⁎⁎ n.s. b0.001⁎⁎⁎ (R2 adjusted: 0.899)

Dependent variable: amount of willingness to pay for coastal defences. n.s.: non-significant ⁎ Coefficient is significant at a 10% significance level. ⁎⁎ Coefficient is significant at a 5% significance level. ⁎⁎⁎ Coefficient is significant at a 1% significance level.

N. Jones et al. / Ecological Economics 119 (2015) 74–82

describing the results of Table 5 we should briefly explain how the signs of the parameter estimates are interpreted. All aggregated factors (social capital parameters, benefits, disadvantages and risk perceptions) were introduced in the model as continuous variables. Thus a positive sign in a parameter estimate reveals that the specific variable has a positive influence on WTP (higher levels of the independent variable result to higher WTP). The remaining variables in the table were introduced as categorical variables. (For example perception on global impacts of climate change and awareness of the current SMP). In this case one category of each variable was considered as the reference category. Then for each of the remaining categories, when a parameter estimate has a negative sign, this means that respondents who chose this specific answer (category) were less willing to pay compared to those respondents who chose the reference category. In the first model (GLM1, Table 5, including all respondents) all social capital variables had a statistically significant influence on WTP. Thus respondents with higher levels of social trust and institutional trust were more willing to pay, while those with greater involvement in social networks and a higher sense of reciprocity were less willing to pay. Furthermore, the variable measuring the aggregate measurement of risk had a negative impact on WTP. This model also revealed that respondents with an income over £70,000 were more willing to pay compared to those respondents in the categories £12,001–£30,000 and £30,001–70,000. However this result is statistically significant only for the latter category. Also, respondents who were ‘very concerned’ of the impacts of global climate change were more willing to pay than the rest of the respondents and this result was statistically significant in the second category of the variable. The model also showed that those respondents who ‘totally agreed’ with the proposed policy were more willing to pay compared to all other respondents, with the ‘disagree’ category having a statistically significant influence. Turning next to GLM2, institutional trust and social trust were both positively correlated with WTP while social networks were negatively correlated. Hence individuals who trust institutions and their fellow citizens were more willing to pay, while those who participate in social networks were willing to pay less compared to individuals who were not involved in social networks. Furthermore, income, concern of global climate change impacts and risk perceptions had a similar influence as in GLM1. In addition, concern for the local impacts of climate change was statistically significant in GLM2 with respondents with the highest level of concern being more willing to pay for sea defences compared to the rest of the sample. Also, individuals who were not aware of the SMP were willing to pay more compared to those who were informed about it. Age was also positively correlated with WTP meaning that older respondents (age measured through year of birth) are more willing to pay for coastal defences. In GLM3, from the social capital parameters, only reciprocity had a statistical significant influence on WTP revealing that individuals who believed other people would not help them in case of a flood emergency were willing to pay more for coastal defences. Furthermore, income, concern for global climate change impacts and risk perceptions had a similar influence as in GLM1 and GLM2. Awareness of the SMP had a negative influence on WTP as in GLM2 while the belief that the proposed approach will offer protection from sea level rise was correlated positively with WTP (those who stated ‘yes’ were more willing to pay when compared to those who stated ‘no’). Finally, in this model people with higher levels of educational attainment were willing to pay less. As regards model fit, the R2 value including all WTP responses is 0.785 (GLM1 R2 adjusted: 0.564), whereas the fit of the other two models was found to be considerably better [GLM2 R2: 0.954 (R2 adjusted: 0.843); GLM3 R2: 0.977 (R2 adjusted: 0.899)] indicating that

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through the selected factors the analysis explains the majority of the variance in the answers of respondents on their WTP. 4. Discussion Our study has sought to estimate the willingness to pay of individuals for a hypothetical payment vehicle to cover costs for the maintenance and construction of hard engineered coastal defences, and to explore the influence of social capital on respondents' monetary evaluations. This is a very timely topic with high policy relevance given that, globally, coastal management authorities are facing increasing challenges in funding hard engineered coastal defences. Such defences remain the most common policy of protecting communities at risk due to sea level rise and coastal erosion. The first question explored the overall perception of local residents in Romney Marsh to the threat posed by climate change. The level of concern exhibited by the sample was manifestly higher than the average of the scale on which it was measured. This is possibly due to regular media reports of the impacts of sea level rise locally, and respondents' own observations of the ongoing structural works and improvements conducted on hard engineered defences in the study area by UK Government agencies, especially the Environment Agency. Moreover in the literature it is noted that individuals with personal experience of flooding are more aware and more concerned about the effects of climate change (Spence et al., 2011). Although in Romney Marsh individuals have not had direct experience of flooding, the fact that they observe the constant need for maintenance works on coastal defences to protect their community clearly affects their perception of climate change. Moreover, respondents' consistently high evaluation of the risks associated with water shortage and deterioration in water quality can be explained by the survey being conducted immediately after a very dry winter, when restrictions on water use were imposed on households (Southern Water, 2013). Regarding the specific estimation of WTP, three different approximations were generated in the study through separate modelling exercises (only positive responses: £4.46, positive responses and ‘true’ zeroes: £3.53, all responses: £ 2.01). We believe the estimate generated by excluding protest respondents from the sample as the most reliable (i.e., GLM2). Thus, our best estimate of acceptable levels of monthly payments for the maintenance and construction of coastal defences in the Romney area is £3.53. Currently there are no similar studies with which to compare this result. By scaling up this amount for the wider local community (approximately 22,000 households) this results in an overall tax of £931,920 annually. Based on current government expenditure, this would not be anywhere near sufficient to fully fund the existing network of defences. For example, the new defences around Dymchurch cost £60 million (Dymchurch Parich Council, 2011). However, it could be seen as a significant financial contribution in the long-term. Although an estimation of WTP was achieved through the study, a major concern for policymakers is the relatively high level of refusal to pay. Nonetheless, current decentralization efforts and a further round of public sector budgetary cuts may mean that citizens will be required to pay for coastal defences in the near future. Management bodies should therefore be prepared to deal with the significant opposition that such a tax may provoke. According to our results, another significant issue requiring careful thought is the dilemma between imposing a local and a national tax. Approximately half of respondents in our sample stated they were not willing to contribute towards the cost of coastal defences under any circumstances, on the grounds that ‘everyone should pay’. Thus many respondents believed that these costs should be serviced through general taxation rather than being borne by those who are directly affected by sea level rise and coastal erosion processes. This certainly needs to be taken into consideration in any future policy decision-making where a ‘coastal defence’ tax is proposed for local

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communities. The two arguments that will have to be considered are whether coastal defences should be seen as beneficial mainly for local coastal communities protecting properties, agricultural land and maintaining everyday activities of locals; or if they are seen as beneficial for the whole nation, as defences maintain coastal recreational areas used by UK residents and tourists from abroad while at the same time slowing erosion rates so protecting in the long-term areas which are further inland (UNEP, 2010). These two arguments should be the focus for consultation with coastal communities and nationally over the future direction of flood and coastal defence policy decision-making processes. Furthermore, the high level of WTP refusal identified here also indicates a potential consideration of alternative management options for coastal zones facing climate change from policy-makers where local communities would not need to contribute financially to such a high level and also some of the negative impacts caused by hard sea defences (such as coastal squeeze) can be reduced (UNEP, 2010). For example, managed realignment policies have been applied in different parts of the world (Apine, 2011; Roca and Villares, 2012) allowing erosion cycles to occur naturally while permitting management of flooding incidents and coastal erosion in a sustainable way (De Vries and Wolsink, 2009; Defra, 2004; Milligan et al., 2009). A major concern however with this approach is the likely need to compensate individuals whose properties will be influenced by the changing coastline resulting from managed realignment (Jones and Clark, 2013). Thus, although citizens might not be asked to pay during the implementation of such policies due to the lower costs of their application, the financial impacts that such a policy may have on certain individuals might incur high costs due to property damage, reduction in property value and/or loss of agricultural land. The study has also sought to explore the influence of social factors, through examining for the first time the impact of social capital for WTP for coastal defences. We focus here on the results from the model where protest responses were excluded, i.e., GLM2. This is mainly because we regard that protest responses may significantly bias the interpretation of results. In this model, three out of the four social capital parameters measured had a statistically significant impact on WTP. In particular, both institutional trust and social trust had a positive influence, revealing that respondents who tend to trust their fellow citizens and also trust coastal management agencies are more willing to pay for defence works. This is supported by the literature on the positive impact of trust on environmental perception (Wagner and Fernandez-Gimenez, 2008; Pretty, 2003; Halkos and Jones, 2012). An interesting finding in this context concerns the different levels of trust towards institutions. The Environment Agency (EA) was the most trusted institution among respondents in the study. This result can be justified taking into consideration the ongoing daily works that take place in Romney Marsh by the EA in order to protect local communities from flooding. By contrast institutions such as Defra and national government are considered to be much more remote from the concerns of residents. One limitation that should be noted is that we did not measure the legitimacy of the different institutions involved in coastal management. Research on legitimacy could reveal additional reasons why certain institutions were trusted more by the public and were linked with WTP. Regarding social networks, these had a largely negative impact on WTP, contradicting the assumptions that participation in social networks increases monetary contributions (Polyzou et al., 2011; Veronesi et al., 2014). In fact, respondents who participated in social networks were willing to contribute less, or were not willing to contribute at all, compared to individuals who did not participate in networks. This negative role of social networks on environmental perceptions and activism has been highlighted in previous studies (Wolf et al., 2010). In the case of Romney Marsh, this means that people who are more informed through these networks about

local issues are willing to pay less. Although further research is necessary in order to understand this result, one explanation might be that existing networks in the area help sustain the idea that construction and maintenance of coastal defences should be the responsibility of the Environment Agency and that local communities should not be burdened with their funding. On the impact of other variables, one result is of particular interest. Risk perceptions were connected negatively with WTP, meaning that individuals who considered that risks were low in the area were willing to pay more for the protection of their houses. This result is not in accordance with previous findings (Viscusi and Zeckhauser, 2006). One possible explanation is that those who believe that risk is very high, view flood effects as likely to be catastrophic and as a result see no point in having any protection. However, further investigation is necessary in order to corroborate these findings.

5. Conclusions Although much academic attention is now given to the role of ‘softer’ mitigation and adaptation policies to address climate change impacts, in many cases maintaining hard engineered coastal defences will remain essential, for example where the value of social, economic and environmental assets is particularly high. Coupled with future projections for greater storminess at the coast and increasing unpredictability of weather patterns, it is thus possible that the UK's coastal communities will be asked to contribute financially in order to receive continued protection from sea level rise and increased erosion risk. In Romney Marsh, the average WTP was estimated to £3.53 per month. Our study demonstrates that generalised and particularised forms of trust clearly exert a positive influence on WTP, which could be used by policy actors to enhance and possibly to increase public acceptability in cases where financial contributions are likely to be requested from the public by government. Our main conclusion is that, due to the unexpectedly high level of refusals in WTP, the degree of trust in coastal management institutions should be significantly increased prior to any attempt to apply a taxbased policy. This could be done through intense consultation processes aiming to provide information to local residents on why such a tax is considered necessary, coupled with careful enumeration of exactly how monies raised would be used. Furthermore, public opinion needs to be canvassed regarding the type of tax, the political administrative level at which it might be collected (national or local) and how it might be paid. A second conclusion concerns social networks. The way networks operate in the area, and specifically the involvement of local and central authorities in these networks should be taken into account in reformulating existing decision-making processes on coastal management. One approach would be to ensure greater agency–public interaction with those managing bodies that are most trusted by the public (such as the EA), while at the same time seeking to address the ‘trust deficit’ exhibited by other authorities, most clearly national government. We deem the application of this approach essential in order to understand the reaction of local communities to coastal management agencies and to incorporate their knowledge and opinion into policy planning processes. Such efforts would also raise significantly the social acceptability of future coastal management policies based on revenue collection from local communities.

Acknowledgements This research was supported by the European Union's FPVII Marie Curie Intra European Fellowship programme, contract number 273361.

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Appendix A

References

Table A1 Variables used in our analysis. Categorical level variables

Values

Concern over climate change (CONCERN) Level of concern for global climate change impacts (GLOBAL) Level of concern for local climate change impacts (LOCAL) Awareness of the current Shoreline Management Plan (AWARE) Sea defences can protect the area from flooding in the long-term (PROTECT) Level of agreement with the maintenance of current defences and construction of new ones (AGREEMENT) Gender Owner Income level

Not at all concerned (1), (2), (3), (4), Very concerned (5) Not at all concerned (1), (2), (3), (4), Very concerned (5) Not at all concerned (1), (2), (3), (4), Very concerned (5) Yes (1), No (2)

Continuous variables Age Education Factors (measured at a continuous level) Institutional trust

Social trust

Networks

Reciprocity

Benefits

Disadvantages

Risks

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Yes (1), No (2) Totally disagree (1), Disagree (2), Neither agree nor disagree (3), Agree (4), Totally agree (5) Male (1), Female (2) Yes (1), No (2) ≤£12,000 (1), £12,001–£30,000 (2), £30,001–£70,000 (3), N£70,000 (4) Measured at a continuous level Measured at a continuous level (years of education) Items for constructing the factors Q1. Trust the national government Q2. Trust the European Union Q3. Trust Local councils Q4. Trust Environment Agency Q5. Trust DEFRA Q6. Trust Natural England Q7. Trust local NGOs Q1. Do you think that most people can be trusted, or that you can't be too careful? Q2. Do you think that most people are fair or they try to take advantage of you? Q3. Trust neighbours Q4. Trust people in local communities Q5. Trust in local communities to deal with coastal management issues Q1. Membership in NGO Q2. Volunteer in NGO Q3. Membership in environmental NGO Q4. Volunteer in environmental NGO Q5. Participation in local community groups Q6. Participation in coastal defence action groups Q1. Help from your neighbours if your home is in danger of flooding Q2. Help from your close friends if your home is in danger of flooding Q1. Protecting biodiversity Q2. Maintenance of recreational activities Q3. Retaining public access to beach Q4. Protection of house/properties Q5. Protection of agricultural lands Q1. Tax burden on citizens Q2. High maintenance cost Q3. Possible biodiversity loss Q1. Water shortage Q2. Deterioration in water quality Q3. Flooding of agricultural land Q4. Flooding of homes Q5. Soil erosion Q6. Increased crop diseases and pests Q7. Flooding of other property/infrastructure

Dependent variable Amount of willingness to pay for coastal defences

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