Predictor variables

Based on the theoretical framework a variety of predictors were included in the models. Table 5-5 gives an overview about predictors, their description, coding and coefficients’ expected signs. The predictors are classified into four categories: i) (experimental) study design; ii) socio-demographics; iii) sense of connectedness as well as usage of ES / being in nature; and iv) attitudes, perceptions and knowledge regarding ecosystems, species conservation and wolves.

(i) Concerning the method comparison, the predictor variables of primary interest are stage, treatment and their interaction. In case that one of the treatment levels is significant, the associated method would have a significant effect on WTP irrespective of the stage. If stage is significant both deliberative methods would be significantly different from CV irrespective of stage. In case that the interactions of stage and treatment are significant, the WTP differs significantly after deliberation. Thus, a difference between the deliberative methods exists if only one interaction turns out to be significant. As illustrated above, the existing empirical research gives no clear indication how WTP amounts are altered through deliberation.

Therefore, the expected direction of the estimates is unpredictable.

Table 5-5 Description, coding and expected sign of predictor variables

stage Valuation stage within valuation workshop.

1 = first stage 2 = second stage

? treatment Indicator for the valuation method used in

the specific valuation workshop.

age Participants’ age (measured in categories) 7-point scale from 1 = 16-25 years to

income Personal disposable income per month 6-point scale from 1 = < €500 to 6 = > €4000

+

edu Highest educational level 6-point scale from

1 = no graduation to 6 = university degree

○

urban.residence Current place of residence 0 = countryside 1 = city

+ urban.origin Predominant place of residence until 16

years old donation Donation to environmental organisation

within past 12 months farmer Participant or person within family

engaged in agriculture and/or livestock farming

activities Recreational activities undertaken in forests, fields, and/or pasture landscapes within past year

Count from 0 to 9 ?

Table 5-5 (continued)

pref_env Environmental protection ranked as most important spending of public funds

0 = no 1 = yes

+ pref_animal Protection of rare animal species ranked as

most important spending of public funds towards environmental projects

0 = no 1 = yes

+

know Self-assessed knowledge about wolves 10-point scale from 0 = none to 10 = expert

+ att_sc_1 Attitude toward preservation of rare

species for future generations (bequest value)

5-point Likert scale +

att_sc_2 Attitude toward unimportance of a single species’ extinction

5-point Likert scale – att_sc_3 Attitude toward mastery of nature in order

to meet human needs

5-point Likert scale – att_sc_4 Attitude toward satisfaction contributing

to species conservation (warm glow)

5-point Likert scale + att_sc_5 Attitude toward nature conservation due to

intrinsic value

5-point Likert scale + att_sc_6 Attitude toward species conservation due

to existence rights of animals

5-point Likert scale + att_w_1 Attitude toward impossibility of

coexistence of humans and wolves

5-point Likert scale – att_w_2 Attitude towards wolves’ and other

predators’ contribution to natural balance

5-point Likert scale + att_w_3 Attitude toward historic extinction of

wolves

5-point Likert scale – att_w_4 Attitude toward wolves’ benefits for

humans

5-point Likert scale + att_w_5 Attitude toward wolves as competitors for

hunters att_w_8 Attitude toward wolves as threat for other

native species

5-point Likert scale – nimby Support of wolves’ establishment close to

own residence

(ii) Turning to the predictors with reference to socio-demographics, no effect is expected for age and education (edu) due to the nature of the sampling going hand in hand with a low variability of these variables. Although, reviewing 38 quantitative surveys Williams et al.

(2002) found that age has a negative correlation with attitudes towards wolves and education a positive one (see also Kleiven et al., 2004; Naugthon-Treves et al., 2003).²⁹ The effect of participants’ gender on stated WTP amounts is unclear. Some studies found that women have a more positive attitudes towards wildlife (Czech et al., 2001; Teel & Manfredo, 2010), whereas others found the opposite to be true in case of attitudes towards wolves (see e.g. Kleiven et al., 2004). The effect of income is expected to be positive as an increasing income is associated with a higher ability-to-pay (see e.g. Bateman et al., 1994) and more positive attitudes towards wolves (Williams et al., 2002). Participants having the place of residence currently in a city (urban.residence) or grew up in a city (urban.origin) are predicted to have a higher WTP, as in general attitudes towards wolves of rural residents are less positive (Heberlein & Ericsson, 2005; Kleiven et al., 2004; Williams et al., 2002). A positive correlation is expected between WTP and membership in an environmental organisation (member) (Williams et al., 2002) or donations to the latter within the last year (donation). Whereas being engaged in farming or livestock production (or at least having ties to it) (farmer) is associated with negative attitudes towards wolves (Naugthon-Treves et al., 2003; Williams et al., 2002) and therefore, also an expected negative effect on WTP. The same applies to being engaged in hunting (hunter). While attitudes of hunters towards wolves are heterogeneous in a global context (Williams et al., 2002), in Sweden hunters expressed most negative attitudes (Ericsson & Heberlein, 2003). How ownership of a dog (dog) effects WTP is unclear. On the one hand, wolves are a potential threat to dogs, on the other hand, dog owners may be more animal-friendly in general.

(iii) Regarding the two measures of connectedness, a high subjective sense of connectedness to nature (INS) is likely to result in higher WTP amounts stated, while the opposite is the case for connectedness to society (ICS). It is assumed that participants with self-reported strong relationship to society place more weight on the concerns of specific groups effected by wolves, such as farmers and hunters, and/or on the potential threats to human-beings. It is not obvious

29 In their review Williams et al. (2002, p. 577) define attitudes towards wolves simply as ‚liking or disliking wolves‘. Also the studies of Naugthon-Treves et al. (2003) and Kleiven et al. (2004) investigated correlations between socio-demographic variables and attitudes or rather tolerance towards wolves instead of WTP. Still, it is assumed that the directions of correlations are similar.

how the amount of recreational activities alters WTP as it could reflect opportunity costs but only if wolves are considered to be a threat which hinders participants from practicing activities.

(iv) Considering attitudes, perception and knowledge the predictor variables can be roughly divided in two groups either in favour of wolves or with negative attitudes towards them. A strong preference for spending public funds towards the environment (pref_env) and towards protection of rare animal species (pref_animal) are expected to have a positive impact on WTP.

The same applies to a high knowledge about wolves (know) which can lead to more positive attitudes (Ericsson & Heberlein, 2003), although little empirical evidence for Europe exists and globally the results are mixed (Williams et al., 2002). General attitudes that link rare nature and rare species with bequest value (att_sc_1), intrinsic value (att_sc_5), existence rights (att_sc_6) as well as specific attitudes towards wolves’ contribution to a natural balance (att_w_2), benefits to humans (att_w_4) and worth of protection (att_w_7) are expected to increase WTP as well. Lastly warm glow (att_sc_4), the satisfaction of donating for a good cause in this case species conservation, has a positive expected sign.

On the contrary, participants which consider wolves as a threat towards humans (att_w_6) or native species (att_w_8), who do not believe in the possibility of coexistence of humans and wolves (att_w_1) and think that wolves were extinct for good reason (att_w_3) are expected to have a lower or rather negative WTP. This applies also to more general attitudes towards the environment or nature such as the attitude towards (un-)importance of species extinction (att_sc_2) and anthropocentric attitudes towards human nature relationships or rather mastery of nature (att_sc_3). If participants state a not in my backyard attitude (NIMBY) – a reluctance against wolves’ establishment close to one’s place of residence – they are expected to have a lower or even negative WTP. Karlsson and Sjöström (2007) have found that as distance to nearest wolf decreases, attitudes towards wolves become more negative. NIMBY attitudes are not necessarily irrational but may be rational risk averse behaviour (Fischel, 2001). Further, local opposition may arise as the conservation of wolves and their protection status is legally bound on an international and European level.

As illustrated by the overview, the expected signs of the coefficients’ estimates are derived from existing literature. The latter is dominantly focussing on countries that have longer experience with wolves or their return such as North America and Scandinavia. Yet, some of these studies found contradicting results. As discussed above, empirical evidence for Germany is lacking so far and it is unclear in how far results are generalisable between countries and

respective culture as well as from a local to a larger scale. Hence, the directions of the predictors may not be as expected based on the literature review.

By means of the quantitative analysis absolute magnitude of WTP and determinants of WTP can be compared between and within the three applied valuation methods. This analysis will shed light on the question whether economic valuation methods represent VAIs implying that elicitation of social values is dependent on the method. Further, social values can be identified based on the process – preference construction due to deliberation and social learning.

To gain a deeper understanding of motivations behind stated preferences in order to identify social values based on intention and value scale, and to assess the consistency of the novel conceptual framework (developed in Section 4.1.2), the regression analysis will be complemented by the analysis of motives behind WTP. The approach to analyse the motives will be described in the following.