The study was designed by SC, LW and NN. The analysis was carried out by SC with assistance 718
from LW. The paper writing was led by SC, with assistance and contributions from LW, NN, PH and 719
JL.
720 721
12 Funding 722
Funding for this research was received from the European Research Council, CASPI Starting Grant 723
(336665).
724
13 Acknowledgments 725
We gratefully acknowledge the support of international colleagues in facilitating this research.
726 727
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Table 1 Factor structure and descriptive statistics of pro-environmental behaviours 829
across six countries (Brazil, Denmark, India, Poland, South Africa, UK) 830
Component
1 2 3 Mean (S.D.)
Took part in a protest about an environmental issue .807 -.068 .141 0.84 (1.83) Got involved in conservation work to protect natural
environments (e.g. national parks, coastline)
.802 .059 .162 1.43 (2.37)
Offered support (e.g. by voting) for political action to protect the environment
.797 .047 .142 2.40 (2.24)
Contacted a politician about an environmental issue .779 -.105 .091 0.66 (1.64) Signed a petition about an environmental issue .770 .041 .111 1.37 (2.17) Donated money to an environmental campaign group .741 -.022 .207 1.16 (1.88) Done something together with neighbours, people at work
or friends to address an environmental issue
.686 .081 .301 1.77 (2.40)
Found out more about environmental issues (e.g. learning more about climate change)
.575 .244 .344 3.33 (2.71)
Avoided buying new things (e.g. clothes, luxury items) .338 .269 .237 3.60 (2.79) Avoided wasting food (e.g. by using leftovers) .054 .712 .129 7.36 (2.09) Avoided littering (throwing rubbish on the street) -.116 .684 -.015 8.10 (1.92) Turned off the tap when brushing teeth -.028 .669 .061 8.07 (2.21)
Turned off lights when not in use -.140 .630 .130 8.25 (1.76)
Taken short showers (less than 3 minutes long) or infrequent baths
.172 .536 .182 6.12 (3.08)
Recycled household waste (e.g. glass, plastic, food waste) .134 .408 .161 5.82 (3.14) Encouraged other people to save energy .378 .394 .339 4.40 (2.93) Eaten organic, locally-grown or in season food .131 .160 .787 4.96 (2.80) Bought environmentally-friendly products .227 .158 .769 4.50 (2.48) Bought products with less packaging .229 .261 .694 4.50 (2.59)
Avoided eating meat .204 .066 .529 3.10 (3.29) 831
832 833
Table 2. Items and descriptive statistics for Compensatory and Catalysing Beliefs scales (all Doing some things that are
positive for the environment means I am allowed to do other things that are less
environmentally-friendly actions to protect the
environment then that is enough
4.24 environmental issues; I am not prepared to change my lifestyle any further
If I save electricity through switching off appliances, I am entitled to use it in other ways such as by turning up the heating
3.40 the environment at home, there is no need to worry about doing this at work or in other situations
2.84
The environmental impact of flying on holiday can be made up for by reducing one's car use at other times
4.13
Reducing my environmental impact at home (e.g. by
recycling) helps to compensate for any environmental impacts I have at work or elsewhere
3.92
It doesn't matter how much compensates for any
environmental harm from them burning petrol/diesel in cars
3.03
Equivalent per item
31.43
is not about taking small actions, it is a complete approach to life
5.43
Doing something positive for the environment in my everyday life makes me want to do other for the environment, it gives me the sense that bigger changes in my lifestyle are possible
5.30
If I act in a manner that benefits the environment, it makes me more aware of other similar actions I can take
5.44
Equivalent per item 5.38 (1.06)
836 837 838
Table 3 Relationship between green identity and compensatory beliefs 839
840
Country Correlation
(Pearson’s r)
R2
Brazil -.29*** .09
China -.44*** .19
Denmark -.41*** .16
India -.46*** .21
Poland -.23*** .05
South Africa -.39*** .15
UK -.42*** .17
Full dataset -.36*** .13
*** p<.001 841
842 843
Table 4 Relationship between green identity and catalysing beliefs 844
Country Correlation
(Pearson’s r)
R2
Brazil .53*** .28
China .61*** .37
Denmark .49*** .24
India .39*** .15
Poland .53*** .28
South Africa .54*** .29
UK .60*** .36
Full dataset .27
*** p<.001 845
846 847
Table 5 Relationship between preference for consistency and compensatory beliefs 848
Country Correlation
(Pearson’s r)
R2
Brazil .19*** .04
China -.04 (ns) .00
Denmark .02 (ns) .00
India .13*** .02
Poland -.06 (ns) .00
South Africa .02 (ns) .00
UK .04 (ns) .00
Full dataset .12*** .01
*** p<.001 849
850 851 852 853 854
Table 6 Relationship between preference for consistency and catalysing beliefs 855
Country Correlation
(Pearson’s r)
R2
Brazil .26*** .07
China .53*** .28
Denmark .27*** .07
India .38*** .15
Poland .31*** .10
South Africa .34*** .11
UK .40*** .16
Full dataset .41*** .16
*** p<.001 856
857
858
Table 7 Relationships between PEB factors and compensatory beliefs 859
Dependent variable:
public-sphere PEB (factor 1)
Dependent variable:
resource/waste PEB (factor 2)
Dependent variable:
purchasing/food (factor 3)
B (SE) Beta R2 (Δ R2)
B (SE)
Beta Δ R2 (Δ R2)
B (SE) Beta Δ R2 (Δ R2)
Step 1 .16 .05 .003
Compensatory beliefs
.04 (.001)
.39*** -.02 (.001)
-.21*** -.005 (.001)
-.05***
Step 2 .19
(.04)
.17 (.12)
.06 (.06) Compensatory
beliefs
.05 (.001)
.46*** -.01 (.001)
-.09* .004
(.001)
.04**
Green identity .03 (.002)
.21*** .06 (.002)
.37*** .04
(.002)
.26***
860 861 862 863
Table 8 Relationships between PEB factors and catalysing beliefs 864
Dependent variable:
public-sphere PEB (factor 1)
Dependent variable:
resource/waste PEB (factor 2)
Dependent variable:
purchasing/food (factor 3)
B (SE) Beta R2 (Δ R2)
B (SE)
Beta Δ R2 (Δ R2)
B (SE) Beta Δ R2 (Δ R2)
Step 1 .10 .08 .06
Catalysing beliefs
.07 (.003)
.31*** .06 (.003)
.28*** .06
(.003)
.24***
Step 2 .11
(.02)
.17 (.09)
.08 (.02) Catalysing
beliefs
.09 (.003)
.39*** .02 (.003)
.10*** .03
(.003)
.15***
Green identity -.02 (.002)
-.15*** .06
(.002)
.35*** .03
(.002)
.17***
865 866 867 868
Table 9 Relationships between PEB inconsistency and compensatory beliefs 869
Dependent variable: