The University of Manchester ANALYSING ENVIRONMENTAL CONCERN OVER TIME: RESULTS FROM THE BRITISH NATIONAL CHILD DEVELOPMENT STUDY 1958 Gabriella Melis Mark Elliot Nick Shryane CCSR/ISC The University of Manchester

AIMS AND RATIONALE A.: To observe whether levels of attention towards environmental problems amongst the public change over time, as well as how individuals’ socio-economic characteristics are related to this R.: Focus on patterns of association in a longitudinal and individual-level perspective rather than on cross-sectional aggregate data

RESEARCH QUESTIONS Does the level of environmental concern change over time? How is environmental concern associated with socio-demographic characteristics over time? How does political orientation affect environmental concern across time?

THEORY AND HYPOTHESES: MACRO-LEVEL Trends: Preference for environmental protection over economic growth has decreased (Newport, 2009); Environmental concern was high in the 70s, low in the 80s, high in the 90s until 2008-2009, then further contraction (Leiserowitz, et al., 2010) HP1: aggregate level of environmental concern was stable from the 90s until 2008. In 2008 a contraction can be observed

THEORY AND HYPOTHESES: MICRO-LEVEL HP2: Main covariates, as per relevant literature (Fransson and Garling, 1999): Age Social class Place of residence Political ideology Gender Partnership status Presence of children

HOW HAS ENVIRONMENTAL CONCERN BEEN DEFINED AND MEASURED? ONE KEY QUESTION HOW HAS ENVIRONMENTAL CONCERN BEEN DEFINED AND MEASURED? Tension between construct validity and external validity (Dunlap and Jones: 2002)

RESEARCH TOOLS DATASET: National Child Development Study 1958 (NCDS) 1991 (age 33): 11469 cases 2000 (age 42): 11419 cases 2008-2009 (age 51): 9790 cases Pooled-longitudinal achieved: 13292 MEASURING INSTRUMENT: 5-POINT Likert scale Environmental problems are as serious as people claim (‘Problems’) We should tackle problems in the environment even if this means slower economic growth (‘Growth’) Preserving the environment is more important than any other political issue today (‘Important’) METHODS: Categorical Multiple-indicator Latent Growth Curve Modelling

SINGLE-INDICATOR TRAJECTORIES (SELECTED CATEGORIES) “Strongly agree” and “Agree” over time (% valid cross-sectional values) Source: NCDS sweeps 1991, 2000, 2008-2009

VALIDATION: 2-P NORMAL-OGIVE IRT MODEL Choices affecting the estimation of structural parameters The theoretical model (correlated errors and residuals) Reference indicator (Growth) Polychoric inter-item correlations for ordered categorical indicators Estimator: WLSMV for missing data and categorical outcome variables

VALIDATION: RESULTS Chi-square = 175.560, 15 d.f. RMSEA 90% C.I. = .025-.033 CFI = .995 TLI= .989 WRMSR= 1.258 Cases: 12994 V(EC2000)= 0.576 (0.020)

R.Q. 1: CHANGE OVER TIME? Unconditional latent growth curve models (estimator: WLSMV, cases: 12994) Factorial invariance tests: Chi-square difference test WEAK vs. STRONG invariance = 2006.722 (18 D.F.) However, strong invariance is needed for further analysis Strong-invariance model fit: Chi-square = 2232.461, 36 D.F. RMSEA 95% C.I. = .066 -.071 CFI = .938 TLI= .938 WRMSR= 4.919

R.Q. 1: CHANGE OVER TIME? Mean change across sweeps Mean Intercept= 0.000 (constraint); Variance= 0.422 (p-value= 0.000) Mean slope= -0.018 (p-value= 0.000); Variance= 0.000 (p-value= 0.092) Corr(Intercept, slope)= -0.216 (p-value=0.024): individuals with higher initial values record a steeper decline

R.Q. 2 & 3: socio-demographic predictors I Micro-level theory: Age, Social class, Place of residence, Political ideology, Gender, Partnership status, Presence of children

R.Q. 2 & 3: Socio-demographic predictors II -Time-invariant covariates model (TIC) (cases: 9127) when p-value<0.05

R.Q. 2 & 3: Socio-demographic predictors III -Time-varying covariates model (TVC) (cases: 6951)

Conclusions Model-fit indices: TIC vs. TVC Answer to research question 1: from 1991 to 2008-2009 the level of environmental concern as measured in the NCSD 1958 records a small but statistically significant decrease Answer to research question 2 and 3: political orientation is a consistent predictor of levels of environmental concern in our sample and amongst the theoretically relevant covariates of environmental concern accounted for in our study

Limitations Predictors/covariates of political orientation? Better measure of environmental concern Model complexity Relax assumption of Strong factorial invariance (Bayesian SEM?)

References DUNLAP, R. E. & JONES, R. E. 2002. Environmental concern: conceptual and measurement issues. In: DUNLAP, R. E. & MICHELSON, W. (eds.) Handbook of Environmental Sociology. Westport, CT: Greenwood Press. FRANSSON, N. & GARLING, T. 1999. Environmental concern: Conceptual definitions, measurement methods, and research findings. Journal of Environmental Psychology, 19, 369-382. LEISEROWITZ, A., MAIBACH, E. W., ROSER-RENOUF, C., SMITH, N. & DAWSON, E. 2010. Climategate, public opinion and the loss to trust. Social Science Research Network (SSRN) [Online]. Available: http://www.climatechangecommunication.org/images/files/Climategate_Public%20Opinion_and%20Loss%20of%20Trust%281%29.pdf [Accessed 31/05/2013]. NEWPORT, F. 2009. Americans: economy takes precedence over environment. First time majority has supported economy in 25 years of asking questions. Gallup Economy [Online]. Available: http://www.gallup.com/poll/116962/americans-economy-takes-precedence-environment.aspx [Accessed 15/05/2012]. Thank you!