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Environmental Concern Over Time: Evidence from the Longitudinal Analysis of a British Cohort Study from 1991 to 2008

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  • Gabriella Melis
  • Mark Elliot
  • Nick Shryane

Abstract

type="main"> We examined whether and how levels of environmental concern (EC) changed over time in the United Kingdom, from 1991 to 2008–2009, as well as how EC relates to socioeconomic characteristics across this same timeframe. Using item response theory models on the last three sweeps of the British National Child Development Study 1958, we evaluated a measure of EC. Then, using latent growth curve models (LGCMs) we estimated the pattern of change for EC across time. Finally, theoretically relevant sociodemographic characteristics were introduced as covariates into the LGCM. We found a small but significant downfall of the mean level of EC over time, with individual-level values displaying higher dispersion in 2008–2009 against the previous sweeps of data. We also found that political orientation has significant effects on the outcome and on its changes across time. Hypotheses regarding the influence of interest in politics and voting choices on EC are supported. The increasing variance of EC over time warrants further investigation.

Suggested Citation

  • Gabriella Melis & Mark Elliot & Nick Shryane, 2014. "Environmental Concern Over Time: Evidence from the Longitudinal Analysis of a British Cohort Study from 1991 to 2008," Social Science Quarterly, Southwestern Social Science Association, vol. 95(4), pages 905-919, December.
  • Handle: RePEc:bla:socsci:v:95:y:2014:i:4:p:905-919
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    File URL: http://hdl.handle.net/10.1111/ssqu.12107
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    1. Roderick J. A. Little & Donald B. Rubin, 1989. "The Analysis of Social Science Data with Missing Values," Sociological Methods & Research, , vol. 18(2-3), pages 292-326, November.
    2. Axel Franzen & Dominikus Vogl, 2013. "Acquiescence and the Willingness to Pay for Environmental Protection: A Comparison of the ISSP, WVS, and EVS," Social Science Quarterly, Southwestern Social Science Association, vol. 94(3), pages 637-659, September.
    3. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    4. Denise Hawkes & Ian Plewis, 2006. "Modelling non‐response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491, July.
    5. Frederic Lord, 1965. "A note on the normal ogive or logistic curve in item analysis," Psychometrika, Springer;The Psychometric Society, vol. 30(3), pages 371-372, September.
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    1. Andersson-Hudson, Jessica & Knight, William & Humphrey, Mathew & O’Hara, Sarah, 2016. "Exploring support for shale gas extraction in the United Kingdom," Energy Policy, Elsevier, vol. 98(C), pages 582-589.
    2. Lorteau, Steve & Muzzerall, Parker & Deneault, Audrey-Ann & Kennedy, Emily Huddart & Rocque, Rhéa & Racine, Nicole & Bureau, Jean-François, 2024. "Do climate concerns and worries predict energy preferences? A meta-analysis," Energy Policy, Elsevier, vol. 190(C).
    3. Ting Liu & Nick Shryane & Mark Elliot, 2022. "Attitudes to climate change risk: classification of and transitions in the UK population between 2012 and 2020," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    4. Zeynep Altinay & Eric Rittmeyer & Lauren L. Morris & Margaret A. Reams, 2021. "Public risk salience of sea level rise in Louisiana, United States," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 11(4), pages 523-536, December.

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    More about this item

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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