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Sudden Transitions in Attitudes

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  • Han L. J. van der Maas
  • Rogier Kolstein
  • Joop van der Pligt

Abstract

Both the dynamic approach and catastrophe modeling have been warmly welcomed in research on attitudes and opinions. In this article, the authors discuss a general methodology for testing catastrophe models and apply it to the dynamics of attitude formation and change. First, by making use of the so-called catastrophe flags, converging support for the catastrophe model can be attained. Each flag relates to a specific hypothesis about attitudinal change. Second, fitting stochastic catastrophe models to data enables one to carry out a direct test of catastrophe models. Results of analyzing large data sets on political attitudes support the validity of the general catastrophe model of attitude change in which transitions in attitudes are a function of involvement and information. Present results suggest that in the case of political attitudes, involvement might well be correlated with attitude. A more refined approach to the measurement of information and involvement is suggested.

Suggested Citation

  • Han L. J. van der Maas & Rogier Kolstein & Joop van der Pligt, 2003. "Sudden Transitions in Attitudes," Sociological Methods & Research, , vol. 32(2), pages 125-152, November.
  • Handle: RePEc:sae:somere:v:32:y:2003:i:2:p:125-152
    DOI: 10.1177/0049124103253773
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    References listed on IDEAS

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    1. Lange Rense & Oliva Terence A. & McDade Sean R., 2000. "An Algorithm for Estimating Multivariate Catastrophe Models: GEMCAT II," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(3), pages 1-34, October.
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    1. repec:jss:jstsof:32:i08 is not listed on IDEAS
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    3. Teun Terpstra & Jan Gutteling & Bert Kappe & Govert Geldof, 2005. "The perception of flooding and water nuisance," ERSA conference papers ersa05p760, European Regional Science Association.
    4. Wang, J., 2015. "Can a stochastic cusp catastrophe model explain housing market crashes?," CeNDEF Working Papers 15-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

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