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The Dynamics of Public Opinion on Cultural Policy Issues in the U.S., 1972–2010

Abstract

This study investigates the dynamics of public opinion on cultural policy issues over the past four decades. We find collective opinions on many such issues follow the same path over time, driven by an underlying cultural policy mood (CPM). We use more than 2,000 survey marginals, nested in more than 200 time series, that reflect aggregate opinions in 16 cultural policy domains, across 38 years. Using a dynamic principal components method, the results show that since the early 1970s, CPM has moved steadily and consistently in a liberal direction. Over this period, changes in CPM have been tightly linked to changes in aggregate religiosity. Opinion on two notable cultural issues—the death penalty and abortion—do not follow CPM. While public opinion has grown increasingly anti-death-penalty for more than a decade, over roughly the same period it has become as pro-life on abortion as at any time since Roe v. Wade. The measurement of CPM provides evidence of a macro construct of cultural issues that includes opinion toward many, but not all, morality policies.

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Notes

  1. 1.

    To develop the index of PPM, Stimson uses an algorithm that extracts a common, latent, ideological dimension from the survey marginals of many questions. For a given year, the several marginals for that year are combined into a single value that represents the ideological policy mood of the U.S. for that period. Similar to factor analysis, some items fit the latent PPM dimension better than others. The components that fit include especially items about taxes and spending. “The defining variables are essentially the New Deal issue cluster,” Stimson says, with the most important issues “hav[ing] to do with how much the federal government should or should not do or spend in intruding itself into the domains of health, education, welfare, environment, and racial equality.” (Stimson 1999, p. 70).

  2. 2.

    Although cultural opinions are said to arise from first principles, we wish to emphasize that we are not suggesting that issues outside of this domain—involving health care, education, etc.—do not implicate morality. Clearly they often do. Proponents sometimes appeal to values when taking positions on spending issues, and opinions on them may be derived from principles of ultimate justice. Indeed, although the issues in this study are sometimes appropriately labeled “moral” (e.g., Mooney 2001; Olson et al. 2006), we adopt the “cultural” rubric to avoid the implication that issues outside of this domain lack moral implications.

  3. 3.

    Reviews of each of these literatures in the context of the present study include, respectively, Mooney and Schuldt (2008), Dionne and Cromartie (2006), Carmines and Wagner (2006), and Layman et al. (2006).

  4. 4.

    The results of the database searches were cross referenced with the bibliographies of studies acquired in the search. In addition, although policies that implicate race are cultural in nature, because they are a domain with a policy mood of their own (see Kellstedt 2003), in the present analysis they are excluded at least initially. This assumption that racial issues are a separate dimension will be tested empirically in the section on discriminant validity.

  5. 5.

    The method accepts a single datum for each marginal. The conservative response was chosen in order to facilitate the comparison with the Aggregate Religiosity Index (ARI), discussed below. This choice turns out to be essentially arbitrary, as in the vast majority of opinion items the conservative response is simply the flip side of the liberal response. Alternative specifications were tested and they did not alter the results of this analysis whatsoever. In the relatively few questions that had multiple response options, the conservative responses were added together (e.g., “agree somewhat” was added to “agree strongly”) and used as the datum for the item.

  6. 6.

    The method imputes missing years of a given question series with the average from other ratios.

  7. 7.

    The method is discussed in greater detail in the Appendix of Stimson (1999).

  8. 8.

    Elizabeth K. Coggins, James A. Stimson, Mary Layton Atkinson, and Frank R. Baumgartner. “Absolute and Relative Opinion Change.” Unpublished Manuscript.

  9. 9.

    This approach is essentially the same as that used by Baumgartner et al. (2008) in their study of the politics of the death penalty in the U.S. However, they used a slightly different sample of items over a somewhat longer period of time. Also, while we standardized each of the indexes in our study to have a mean of 0 and standard deviation of 1, they scaled their measure to range from 0 to 100 and did not standardize the variance. Even so, their results look similar to those presented here.

  10. 10.

    Because the two series are nonstationary, this simple correlation may be misleading. However, differencing the variables makes them stationary, and the correlation between the differenced variables, as displayed in Table 4, is negative and statistically nonsignificant.

  11. 11.

    The RPM data was downloaded from Stimson’s website: http://www.unc.edu/jstimson.

  12. 12.

    To facilitate interpretation, RPM is coded so that higher values indicate racial conservatism and lower values reflect liberalism on race-related issues.

  13. 13.

    The analysis includes the marginals from each of the 27 administrations of these questions by the GSS between 1973 and 2010. The items are necessarily a subset of the more-than 9,000 indicators of PPM, which are not themselves publicly available.

  14. 14.

    As a final check of this analysis, we re-ran the dynamic principal components model of CPM while including in it the 15 GSS spending items. As one would expect, the loadings of the GSS items are similar to the correlations in the table. The inclusion of the GSS items diminishes the fit of the CPM index, reducing the variance explained from 58 to 52 %.

  15. 15.

    These data come from the Current Population Survey (CPS) and the Annual Social and Economic Supplement to the CPS.

  16. 16.

    The lag of CPM is included to estimate the rate of change. The model estimates the percent of the long-term effects that occur in each period as 1 − β1.

  17. 17.

    Future research can test whether this relationship is causal or the result of some intervening variable driving both ARI and CPM.

  18. 18.

    According to the model, 61 % of this long-term effect will happen by the next year (1 − 0.39), with an additional 61 % of the remainder the next year, and so on for each year.

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Acknowledgments

For helpful comments and suggestions we wish to thank Dave Campbell, John Clark, Rebecca Glazier, Steve Mockabee, and Corwin Smidt. We thank Jeffrey Linz, Josh Mitchell, and Maja Wright-Philips for research assistance.

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Correspondence to Kenneth Mulligan.

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Mulligan, K., Grant, T. & Bennett, D. The Dynamics of Public Opinion on Cultural Policy Issues in the U.S., 1972–2010. Polit Behav 35, 807–829 (2013). https://doi.org/10.1007/s11109-012-9209-x

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Keywords

  • Public opinion
  • Policy mood
  • Collective preferences
  • Morality policy
  • Cultural policy
  • Abortion
  • Abortion rights
  • Roe v. Wade
  • Gay rights
  • Death penalty
  • Time series