Quality & Quantity

, Volume 52, Issue 3, pp 969–982 | Cite as

Religious pluralism and religious participation: a median-based approach to the non-substantive problem

  • Anning Hu


Sociologists of religion have long been interested in the interaction between religious pluralism and religious vitality. Previous empirical studies approach this theme by drawing on data of denominational participation rates across geographical units, investigating the property of association between the quantity of one minus the Herfindahl–Hirschman Index (religious pluralism), and the total religious participation rate (religious vitality). However, this association could be theoretically spurious. Taking advantage of the median’s statistical property of being less sensitive to the variations of extreme values, this study proposes to apply the median instead of the arithmetic summation of religious participation rates to measure geographical-unit-level religious vitality. This method is illustrated by analyzing the New York State census of religion 1865 and the U.S. county survey 1990.


Religious pluralism Religious prevalence Non-substantive connection Religious economies theory Median-based test 



This study was partly supported by the School of Social Development and Public Policy, Fudan University.


  1. Angrist, J.D., Pischke, J.-S.: Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press, Princeton (2009)Google Scholar
  2. Barro, J.Robert, McCleary, R.M.: Religion and economic growth across countries. Am. Sociol. Rev. 68(5), 760–781 (2003)CrossRefGoogle Scholar
  3. Berger, P.: The Sacred Canopy: Elements of a Sociological Theory of Religion. Anchor, New York (1967)Google Scholar
  4. Chaves, M., Gorski, P.: Religious pluralism and religious participation. Ann. Rev. Sociol. 27, 261–281 (2001)CrossRefGoogle Scholar
  5. Demographia International.: 4th Annual Demographia International Housing Affordability Survey, retrieved at (2008)
  6. Donoho, D.L., Gasko, M.: Breakdown properties of location estimates based on halfspace depth and projected outlyingness. Ann. Stat. 20(4), 1803–1827 (1992)CrossRefGoogle Scholar
  7. Hannan, T.H.: Market share inequality, the number of competitors, and the HHI: an examination of bank pricing. Rev. Ind. Organ. 12, 23–35 (1997)CrossRefGoogle Scholar
  8. Hao, L., Naiman, D.Q.: Quantile Regression. Sage, Thousand Oaks (2007)CrossRefGoogle Scholar
  9. Imbens, G., Rubin, D.: Causal inference in statistics, social, and biomedical sciences. Cambridge University Press, Cambridge (2015)CrossRefGoogle Scholar
  10. Imbens, G., Angrist, J.: Identification and estimation of local average treatment effects. Econometrica 62(2), 467–475 (1994)CrossRefGoogle Scholar
  11. Kocak, O., Carroll, G.: Growing church organizations in diverse U.S. communities, 1890–1960. Am. J. Sociol. 113, 1272–1315 (2008)CrossRefGoogle Scholar
  12. Montgomery, J.: A formalization and test of the religious economies model. Am. Sociol. Rev. 68, 782–809 (2003)CrossRefGoogle Scholar
  13. Olson, D.: Religious pluralism and U. S. church membership: a reassessment. Sociol Relig 60, 149–173 (1999)CrossRefGoogle Scholar
  14. Stark, R., Finke, R.: Acts of faith: Explaining the human side of religion. University of California Press, Berkeley (2000)Google Scholar
  15. Stigler, S.M.: Studies in the history of probability and statistics. Biometrika 60(3), 439–445 (1973)Google Scholar
  16. Voas, D., Crockett, A., Olson, Daniel V.A.: Religious pluralism and participation: why previous research is wrong. Am. Sociol. Rev. 67(2), 212–230 (2002)CrossRefGoogle Scholar
  17. Young, C.: Model uncertainty in sociological research: an application to religion and economic growth. Am. Sociol. Rev. 74, 380–397 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  1. 1.Fudan UniversityShanghaiChina

Personalised recommendations