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A Mixture Model for Middle Category Inflation in Ordered Survey Responses

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  • Bagozzi, Benjamin E.
  • Mukherjee, Bumba

Abstract

Recent research finds that, for social desirability reasons, uninformed individuals disproportionately give “neither agree nor disagree†type responses to survey attitude questions, even when a “do not know†option is available. Such “face-saving†responses inflate the indifference (i.e., middle) categories of ordered attitude variables with nonordered responses. When such inflation occurs within the middle category of one's ordered dependent variable, estimates from ordered probit (and ordered logit) models are likely to be unreliable and inefficient. This article develops a set of mixture models that estimate and account for the presence of “face-saving†responses in middle categories of ordered survey response variables, and applies these models to (1) simulated data and (2) a commonly studied survey question measuring attitudes toward European Union (EU) membership among individuals in EU-candidate countries. Results from the survey data set and the Monte Carlo experiments suggest that, when middle category inflation is present in one's ordered dependent variable, the estimates obtained from middle category mixture models are less biased than—and in some cases substantively distinct from—the estimates obtained from “naive†ordered probit models.

Suggested Citation

  • Bagozzi, Benjamin E. & Mukherjee, Bumba, 2012. "A Mixture Model for Middle Category Inflation in Ordered Survey Responses," Political Analysis, Cambridge University Press, vol. 20(3), pages 369-386, July.
  • Handle: RePEc:cup:polals:v:20:y:2012:i:03:p:369-386_01
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    Cited by:

    1. Greene, William H. & Gillman, Max & Harris, Mark N. & Spencer, Christopher, 2013. "The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy," CEI Working Paper Series 2013-04, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    2. David Dale & Andrei Sirchenko, 2021. "Estimation of nested and zero-inflated ordered probit models," Stata Journal, StataCorp LP, vol. 21(1), pages 3-38, March.
    3. Sarah Brown & Mark N. Harris & Christopher Spencer & Karl Taylor, 2020. "Financial Expectations and Household Consumption: Does Middle Inflation Matter?," Working Papers 2020002, The University of Sheffield, Department of Economics.
    4. Belderbos, Rene & Ikeuchi, Kenta & Fukao, Kyoji & Kim, Young Gak & Kwon, Hyeog Ug, 2013. "Plant Productivity Dynamics and Private and Public R&D Spillovers: Technological, Geographic and Relational Proximity," CEI Working Paper Series 2013-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    5. Makram El‐Shagi & Gregor von Schweinitz, 2022. "Why they keep missing: An empirical investigation of sovereign bond ratings and their timing," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 186-224, May.
    6. Hantzsche, Arno, 2022. "Fiscal uncertainty and sovereign credit risk," European Economic Review, Elsevier, vol. 148(C).
    7. Tianji Cai & Yiwei Xia & Yisu Zhou, 2021. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," Sociological Methods & Research, , vol. 50(1), pages 365-400, February.
    8. Fumagalli, Elena & Fumagalli, Laura, 2022. "Subjective well-being and the gender composition of the reference group: Evidence from a survey experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 196-219.
    9. Tennant, David F. & Tracey, Marlon R. & King, Damien W., 2020. "Sovereign credit rating: Evidence of bias against poor countries," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    10. Andrei A. Sirchenko, 2017. "An endogenous regime-switching model of ordered choice with an application to federal funds rate target," 2017 Papers psi424, Job Market Papers.
    11. El-Shagi, Makram & von Schweinitz, Gregor, 2017. "Why they keep missing: An empirical investigation of rational inattention of rating agencies," IWH Discussion Papers 1/2017, Halle Institute for Economic Research (IWH), revised 2017.
    12. Benjamin E. Bagozzi, 2016. "The baseline-inflated multinomial logit model for international relations research," Conflict Management and Peace Science, Peace Science Society (International), vol. 33(2), pages 174-197, April.
    13. Sarah Brown & Mark N. Harris & Christopher Spencer, 2020. "Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1342-1361, December.
    14. Cai, Tianji & Xia, Yiwei & Zhou, Yisu, 2017. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," SocArXiv 4r2j3, Center for Open Science.
    15. Stephen Weymouth & J. Lawrence Broz, 2013. "Government Partisanship and Property Rights: Cross-Country Firm-Level Evidence," Economics and Politics, Wiley Blackwell, vol. 25(2), pages 229-256, July.

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