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A Zero-Inflated Regression Model for Grouped Data

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Listed:
  • Sarah Brown
  • Alan Duncan
  • Mark N. Harris
  • Jennifer Roberts
  • Karl Taylor

Abstract

type="main" xml:id="obes12086-abs-0001"> We introduce the (panel) zero-inflated interval regression (ZIIR) model, which is ideally suited when data are in the form of groups, and there is an ‘excess’ of zero observations. We apply our new modelling framework to the analysis of visits to the general practitioner (GP) using individual-level data from the British Household Panel Survey. The ZIIR model simultaneously estimates the probability of visiting the GP and the frequency of visits (defined by given numerical intervals in the data). The results show that different socio-economic factors influence the probability of visiting the GP and the frequency of visits.

Suggested Citation

  • Sarah Brown & Alan Duncan & Mark N. Harris & Jennifer Roberts & Karl Taylor, 2015. "A Zero-Inflated Regression Model for Grouped Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(6), pages 822-831, December.
    • Handle: RePEc:bla:obuest:v:77:y:2015:i:6:p:822-831
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    File URL: http://hdl.handle.net/10.1111/obes.2015.77.issue-6
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    References listed on IDEAS

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    1. Freund, Deborah A. & Kniesner, Thomas J. & LoSasso, Anthony T., 1999. "Dealing with the common econometric problems of count data with excess zeros, endogenous treatment effects, and attrition bias," Economics Letters, Elsevier, vol. 62(1), pages 7-12, January.
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    5. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.
    6. Gurmu, Shiferaw & Elder, John, 2008. "A bivariate zero-inflated count data regression model with unrestricted correlation," Economics Letters, Elsevier, vol. 100(2), pages 245-248, August.
    7. Wang, Peiming, 2003. "A bivariate zero-inflated negative binomial regression model for count data with excess zeros," Economics Letters, Elsevier, vol. 78(3), pages 373-378, March.
    8. Harris, Mark N. & Zhao, Xueyan, 2007. "A zero-inflated ordered probit model, with an application to modelling tobacco consumption," Journal of Econometrics, Elsevier, vol. 141(2), pages 1073-1099, December.
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    Cited by:

    1. Davillas, Apostolos & Pudney, Stephen, 2020. "Using biomarkers to predict healthcare costs: Evidence from a UK household panel," Journal of Health Economics, Elsevier, vol. 73(C).
    2. Fichera, Eleonora & Emsley, Richard & Sutton, Matt, 2016. "Is treatment “intensity” associated with healthier lifestyle choices? An application of the dose response function," Economics & Human Biology, Elsevier, vol. 23(C), pages 149-163.
    3. Cristian Roner & Claudia Di Caterina & Davide Ferrari, 2021. "Exponential Tilting for Zero-inflated Interval Regression with Applications to Cyber Security Survey Data," BEMPS - Bozen Economics & Management Paper Series BEMPS85, Faculty of Economics and Management at the Free University of Bozen.
    4. Gregory N. Price, 2019. "Does Productivity in the Formal Food Sector Drive Human Ebola Virus Infections in Sub‐Saharan Africa?," African Development Review, African Development Bank, vol. 31(2), pages 167-178, June.

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    More about this item

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D1 - Microeconomics - - Household Behavior
    • I1 - Health, Education, and Welfare - - Health

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