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Panel data analysis of dentists’ activity under global budgeting in the presence of activityrelated non-response

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  • Miaw-Chwen Lee
  • Andrew M Jones

Abstract

This paper evaluates the impact of the introduction of global budgeting on dentists’ activity in Taiwan using a unique and rich panel dataset that was created specifically for the task. The panel data for 4424 dentists over 48 months, January 1997 to December 2000, was drawn from the BNHI’s data warehouse. The dataset has approximately 66% of dentists who are not observed over all periods. The paper examines the existence and consequences of unit nonresponse on estimates of the response of dentists’ activity to the introduction of global budgeting. It is based on the framework of selection on observables. We apply three techniques to assess the existence and magnitude of non-response bias: (1) probit models for non-response (2) variable addition tests (3) inverse probability weighting. The results show evidence of activity-related non-response. Non-response is concentrated among dentists with lower and unstable daily numbers of visits and with higher income. Non-response has substantial influence on the estimates of the mix of services provided to patients. The empirical results shed light on the emergence of a two-tier dental care system due to the introduction of global budgeting.

Suggested Citation

  • Miaw-Chwen Lee & Andrew M Jones, 2005. "Panel data analysis of dentists’ activity under global budgeting in the presence of activityrelated non-response," Health, Econometrics and Data Group (HEDG) Working Papers 05/06, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:05/06
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    More about this item

    Keywords

    Dental care; global budgeting; unit non-response; attrition; panel data; selection on observables; inverse probability weighting; Taiwan;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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