Panel data analysis of dentists’ activity under global budgeting in the presence of activityrelated non-response
AbstractThis 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.
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Bibliographic InfoPaper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 05/06.
Date of creation: Oct 2005
Date of revision:
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Postal: HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
Phone: (0)1904 323776
Fax: (0)1904 323759
Web page: http://www.york.ac.uk/res/herc/research/hedg/
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Dental care; global budgeting; unit non-response; attrition; panel data; selection on observables; inverse probability weighting; Taiwan;
Find related papers by 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; Longitudinal Data; Spatial Time Series
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