A Zero Inflated Regression Model for Grouped Data
AbstractWe introduce the (panel) zero-inflated interval regression (ZIIR) model, which is ideally suited when data are in the form of groups, which is commonly the case in survey data, and there is an ‘excess’ of zero observations. We apply our new modelling framework to the analysis of visits to general practitioners (GPs) using individual-level panel data from the British Household Panel Survey (BHPS). 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, thereby providing potentially valuable information to policy-makers concerned with health care allocation.
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Bibliographic InfoPaper provided by Bankwest Curtin Economics Centre (BCEC), Curtin Business School in its series Bankwest Curtin Economics Centre Working Paper series with number WP1401.
Length: 14 pages
Date of creation: Jan 2014
Date of revision:
interval regression; inflated responses; health care allocation; general practitioners;
Find related papers by 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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