Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/56521 
Year of Publication: 
2011
Series/Report no.: 
MAGKS Joint Discussion Paper Series in Economics No. 48-2011
Publisher: 
Philipps-University Marburg, Faculty of Business Administration and Economics, Marburg
Abstract: 
In many countries the demand for health care services is of increasing importance. Especially in the industrialized world with a changing demographic structure social insurances and politics face real challenges. Reliable predictors of those demand functions will therefore become invaluable tools. This article proposes a prediction method for the distribution of the number of visits to the medical doctor for a determined population, given a sample that is not necessarily taken from that population. It uses the estimated conditional sample distribution, and it can be applied for forecast scenarios. The methods are illustrated along data from Sidney. The introduced methodology can be applied as well to any other prediction problem of discrete distributions in real, future or any fictitious population. It is therefore also an excellent tool for future predictions, scenarios and policy evaluation.
Subjects: 
predicting health care demand
visits to the doctor
health economics
model selection
JEL: 
I12
C51
C53
H75
Document Type: 
Working Paper

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