Description Usage Format Source References
Data is from Riphahn, Wambach and Million (2003), used for studying longitudinal analysis concerning the usage of the German health insurance system. The original data contain a few years data for patients, but we have only for first year.
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A data frame with 7293 observations of 26 variables as below;
identification number (numeric)
female or not (categorical)
year (categorical)
age (numeric)
health satisfaction coded 0 (low) to 10 (high) (numeric)
person is handicappe or not (categorical)
percentage degree of handicap (numeric)
monthly household net income (numeric)
child (ren) below age 16 in household (numeric)
years of schooling (numeric)
person is married or not (categorical)
level of schooling (categorical)
level of schooling (categorical)
level of schooling (categorical)
level of schooling (categorical)
level of schooling (categorical)
employed or not (categorical)
person is blue collar worker or not (categorical)
person is white collar worker or not (categorical)
person is self-employed or not (categorical)
civil servant or not (categorical)
number of doctor visits in last 3 months (numeric)
number of hospital visits last year (numeric)
person is insured in public health insurance or not (categorical)
person is insured in add-on insurance or not (categorical)
scaled income; original income/1000 (numeric)
Riphahn, R. T., Wambach, A. and Million, A. (2003) Incentive Effects in the Demand for Health Care: A Bivariate Panel Count Data Estimation, Journal of Applied Econometrics, 18, 4, 387–405. Published online 8 October 2002. https://doi.org/10.1002/jae.680
http://qed.econ.queensu.ca/jae/2003-v18.4/riphahn-wambach-million/
Greene, W. H. (2012) Econometric Analysis, 7th Edition. Pearson education.
Azzalini, A., Kim, H.-M. and Kim, H.-J. (2019) Sample selection models for discrete and other non-Gaussian response variables. Statistical Methods & Applications, 28, 27–56. First online 30 March 2018. https://doi.org/10.1007/s10260-018-0427-1
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