Using quantile and asymmetric least squares regression for optimal risk adjustment
Year of publication: |
June 2017
|
---|---|
Authors: | Lorenz, Normann |
Published in: |
Health economics. - Chichester : Wiley-Blackwell, ISSN 1057-9230, ZDB-ID 1135838-5. - Vol. 26.2017, 6, p. 724-742
|
Subject: | risk selection | risk adjustment | contest | quantile regression | asymmetric least squares regression | Regressionsanalyse | Regression analysis | Kleinste-Quadrate-Methode | Least squares method | Schätztheorie | Estimation theory |
-
Using quantile regression for optimal risk adjustment
Lorenz, Normann, (2014)
-
Least weighted squares quantiles reveal how competitiveness contributes to tourism performance
Kalina, Jan, (2022)
-
Out of shape : the implications of (extremely) nonnormal dependent variables
Certo, S. Trevis, (2024)
- More ...
-
Optimal cost reimbursement of health insurers to reduce risk selection
Kifmann, Mathias, (2005)
-
Health Care Expenditures and Longevity: Is there a Eubie Blake Effect?
Breyer, Friedrich, (2012)
-
Adverse selection and risk adjustment under imperfect competition
Lorenz, Normann, (2013)
- More ...