Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/186066 
Year of Publication: 
2017
Citation: 
[Journal:] Swiss Journal of Economics and Statistics [ISSN:] 2235-6282 [Volume:] 153 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2017 [Pages:] 1-13
Publisher: 
Springer, Heidelberg
Abstract: 
We propose a new non-linear regression model for rating dependent variables. The rating scale model accounts for the upper and lower bounds of ratings. Parametric and semi-parametric estimation is discussed. An application investigates the relationship between stated health satisfaction and physical and mental health scores derived from self-reports of various health impairments, using data from the German Socio-Economic Panel. We compare our new approach to modeling ratings with ordinary least squares (OLS). In one specification, OLS average effects exceed that from our rating scale model by up to 50 percent. Also, OLS in-sample mean predictions violate the upper bound of the dependent variable in a number of cases.
Subjects: 
Quasi maximum likelihood
bounded dependent variable
German Socio-Economic Panel
JEL: 
C25
I10
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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