Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/90754 
Authors: 
Year of Publication: 
2013
Series/Report no.: 
Memorandum No. 08/2013
Publisher: 
University of Oslo, Department of Economics, Oslo
Abstract: 
In the paper is considered identification of coefficients in equations explaining a continuous variable, say the number of sickness absence days of an individual per year, by cohort, time and age, subject to their definitional identity. Extensions of a linear equation to polynomials, including additive polynomials, are explored. The cohort+time=age identity makes the treatment of interactions important. If no interactions between the three variables are included, only the coefficients of the linear terms remain unidentified unless additional information is available. Illustrations using a large data set for individual long-term sickness absence in Norway are given. The sensitivity to the estimated marginal effects of cohort and age at the samplemean, as well as conclusions about the equations' curvature, are illustrated. We find notable differences in this respect between linear and quadratic equations on the one hand and cubic and fourth-order polynomials on the other.
Subjects: 
age-cohort-time problem
identification
polynomial regression
interaction
age-cohort curvature
panel data
sickness absence
JEL: 
C23
C24
C25
C52
H55
I18
J21
Document Type: 
Working Paper

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