Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/192649 
Year of Publication: 
2011
Series/Report no.: 
Discussion Papers No. 667
Publisher: 
Statistics Norway, Research Department, Oslo
Abstract: 
A model for matched data with two types of unobserved heterogeneity is considered - one related to the observation unit, the other to units to which the observation units are matched. One or both of the unobserved components are assumed to be random. Applying the Helmert transformation to reduce dimensionality simplifies the computational problem substantially. The framework has many potential applications; we apply it to wage modeling. Traditionally, unobserved individual and firm heterogeneity in wage equations have been represented by fixed effects. However, because of the presence of time-invariant covariates, we argue that specifications with random effects also deserve some attention. Our mixed model allows identification of the effects of time invariant variables on wages, such as for instance education. Using Norwegian manufacturing data it turns out that the assumption with respect to firm-specific unobserved heterogeneity affects the estimate of the return to education considerably.
Subjects: 
High-dimensional two-way unobserved components
Matched employer-employee data
ECM-algorithm
JEL: 
C23
C81
J31
Document Type: 
Working Paper

Files in This Item:
File
Size
190.29 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.