GEE estimation of the covariance structure of a bivariate panel data model with an application to wage dynamics and the incidence of profit-sharing in West Germany

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Erscheinungsjahr:
2009
Medientyp:
Text
Schlagworte:
  • Generalized estimating equations
  • Longitudinal data
  • Random effects
  • Estimator
  • Models
  • Variable Selection
  • Generalized estimating equations
  • Longitudinal data
  • Random effects
  • Estimator
  • Models
  • Variable Selection
Beschreibung:
  • We propose a generalized estimating equations (GEE) approach to the estimation of the mean and covariance structure of bivariate time series processes of panel data. The one-step approach allows for mixed continuous and discrete dependent variables. A Monte Carlo Study is presented to compare our particular GEE estimator with more standard GEE-estimators. In the empirical illustration, we apply our estimator to the analysis of individual wage dynamics and the incidence of profit-sharing in West Germany. Our findings show that time-invariant unobserved individual ability jointly influences individual wages and participation in profit sharing schemes. © 2009 Springer-Verlag.
Lizenz:
  • info:eu-repo/semantics/closedAccess
Quellsystem:
Forschungsinformationssystem der UHH
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oai:www.edit.fis.uni-hamburg.de:publications/a470181b-1053-40db-ad6e-4ce50b86d1d0