Estimating German overqualification with stochastic earnings frontiers

DOI10.1007/s10182-009-0121-6zbMath1443.62473OpenAlexW2018821661MaRDI QIDQ1635008

Hermann Gartner, Susanne Rässler, Uwe Jensen

Publication date: 18 December 2018

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-009-0121-6

zbMATH Keywords

multiple imputationcensored dataearnings frontiersIAB employment sampleovereducationoverqualification

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Labor markets (91B39)

Related Items (1)

The case for the use of multiple imputation missing data methods in stochastic frontier analysis with illustration using English local highway data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Survey item nonresponse and its treatment
• Likelihood functions for generalized stochastic frontier estimation
• Bayes inference in the Tobit censored regression model
• Formulation and estimation of stochastic frontier production function models
• Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
• The Skill Content of Recent Technological Change: An Empirical Exploration
• Revisiting the German Wage Structure^*

This page was built for publication: Estimating German overqualification with stochastic earnings frontiers