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A Structure Analysis of the Correlated Random Coefficient Wage Regression Model Author info | Abstract | Publisher info | Download info | Related research | Statistics Belzil, Christian
Hansen, Jörgen
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We estimate a finite mixture dynamic programming model of schooling decisions in which the log wage regression function is set in a random coefficient framework. The model allows for absolute and comparative advantages in the labour market and assumes that the population is composed of eight unknown types. Overall, labour market skills (as opposed to taste for schooling) appear to be the prime factor explaining schooling attainments. The estimates indicate a higher cross-sectional variance in the returns to experience than in the returns to schooling. From various simulations, we find that the sub-population mostly affected by a counterfactual change in the utility of attending school is composed of individuals who have any combination of some of the following attributes: absolute advantages in the labour market, high returns to experience, low utility of attending school and relatively low returns to schooling. Unlike what is often postulated in the average treatment effect literature, the weak correlation (unconditional) between the returns to schooling and the individual reactions to treatment is not sufficient to reconcile the discrepancy between OLS and IV estimates of the returns to schooling often found in the literature.
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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
3601.
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Date of creation: Oct 2002Date of revision:
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Keywords: comparative advantages ; dynamic programming ; dynamic self-selection ; random coefficient ; returns to schooling ; Other versions of this item:
Article Paper Christian Belzil & Jörgen Hansen, 2004.
"A Structural Analysis of the Correlated Random Coefficient Wage Regression Model ,"
Working Papers
0405, Groupe d'Analyse et de Théorie Economique (GATE), Centre national de la recherche scientifique (CNRS), Université Lyon 2, Ecole Normale Supérieure.
[Downloadable!] Christian Belzil & Jörgen Hansen, 2002.
"A Structural Analysis of the Correlated Random Coefficient Wage Regression Model ,"
CIRANO Working Papers
2002s-07, CIRANO.
[Downloadable!] Belzil, Christian & Hansen, Jörgen, 2002.
"A Structural Analysis of the Correlated Random Coefficient Wage Regression Model ,"
IZA Discussion Papers
512, Institute for the Study of Labor (IZA).
[Downloadable!] Find related papers by JEL classification: J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
This paper has been announced in the following NEP Reports :
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Martin Kahanec, 2007.
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"The Return to Schooling in Structural Dynamic Models: A Survey ,"
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halshs-00142538_v1, HAL.
[Downloadable!] Christian Belzil, 2006.
"The Return to Schooling in Structural Dynamic Models: A Survey ,"
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[Downloadable!] (restricted) Christian Belzil & Jörgen Hansen, 2004.
"Earnings Dispersion, Risk Aversion and Education ,"
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"Earnings Dispersion, Risk Aversion and Education ,"
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[Downloadable!] Christian Belzil & Jörgen Hansen, 2002.
"Earnings Dispersion, Risk Aversion and Education ,"
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[Downloadable!] Christian Belzil & Jörgen Hansen, 2004.
"Earnings Dispersion, Risk Aversion and Education ,"
Working Papers
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"A Structural Analysis of the Correlated Random Coefficient Wage Regression Model with an Application to the OLS-IV Puzzle ,"
IZA Discussion Papers
1585, Institute for the Study of Labor (IZA).
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"Calibration and IV Estimation of a Wage Outcome Equation in a Dynamic Environment ,"
IZA Discussion Papers
3528, Institute for the Study of Labor (IZA).
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"Unobserved Ability and the Return to Schooling ,"
IZA Discussion Papers
508, Institute for the Study of Labor (IZA).
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567, Research Department of Statistics Norway.
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