Estimation of an Occupational Choice Model when Occupations are Misclassified

Abstract

This paper examines occupational choices using a discrete choice model that accounts for the fact that self-reported occupation data is measured with error. Despite evidence from validation studies which suggests that there is a substantial amount of measurement error in self-reported occupations, existing research has not corrected for classification error when estimating models of occupational choice. This paper develops a panel data model of occupational choices that corrects for misclassification in occupational choices and measurement error in occupation-specific work experience variables. The model is used to estimate the extent of measurement error in self-reported occupation data and quantify the bias that results from ignoring measurement error in occupation codes when studying the determinants of occupational choices and estimating the effects of occupation-specific human capital on wages. The parameter estimates reveal that 9% of occupational choices in the 1979 cohort of the National Longitudinal Survey of Youth are misclassified. Ignoring misclassification biases the median parameter in the occupational choice model by 25%.