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Separating risk from heterogeneity in education: a semiparametric approach
Author(s) -
Mazza Jacopo,
Ophem Hans
Publication year - 2018
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12253
Subject(s) - variance (accounting) , wage , econometrics , economics , estimation , variable (mathematics) , statistics , mathematics , labour economics , mathematical analysis , accounting , management
Summary Returns to education are variable both within and between educational group. If uncertain pay‐offs are a concern to individuals when selecting an education, wage variance is relevant. The variation is a combination of unobserved heterogeneity and pure uncertainty or risk. The first element is known to the individual, but unknown to the researcher; the second is unknown to both. As a result, the variance of wages observed in the data will overestimate the real magnitude of educational uncertainty and the effect that risk has on educational decisions. We apply a semiparametric estimation technique to tackle the selectivity issues. This method does not rely on distributional assumptions of the errors in the schooling choice and wage equations. Our results suggest that risk is decreasing in schooling. Private information accounts for a share varying between 0% and 13% of total wage variance observed depending on the educational level. Finally, we conclude that the estimation results are very sensitive to the functional relation that is imposed on the error structure.