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Title: A Quantile Correlated Random Coefficients Panel Data Model
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Graham, Bryan Hahn, Jinyong Poirier, Alexandre Powell, James L. |
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A Quantile Correlated Random Coefficients Panel Data Model Journal of Econometrics 206,2 (October 2018): 305-335. Also: https://www.sciencedirect.com/science/article/pii/S0304407618300952 Cohort(s): NLSY79 Publisher: Elsevier Keyword(s): Collective Bargaining; Earnings; Heterogeneity; Modeling, Fixed Effects We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the econometrician to (i) introduce dependence between the regressors and the random coefficients and (ii) weaken the assumption of comonotonicity across them (i.e., to enrich the structure of allowable dependence between different coefficients). We adopt a "fixed effects" approach, leaving any dependence between the regressors and the random coefficients unmodelled. We motivate different notions of quantile partial effects in our model and study their identification... We apply our methods to study the effects of collective bargaining coverage on earnings using the National Longitudinal Survey of Youth 1979 (NLSY79). Consistent with prior work (e.g., Chamberlain, 1982; Vella and Verbeek, 1998), we find that using panel data to control for unobserved worker heterogeneity results in sharply lower estimates of union wage premia. We estimate a median union wage premium of about 9 percent, but with, in a more novel finding, substantial heterogeneity across workers. |
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Bibliography Citation
Graham, Bryan, Jinyong Hahn, Alexandre Poirier and James L. Powell. "A Quantile Correlated Random Coefficients Panel Data Model." Journal of Econometrics 206,2 (October 2018): 305-335.
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