TY - JOUR
T1 - The persistence of wages
AU - Carneiro, Anabela
AU - Portugal, Pedro
AU - Raposo, Pedro
AU - Rodrigues, Paulo M. M.
N1 - Funding Information:
We are grateful to Editor Elie Tamer, Guest Editors David Card, Ian Schmutte, and Lars Vilhuber and three anonymous referees for their very useful comments and suggestions, which have contributed to improving the quality of the paper, as well as to Matei Demetrescu, Jonne Guyt and Geraldo Cerqueiro. This work was funded by Fundação para a Ciência e a Tecnologia through project number UID/Multi/00491/2019 , PTDC/EGE-ECO/28924/2017 , UID/ECO/00124/2013 , UID/ECO/00124/2019 , UID/GES/00407/2013 , UIDB/04105/2020 and Social Sciences DataLab ( LISBOA-01-0145-FEDER-022209 ), POR Lisboa ( LISBOA-01-0145-FEDER-007722 , LISBOA-01-0145-FEDER-022209 ), and POR Norte ( LISBOA-01-0145-FEDER-022209 ).
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023/4
Y1 - 2023/4
N2 - This paper documents the extent to which wage persistence can be explained by permanent worker, employer, and match heterogeneity. Standard methods used to perform such decompositions for industry or racial wage gaps are inappropriate for decomposing wage persistence in dynamic panel data models because of the incidental parameter problem. When we apply these methods without bias correction, we find that the majority, 59.3 percent, of wage persistence is explained by worker heterogeneity, with employer and match heterogeneity explaining 29.7 and 11.0 percent, respectively. We evaluate three methods for addressing incidental parameter bias using a Monte Carlo study. An empirical application to Portuguese linked employer–employee data shows that the uncorrected estimates tend to understate wage persistence by around 24 to 42 percent, depending on the choice of the bias correction estimator used, and overstate the extent to which wage persistence arises from permanent unobserved heterogeneity. Furthermore, results indicate that the uncorrected estimates overstate the role of permanent worker heterogeneity, and understate the role of firm heterogeneity.
AB - This paper documents the extent to which wage persistence can be explained by permanent worker, employer, and match heterogeneity. Standard methods used to perform such decompositions for industry or racial wage gaps are inappropriate for decomposing wage persistence in dynamic panel data models because of the incidental parameter problem. When we apply these methods without bias correction, we find that the majority, 59.3 percent, of wage persistence is explained by worker heterogeneity, with employer and match heterogeneity explaining 29.7 and 11.0 percent, respectively. We evaluate three methods for addressing incidental parameter bias using a Monte Carlo study. An empirical application to Portuguese linked employer–employee data shows that the uncorrected estimates tend to understate wage persistence by around 24 to 42 percent, depending on the choice of the bias correction estimator used, and overstate the extent to which wage persistence arises from permanent unobserved heterogeneity. Furthermore, results indicate that the uncorrected estimates overstate the role of permanent worker heterogeneity, and understate the role of firm heterogeneity.
KW - High-dimensional fixed effects
KW - Incidental parameter problem
KW - Match effects
KW - Wage persistence
UR - http://www.scopus.com/inward/record.url?scp=85122947674&partnerID=8YFLogxK
U2 - 10.1016/j.jeconom.2021.11.014
DO - 10.1016/j.jeconom.2021.11.014
M3 - Article
AN - SCOPUS:85122947674
SN - 0304-4076
VL - 233
SP - 596
EP - 611
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 2
ER -