Measuring wage inequality under right censoring

João Nicolau; Pedro Raposo; Paulo M. M. Rodrigues

doi:10.1111/ecin.13119

Measuring wage inequality under right censoring

João Nicolau, Pedro Raposo^*, Paulo M. M. Rodrigues

^*Corresponding author for this work

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Abstract

A conditional tail index estimator is introduced which explicitly allows for right-tail censoring (top-coding). We show that the factor values used to adjust top-coded wages have changed over time and depend on individuals' characteristics, occupations and industries, and propose suitable values. Specifically, contrasting the results of our approach with those of a conservative fixed adjustment factor of 1.5 (used in the literature), suggests that wage inequality in 2017 measured with the Gini coefficient is larger than that suggested by the fixed adjustment factor.

Original language	English
Pages (from-to)	377-401
Number of pages	25
Journal	Economic Inquiry
Volume	61
Issue number	2
DOIs	https://doi.org/10.1111/ecin.13119
Publication status	Published - Apr 2023

Keywords

Current population survey
Occupations
Pareto
Tail index
Top-coding
Wage inequality
Weekly wage distribution

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/ecin.13119Licence: CC BY

51020179Final published version, 1.78 MBLicence: CC BY

http://hdl.handle.net/10400.14/40480Licence: CC BY

Cite this

@article{d70738e5d05045058d67d1540c008af4,

title = "Measuring wage inequality under right censoring",

abstract = "A conditional tail index estimator is introduced which explicitly allows for right-tail censoring (top-coding). We show that the factor values used to adjust top-coded wages have changed over time and depend on individuals' characteristics, occupations and industries, and propose suitable values. Specifically, contrasting the results of our approach with those of a conservative fixed adjustment factor of 1.5 (used in the literature), suggests that wage inequality in 2017 measured with the Gini coefficient is larger than that suggested by the fixed adjustment factor.",

keywords = "Current population survey, Occupations, Pareto, Tail index, Top-coding, Wage inequality, Weekly wage distribution",

author = "Jo{\~a}o Nicolau and Pedro Raposo and Rodrigues, {Paulo M. M.}",

note = "Funding Information: The authors thank two anonymous referees, the Co‐Editor (Shankha Chakraborty), Daron Acemoglu, David Autor, Manuel Arellano, participants of the Workshop on and of the IX Workshop in for their helpful and constructive feedback on an earlier version of this paper, and Filipe Caires for excellent research assistance. This work was funded by Funda{\c c}{\~a}o para a Ci{\^e}ncia e 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/05069/2020 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). New Frontiers in Statistics of Extremes t Time Series Econometrics Funding Information: The authors thank two anonymous referees, the Co-Editor (Shankha Chakraborty), Daron Acemoglu, David Autor, Manuel Arellano, participants of the Workshop on New Frontiers in Statistics of Extremes and of the IXt Workshop in Time Series Econometrics for their helpful and constructive feedback on an earlier version of this paper, and Filipe Caires for excellent research assistance. This work was funded by Funda{\c c}{\~a}o para a Ci{\^e}ncia e 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/05069/2020 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: {\textcopyright} 2022 Western Economic Association International.",

year = "2023",

month = apr,

doi = "10.1111/ecin.13119",

language = "English",

volume = "61",

pages = "377--401",

journal = "Economic Inquiry",

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N2 - A conditional tail index estimator is introduced which explicitly allows for right-tail censoring (top-coding). We show that the factor values used to adjust top-coded wages have changed over time and depend on individuals' characteristics, occupations and industries, and propose suitable values. Specifically, contrasting the results of our approach with those of a conservative fixed adjustment factor of 1.5 (used in the literature), suggests that wage inequality in 2017 measured with the Gini coefficient is larger than that suggested by the fixed adjustment factor.

AB - A conditional tail index estimator is introduced which explicitly allows for right-tail censoring (top-coding). We show that the factor values used to adjust top-coded wages have changed over time and depend on individuals' characteristics, occupations and industries, and propose suitable values. Specifically, contrasting the results of our approach with those of a conservative fixed adjustment factor of 1.5 (used in the literature), suggests that wage inequality in 2017 measured with the Gini coefficient is larger than that suggested by the fixed adjustment factor.

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KW - Occupations

KW - Pareto

KW - Tail index

KW - Top-coding

KW - Wage inequality

KW - Weekly wage distribution

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M3 - Article

SN - 0095-2583

VL - 61

SP - 377

EP - 401

JO - Economic Inquiry

JF - Economic Inquiry

IS - 2

ER -

Measuring wage inequality under right censoring

Abstract

Keywords

UN SDGs

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CUBE: Católica Lisbon Research Unit in Business and Economics

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Measuring wage inequality under right censoring

Abstract

Keywords

UN SDGs

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CUBE: Católica Lisbon Research Unit in Business and Economics

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