Wage differentials by sector and gender: a quantile analysis for the Spanish case

Rahona-López, Marta; Murillo-Huertas, Inés P.; Salinas-Jiménez, María del Mar

doi:10.1080/17487870.2015.1028936

Cited by 11 publications

(6 citation statements)

References 37 publications

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“…Various studies on the wage inequality of workers have measured the following wage differentials between groups with unequal conditions such as men and women [ 51 , 52 ], private and public sectors [ 53 , 54 , 55 ], different races [ 56 , 57 ], regional concentrations and characteristics [ 58 , 59 ], urban residents and migrant workers [ 60 , 61 ], and industry type [ 62 ]. These studies all utilized the wage function proposed by Mincer [ 63 ].…”

Section: Theoretical Discussionmentioning

confidence: 99%

Wage Differentials between Heat-Exposure Risk and No Heat-Exposure Risk Groups

Kim

Lim

2017

IJERPH

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The goal of this study is to investigate the wage differential between groups of workers who are exposed to heat and those who are not. Workers in the heat-exposure risk group are defined as workers who work in conditions that cause them to spend more than 25% of their work hours at high temperatures. To analyze the wage differential, the Blinder-Oaxaca and Juhn-Murphy-Pierce methods were applied to Korea Working Condition Survey data. The results show that the no heat-exposure risk group received higher wages. In most cases, this can be interpreted as the endowment effect of human capital. As a price effect that lowers the endowment effect, the compensating differential for the heat-exposure risk group was found to be 1%. Moreover, education level, work experience, and employment status counteracted the compensating differentials for heat-exposure risks. A comparison of data sets from 2011 and 2014 shows that the increasing wage gap between the two groups was not caused by systematic social discrimination factors. This study suggests that wage differential factors can be modified for thermal environmental risks that will change working conditions as the impact of climate change increases.

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Section: Theoretical Discussionmentioning

confidence: 99%

Wage Differentials between Heat-Exposure Risk and No Heat-Exposure Risk Groups

Kim

Lim

2017

IJERPH

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“…For instance, Rahona-Lopez et al (2015) provide evidence to prove that public sector workers tend to earn higher wages than private employees in Spain due to favorable productivity characteristics of public sector workers. Also, a differential in wage adjustment between public and private sectors has been explored by Chistopoulou and Monastiriotis (2015) for Greece.…”

Section: Estimation Procedures and Resultsmentioning

confidence: 99%

Wage differentials in Sri Lanka: the case of a post-conflict country with a free education policy

Kumara

2015

IJEED

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This study analyses wage differentials in Sri Lanka by the individuals' educational attainment. The wage returns to education are estimated by using a combination of the techniques of ordinary least-square, two-stage least-square, sample-selection, and quantile regression on micro-data of the Sri Lanka Labour Force Survey-2013. Therefore, the estimates provided by this study are representative of the entire country and corrected for both the endogeniety and the sample-selection biases. The study concludes that education generates a positive impact on private earning. The results show that one additional year of schooling increases hourly wage rate by 9% approximately. Also, according to the results, the primary and secondary education reduces income inequality among people whereas the bachelor's-degree University education is a contributor to the income inequality. Further, the results relating to the additional controls reveal that the male, urban, and the public sector employees earn relatively higher wage returns.

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“…A strand of literature focuses on estimating the wage gap between the public and private sectors at different points on the wage distribution. Using the quantile regression technique, the studies report that the wage premium for public sector workers tends to be large at the bottom wage quantile and smaller at the top (Azam & Prakash, 2015; Bargain & Melly, 2008; Christofides & Michael, 2013; Depalo et al, 2015; Jürges, 2002; Lucifora & Meurs, 2006; Mueller, 1998; Nielsen & Rosholm, 2001; Rahona-López, Murillo-Huertas, & Salinas-Jiménez, 2016; Ramos, Sanromá, & Simón, 2014). However, Mizala, Romaguera and Gallegos (2011) for Latin America and Blackaby, Murphy and O’Leary (1999) for the UK find that public sector workers earn less than their private sector counterparts at the highest wage percentile.…”

Section: Related Literaturementioning

confidence: 99%

Public–Private Wage Gap in the Indian Mining and Quarrying Industry

Mohanty¹,

Mohanty²

2019

Margin: The Journal of Applied Economic Research

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This article examines if there is a wage gap between public and private mining (and quarrying) workers in India, using the NSS data (2004–2005, 2009–2010 and 2011–2012). We employ linear and quantile regressions to estimate the wage gap. The ordinary least squares (OLS) results suggest that workers in the public sector mines (and quarries) earn 59 per cent more than their private sector counterparts. However, the wage gap is not uniform across the conditional wage distribution. The quantile regression estimates show that the magnitude of the wage gap is larger at the bottom quantile than at the top; the gap reduces as we move up the wage distribution. Observations drawn from our sub-sample analysis concur with these findings. JEL Classification: J21, J31, J45

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Wage differentials by sector and gender: a quantile analysis for the Spanish case

Cited by 11 publications

References 37 publications

Wage Differentials between Heat-Exposure Risk and No Heat-Exposure Risk Groups

Wage Differentials between Heat-Exposure Risk and No Heat-Exposure Risk Groups

Wage differentials in Sri Lanka: the case of a post-conflict country with a free education policy

Public–Private Wage Gap in the Indian Mining and Quarrying Industry

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