Wage differences according to health status in France

Halima, Mohamed Ali Ben; Rococo, Emeline

doi:10.1016/j.socscimed.2014.09.035

Cited by 11 publications

(10 citation statements)

References 16 publications

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“…discrimination. These results align with those of previous studies conducted in Europe and the United States, which have also reported that disability-related discrimination contributes to 30-50% of wage differentials Johnson 1994, 1995;DeLeire 2001;Halima and Rococo 2014;Johnson and Lambrinos 1985;Jones, Latreille and Sloane 2006a).…”

Section: Decomposition Of Wage Differentialssupporting

confidence: 92%

“…Globally, people with disabilities (PWD) face persistent wage disparities when compared to people without disabilities (PWOD), a phenomenon extensively documented across various countries (Baldwin and Choe 2014;Johnson 1994, 1995;DeLeire 2001;Gunderson and Lee 2016;Hallock, Jin and Waldman 2022;Johnson and Lambrinos 1985;Jones, Latreille and Sloane 2006a;Kidd, Sloane and Ferko 2000). Two primary factors are often cited to account for this wage gap: a productivity difference suggesting that PWD are less productive than PWOD due to varying levels of human capital investment, and a discrimination effect whereby employer prejudice diminishes earnings (Becker 1964;Castro, Moreira and Silva 2019;Cavanagh et al 2017;Cooke and Zhao 2020;Halima and Rococo 2014;Malo and Pagán 2012;Mincer 1974;Schur, Kruse and Blanck 2005). The prevailing theories of human capital and labor market discrimination provide frameworks to understand these disparities (Becker 1964(Becker , 1971Mincer 1974;Schultz 1961), yet their application yields different conclusions across diverse socioeconomic landscapes.…”

Section: Introductionmentioning

confidence: 99%

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Productivity difference or discrimination effect? Disability‐related wage gap in China

Liao,

Gao,

Zhu

et al. 2024

Asia Pac J Human Res

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The wage gap between people with disabilities (PWD) and people without disabilities (PWOD), which discourages PWD from entering the labor market, is attributed to two factors: productivity differences and discrimination effects. To determine whether PWD in China face wage discrimination in the labor market and which factor contributes more to the disability‐related wage gap in China, this study uses Chinese Household Income Project data (years 2007 and 2013) to estimate disability‐related wage discrimination, decomposing the wage gap between PWD and PWOD using the Oaxaca‐Blinder and Neumark approach. The findings demonstrate the presence of disability‐related discrimination in China, accounting for approximately 38.9%–52.4% of the wage gap between PWD and PWOD. Unobservable productivity effects contribute more to the wage gap than does disability‐related discrimination. Male PWD living in rural areas and less educated people are more likely to experience wage discrimination in China. Moreover, individuals with disabilities in rural areas experience significant disability‐related discrimination, whereas no such phenomenon is observed in urban or migrant populations. Future human resource management policies should consider antidiscrimination measures and improve the productivity of PWD, including providing reasonable accommodation for PWD in the workplace and ensuring equality in job searches and employment.

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Section: Decomposition Of Wage Differentialssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Productivity difference or discrimination effect? Disability‐related wage gap in China

Liao,

Gao,

Zhu

et al. 2024

Asia Pac J Human Res

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“…Several studies covering the US, Western Europe, Brazil and Peru have found that these differences are explained in part, but not in full, by differences in physical health, leaving an unexplained portion which may be due to discrimination (DeLeire, 2001;Jones et al, 2006;Madden, 2004;Gannon and Munley, 2009;Halima and Rococo, 2014;Castro et al, 2017;Mougenot et al, 2017;Malo and Pag an, 2012). Further evidence for the possibility of discrimination comes from randomized experiments measuring call-backs from job applications which disclose a disability compared with those that do not, which receive 26% fewer callbacks for PwD (Ameri et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Disability, employment and wages: evidence from Indonesia

Caron

2020

IJM

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PurposeThe purpose of this paper is to quantify the labor market outcomes of people with disabilities (PwD) in Indonesia and compares them to people without disabilities. It first studies the labor force participation of PwD before examining the large and persistent wage gaps they face. It explores whether these wage gaps are explained by differences in productivity, a distinction which has important implications for policies addressing these gaps.Design/methodology/approachThe analysis is based on the Indonesian Family Life Survey Wave 5, which includes unique questions allowing for several definitions of disability. Multinomial logistic regression is used to study differences in type of employment for PwD. Wage gaps are estimated and corrected for selection using propensity score matching, supported by a Heckman selection model and Oaxaca–Blinder decomposition. Comparisons with other physically disadvantaged subgroups and the analysis of heterogeneity by job requirements and sector of work explore whether productivity gaps help explain wage gaps.FindingsPwD generally have lower unconditional labor force participation, but disparities largely disappear when controlling for characteristics. Moreover, patterns vary depending on whether the measure of disability used depends on prior medical diagnosis. PwD that do not require prior diagnosis tend to work in more vulnerable employment. When they are employed for wages, people with these types of disabilities face lower wages, up to 22% lower. Meanwhile, (surprisingly) those with medically diagnosed conditions face no difference or a wage premium. This paper finds compelling evidence that, where a wage penalty exists, a substantial part is unexplained by observable characteristics.Originality/valuePrevious literature on disability has been mostly based on studies of high-income economies. This paper extends the literature to Indonesia, which differs from high-income contexts due to lack of mental healthcare resources and assistive technologies, as well as weaker rule of law. It provides unique insights based on types of disability and the salient dimensions of disability in the workplace. It also provides evidence that productivity differences do not explain the wage gap.

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“…However, the early research on the health-income effect was criticized for the endogeneity caused by the interaction between health and income [9][10][11]. Thus, some researchers expand econometric techniques from Ordinary Least Square (OLS) to instrumental variable, linear fixed/random effect, matching methods and quantile regressions to solve the problems ( [12][13][14]].…”

Section: Introductionmentioning

confidence: 99%

The inequality of health-income effect in employed workers in China: a longitudinal study from China Family Panel Studies

Xie

Huang

Zang

2020

Int J Equity Health

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Background: The relationship between health and income is an essential part of human capital research. The majority of current analyses using classical regression models show that health has a significant impact on income after controlling for the endogeneity of health due to the measurement error and reverse causality. Currently, the Chinese government implements various policies including health related policies to fiercely fight for the domestic poverty issues, and thus only estimating the average effect of health on income could underestimate the impact for low income population and will make policy makers neglect or not pay enough attention to the significant role of health in poverty alleviation. To study the effect of health on income for workers at different income quantiles, we apply the quantile regression method to a panel data from a Chinese household survey. Furthermore, we test the heterogeneity of this health-income effect for different subgroups of workers characterized by sex, registered residence, and residential area. Lastly, we provide an explanation on the possible mechanism of the health-income effect. Methods: This study uses data from four waves of the China Family Panel Studies (CPFS)-a biennial longitudinal study spanning from 2012 to 2018. The final data used in the regression analysis includes a balanced sample of 19, 540 person-year observations aged between 18 to 70 years, with complete information of demographic and social economic status characteristics, job information, and health status of individuals. We use lagged self-reported health to control the potential endogeneity problem caused by reverse causality between health and income. Our identification on heterogenous treatment effects relies on panel quantile regressions, which generate more information than the commonly used mean regression method, and hopefully could reveal the effects of health on income for workers with income distributed at a wide range of quantiles. In addition, we compare the results derived from panel quantile regressions and mean regressions. Finally, we added interaction terms between health and other independent variables to recover the influence channel of health on income. Results: The regression estimates show that the effects of health on income are more pronounced for workers distributed on the lower ends of income spectrum, and the health-income effect decreases monotonically with the increase of income. The treatment effect is robust to alternative measures of health and seems to be more pronounced for females than males, for rural workers than their urban counterparts. Finally, we find that health not only directly affects worker's income but also has different effects on income for different occupation cohorts.

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Wage differences according to health status in France

Cited by 11 publications

References 16 publications

Productivity difference or discrimination effect? Disability‐related wage gap in China

Productivity difference or discrimination effect? Disability‐related wage gap in China

Disability, employment and wages: evidence from Indonesia

The inequality of health-income effect in employed workers in China: a longitudinal study from China Family Panel Studies

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