Dynamics of inequality and opportunities within European countries

Álvarez, Ana Suárez; Menéndez, Ángel Espiniella

doi:10.1111/boer.12266

Cited by 5 publications

(10 citation statements)

References 24 publications

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“…With respect to the other cross‐country studies using the EU‐SILC survey, notably Checchi et al (2010), the differences may lie in the methodological assumptions because our sample does not include part‐time workers nor the unemployed and those fulfilling domestic tasks and care responsibilities. In addition, the outcome variable in our study is individual labour income, whereas Marrero and Rodríguez (2012), Brzezinski (2015), Suárez Álvarez and López Menéndez (2021) and Palomino et al (2018) use household income. This clearly shows an important role of other non‐labour‐related sources of income, and other household members, in the extent of inequality of opportunity.…”

Section: Resultsmentioning

confidence: 99%

“…In addition, the ex‐ante approach gives us a greater chance of comparability of results as it is more widely applied in the literature. Consequently, we decided to follow the ex‐ante approach to the estimation of inequality of opportunity, similarly to previous studies using the EU‐SILC microdata (e.g., Perez‐Mayo, 2019; Suárez‐Álvarez & López‐Menéndez, 2021). To this end, we measure the level of inequality of opportunity using the following index (Ferreira & Gignoux, 2011):

θ_{a} goodbreak= E_{0} ((), \{μ_{i}^{k}\}) goodbreak= \frac{1}{N} \sum_{i = 1}^{N} italiclog \frac{μ}{μ_{i}^{k}},

where:

θ_{a}

– absolute index of inequality of opportunity,

E_{0}

– mean logarithmic deviation (inequality measure),

({}, μ_{i}^{k})

= (

μ_{1, \dots,}^{1} μ_{n, \dots,}^{1} μ_{i}^{K}, \dots, μ_{N}^{K} true)

– counterfactual (‘smoothed’) distribution of income with

N

individuals (

i

) and K types (

k

μ

– overall mean. …”

Section: Methodsmentioning

confidence: 99%

“…More recent ex‐ante method‐based results are provided by Suárez Álvarez and López Menéndez (2021). They use EU‐SILC data on equivalized disposable income of households in 26 European countries as an outcome variable.…”

Section: Overview Of Relevant Literaturementioning

confidence: 99%

See 2 more Smart Citations

Estimating labour‐income‐based inequality of opportunity for a selection of EU‐SILC countries: National and urban–rural perspectives

Mogiła

Melo

Gaspar

2022

Regional Science Policy & Practice

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This paper measures the extent of inequality of opportunity at the national level and by degree of urbanization. Using data from the European Union Statistics on Income and Living Conditions (EU-SILC), we implement regression models to measure the share of the variation in individuals' labour income that is due to uncontrollable circumstances, namely the relative importance of parental education, activity status of parents, occupation of father and household financial situation. Our results indicate that the level of inequality of opportunity at the country level ranges between 5% and 26% for the sample of countries studied. The analysis by degree of urbanization does not provide evidence of cities as social elevators compared with less urbanized regions.

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Section: Resultsmentioning

confidence: 99%

θ_{a} goodbreak= E_{0} ((), \{μ_{i}^{k}\}) goodbreak= \frac{1}{N} \sum_{i = 1}^{N} italiclog \frac{μ}{μ_{i}^{k}},

where:

θ_{a}

– absolute index of inequality of opportunity,

E_{0}

– mean logarithmic deviation (inequality measure),

({}, μ_{i}^{k})

= (

μ_{1, \dots,}^{1} μ_{n, \dots,}^{1} μ_{i}^{K}, \dots, μ_{N}^{K} true)

– counterfactual (‘smoothed’) distribution of income with

N

individuals (

i

) and K types (

k

μ

– overall mean. …”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Estimating labour‐income‐based inequality of opportunity for a selection of EU‐SILC countries: National and urban–rural perspectives

Mogiła

Melo

Gaspar

2022

Regional Science Policy & Practice

View full text Add to dashboard Cite

show abstract

“…On the one hand, access to broader and more up-to-date information would allow us to expand the existing evidence and increase the strength of the results. On the other hand, it would be of great interest to conduct an in-depth analysis of the causes of the existing vaccination inequality, distinguishing between institutional factors (mainly related to distribution) and individual attitudes (as hesitance or lack of information) by implementing, for example, the Inequality of Opportunity approach [ 21 , 22 ]. All these contributions would be very useful in bringing us closer to the common goal of reducing existing inequality as much as possible.…”

Section: Discussionmentioning

confidence: 99%

Is COVID-19 vaccine inequality undermining the recovery from the COVID-19 pandemic?

Álvarez¹,

López-Menéndez²

2022

J Glob Health

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Background The devastating health and economic impact of the COVID-19 pandemic led to a global response in the development of effective vaccines to fight the disease in an extraordinarily short time. Both the development and the production of these vaccines opened a path of hope, but the inequality in vaccine distribution raises great concerns about the possibility of effectively eradicating the virus. Methods It is particularly important to analyse the extent to which vaccines are equally distributed and investigate the possible effects of vaccine inequalities as well as its major drivers. For this purpose, this paper investigates the extent of equitable vaccine distribution using some well-known inequality measures and disentangles the main drivers of the share of vaccination. In addition, the paper analyses the relationship between the vaccination rate, the GDP growth, and the incidence of the coronavirus disease, with the aim of providing empirical evidence on existing relationships worldwide. Results Our findings show that the situation is more challenging in less developed countries, especially African countries, due to weak health systems and low rates of vaccination. Moreover, we find a positive relationship between the share of vaccinated individuals and GDP. Consequently, the poorest, least developed countries with a lower rate of vaccine uptake will experience lower GDP growth. Conclusions Vaccines and the vaccination process reveal the existing inequalities between countries and how they, in turn, impact the well-being of their citizens. People who live in less developed countries have a lower probability of being vaccinated, which translates into a greater probability of dying from COVID. Countries are seeing their economic future compromised by low vaccination levels, given the positive and significant relationship between the vaccination rate and GDP growth. In short, while some countries are trying to get back to some sort of normality, even with some pandemic protocols, the situation in less developed countries is more challenging due to weak health systems and low rates of vaccination. Consequently, the poorest, least developed countries with a lower rate of vaccine penetration will experience lower GDP growth, and the pandemic will have a greater effect on their economy due to low vaccination rates.

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“…At data collection, Norway was ranked 1st on the human development index compiled by the United Nations Development [23]. In addition, compared to other European countries, Norway have one of the lowest IOp for disposable income [24,25]. Hence, Norway offers a useful 'best-case' benchmark against which other countries can be compared.…”

Section: Introductionmentioning

confidence: 99%

Inequality of opportunity in a land of equal opportunities: The impact of parents’ health and wealth on their offspring’s quality of life in Norway

et al. 2022

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Background The literature on Inequality of opportunity (IOp) in health distinguishes between circumstances that lie outside of own control vs. efforts that – to varying extents – are within one’s control. From the perspective of IOp, this paper aims to explain variations in individuals’ health-related quality of life (HRQoL) by focusing on two separate sets of variables that clearly lie outside of own control: Parents’ health is measured by their experience of somatic diseases, psychological problems and any substance abuse, while parents’ wealth is indicated by childhood financial conditions (CFC). We further include own educational attainment which may represent a circumstance, or an effort, and examine associations of IOp for different health outcomes. HRQoL are measured by EQ-5D-5L utility scores, as well as the probability of reporting limitations on specific HRQoL-dimensions (mobility, self-care, usual-activities, pain & discomfort, and anxiety and depression). Method We use unique survey data (N = 20,150) from the egalitarian country of Norway to investigate if differences in circumstances produce unfair inequalities in health. We estimate cross-sectional regression models which include age and sex as covariates. We estimate two model specifications. The first represents a narrow IOp by estimating the contributions of parents’ health and wealth on HRQoL, while the second includes own education and thus represents a broader IOp, alternatively it provides a comparison of the relative contributions of an effort variable and the two sets of circumstance variables. Results We find strong associations between the circumstance variables and HRQoL. A more detailed examination showed particularly strong associations between parental psychological problems and respondents’ anxiety and depression. Our Shapley decomposition analysis suggests that parents’ health and wealth are each as important as own educational attainment for explaining inequalities in adult HRQoL. Conclusion We provide evidence for the presence of the lasting effect of early life circumstances on adult health that persists even in one of the most egalitarian countries in the world. This suggests that there may be an upper limit to how much a generous welfare state can contribute to equal opportunities.

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Dynamics of inequality and opportunities within European countries

Cited by 5 publications

References 24 publications

Estimating labour‐income‐based inequality of opportunity for a selection of EU‐SILC countries: National and urban–rural perspectives

Estimating labour‐income‐based inequality of opportunity for a selection of EU‐SILC countries: National and urban–rural perspectives

Is COVID-19 vaccine inequality undermining the recovery from the COVID-19 pandemic?

Inequality of opportunity in a land of equal opportunities: The impact of parents’ health and wealth on their offspring’s quality of life in Norway

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