Demographic change and the European income distribution

Dolls, Mathias; Doorley, Karina; Paulus, Alari; Schneider, Hilmar; Sommer, Eric

doi:10.1007/s10888-019-09411-z

Cited by 35 publications

(25 citation statements)

References 33 publications

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“…The absence of any contribution requirement reduces income inequality among retirees, contributing to the compression of the income distribution among the lower income population. For the high‐income population, which mostly consists of working individuals, demographic change pushes income inequality upwards slightly in the top quartile over the past decade, consistent with findings in some of the earlier literature, such as Dolls et al (2019).…”

Section: Resultssupporting

confidence: 89%

Policy, Demography, and Market Income Volatility: What Shaped Income Distribution and Inequality in Australia Between 2002 and 2016?

Sologon

2020

Review of Income and Wealth

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Isolating the impact of policy, demographic shifts, and market volatility on changes in income inequality is of great interest to policymakers. However, such estimation can be difficult due to the complex interactions and evolutions in the social and economic environment. Through an extended decomposition framework, this paper estimates the effect of four main components (policy, demography, market income and other factors) on the year‐over‐year changes in income inequality in Australia between 2002 and 2016. This was a period marked by substantial policy, population, and economic shifts due to factors such as the mining boom, the global financial crisis and increasing immigration. The framework also incorporates a flexible non‐parametric market income model which captures demand‐side shock better than a standard parametric model. Our results suggest that market income was the primary driver of income inequality for all segments of the income distribution in Australia over the past 15 years. Policy factors, moreover, have had the largest net impact on reducing inequality overall, especially for lower income earners.

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Section: Resultssupporting

confidence: 89%

Policy, Demography, and Market Income Volatility: What Shaped Income Distribution and Inequality in Australia Between 2002 and 2016?

Sologon

2020

Review of Income and Wealth

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“…In Hungary, some of the trends are estimated to have a somewhat more sizable though still modest impact (Figure 4). The impact was typically larger on market than on disposable income inequality, which is consistent with previous evidence, highlighting the strong inequality mitigating effect of the tax-benefit systems (Dolls, et al, 2019). Additional decomposition analysis confirms that the inequality-increasing impact of some socio-demographic changes was stronger in certain countries including Hungary, while limited on average across the OECD (OECD, in press).…”

Section: The Overall Impact Of Identified Trends On Income Inequalitysupporting

confidence: 87%

“…This is in line with trends discussed above such as convergence between the relative incomes of age groups and declining within-group inequality of youth. In theory, a larger share of retired people in the population can contribute to a wider between-group inequality as they tend to have lower incomes than the working age population (Dolls, et al, 2018). However, their relative incomes increased, mitigating this impact.…”

Section: Inequality Impact Of Socio-demographic Trends Is Comparatively Higher In Hungarymentioning

confidence: 99%

The impact of demographic and family structure changes on income distribution in Hungary and OECD countries

Förster¹,

Vindics²

2021

DEE

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This paper analyses the impact of socio-demographic trends on income inequality over the past two to three decades. The main socio-demographic trends in Hungary were largely in line with OECD-wide changes. Family structures are becoming increasingly complex and there is a growing disconnect between nuclear families and households. There has been a general retreat from marriage and a growth in both cohabitation and multigenerational households, as well as in the share of single person households. Births outside of marriage increased as well as the share of children living in other than two-parent family structures, and the number of children per household decreased. These changes in family structure fed into the broader cross-sectional development of ageing populations. However, most of these demographic changes had only a modest (upward) impact on trends in income inequality. In Hungary, three of the examined trends had a more significant impact than in other OECD countries: assortative mating; decline in the number of children; and changes in household types taken together. The inequality impact was typically larger on market than on disposable incomes, highlighting the strong inequality mitigating effect of the tax-benefit systems.1 This article is based on analyses from the forthcoming OECD-EC report on the impact of shifting demographic and family structures on income inequality and its policy implications (OECD, in press). A summary of findings has been published in Förster and Vindics, 2020. The authors are grateful to István György Tóth, Attila Melegh, Lívia Murinkó and two anonymous referees for their constructive remarks and valuable suggestions; they have no responsibility for any remaining errors. The views expressed are not necessarily those of the OECD or its member countries.

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“…It is also expected the existence of the negative influence of population aging on the countries' economic growth in the long-term, though related to various time horizons. Dolls et al [17] investigate the expected influence of population aging and upskilling on the income distribution of the EU-27 countries by 2030. The use of reweighting and microsimulation techniques allow the researchers to determine that, while population aging will likely lead to income inequality growth, the estimated impact of increasing educational attainment will be more ambiguous.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Demographic Structure on Economic Development of Ukrainian Coastal Regions

et al. 2021

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The main aim of our paper is to study peculiarities of two periods, i.e., the pre-conflict period (2004–2013) and conflict period (2014–2018), in the context of the impact of the demographic structure of the population on the economic growth and development of coastal regions of Ukraine. In the first step of the analysis, we investigate the relationship between the demographic shifts and selected economic indicators, using the Pearson’s correlation coefficient. In the next step of the analysis, we focus on the quantification of the impact of demographic indicators on the economic variables, based on the panel model with fixed effects. The received results confirm that the influence of the demographic stricture on the economic state of coastal regions changed significantly in the conflict period in comparison with the pre-conflict period, especially concerning income, unemployment, and the openness of the economy. Additionally, our findings show that while economic differences existed between the Azov Sea regions and the Black Sea regions in the pre-conflict period, they disappeared due to the economic deterioration of the Azov Sea regions during the conflict period. It is concluded that war affects adversely the population’s demographic structure, which inhibits the growth and economic development of Ukrainian coastal regions.

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Demographic change and the European income distribution

Cited by 35 publications

References 33 publications

Policy, Demography, and Market Income Volatility: What Shaped Income Distribution and Inequality in Australia Between 2002 and 2016?

Policy, Demography, and Market Income Volatility: What Shaped Income Distribution and Inequality in Australia Between 2002 and 2016?

The impact of demographic and family structure changes on income distribution in Hungary and OECD countries

Impact of Demographic Structure on Economic Development of Ukrainian Coastal Regions

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