The COVID‐19 emergency has had a dramatic impact on market incomes and income‐support policies. The lack of timely available data constrains the estimation of the scale and direction of recent changes in the income distribution, which in turn constrains policymakers seeking to monitor such developments. We overcome the lack of data by proposing a dynamic calibrated microsimulation approach to generate counterfactual income distributions as a function of more timely external data than are available in dated income surveys. We combine nowcasting methods using publicly available data and a household income generation model to perform the first calibrated simulation based upon actual data, aiming to assess the distributional implications of the COVID‐19 crisis in Ireland. Overall, we find that the crisis had an equalizing real‐time effect for both gross and disposable incomes, notwithstanding the significant hardship experienced by many households.

This paper undertakes a near real-time analysis of the income distribution effects of the Covid-19 crisis in Australia to understand the ongoing changes in the income distribution as well as the impact of policy responses. By semi-parametrically combining incomplete observed data from three different sources–the monthly Longitudinal Labour Force Survey, the Survey of Income and Housing and administrative payroll data–we estimate the impact of Covid-19 on the Australian income distribution and decompose its impact into the income shock effect and the policy effect between February and June 2020, covering the immediate periods before and after the initial Covid-19 outbreak. Our results suggest that, despite growth in unemployment, the Gini coefficient of equivalised household disposable income dropped by more than 0.02 points between February and June 2020. This reduction is due to the additional wage subsidies and welfare supports offered as part of the policy response, offsetting the increase in income inequality from the income shock effect. The results shows the effectiveness of temporary policy measures both in maintaining living standards and avoiding increases in income inequality. However, the heavy reliance on the support measures shown in the modelling raises the possibility that the changes in the income distribution may be reversed, or even that inequality and living standards could substantially worsen once the measures are withdrawn.

We evaluate the COVID-19 resilience of a Continental welfare regime by nowcasting the implications of the shock and its associated policy responses on the distribution of household incomes over the whole of 2020. Our approach relies on a dynamic microsimulation modelling that combines a household income generation model estimated on the latest EU-SILC wave with novel nowcasting techniques to calibrate the simulations using external macro controls which reflect the macroeconomic climate during the crisis. We focus on Luxembourg, a country that introduced minor tweaks to the existing tax-benefit system, which has a strong social insurance focus that gave certainty during the crisis. We find the system was well-equipped ahead of the crisis to cushion household incomes against job losses. The income-support policy changes were effective in cushioning household incomes and mitigating an increase in income inequality, allowing average household disposable income and inequality levels to bounce back to pre-crisis levels in the last quarter of 2020. The share of labour incomes dropped, but was compensated by an increase in benefits, reflecting the cushioning effect of the transfer system. Overall market incomes dropped and became more unequal. Their disequalizing evolution was matched by an increase in redistribution, driven by an increase in the generosity of benefits and larger access to benefits. The nowcasting model is a “near” real-time analysis and decision support tool to monitor the recovery, scalable to other countries with high applicability for policymakers.

This paper presents a framework for studying international differences in the distribution of household income. Integrating micro-econometric and micro-simulation approaches in a decomposition analysis, it quantifies the role of tax-benefit systems, employment and occupational structures, labour and financial market returns, and demographic composition in accounting for differences in income inequality across countries. Building upon EUROMOD (the European tax-benefit calculator) and its harmonised datasets, the model is portable and can be implemented for cross-country comparisons between any participating country. An application to the UK and Ireland—two countries that have much in common while displaying different levels of inequality—shows that differences in tax-benefit rules between the two countries account for over one third of the observed difference in disposable household income inequality. Demographic differences play negligible roles. The Irish tax-benefit system is more redistributive than UK’s due to a higher tax progressivity and higher average transfer rates. These are largely attributable to policy parameter differences, but also to differences in pre-tax, pre-transfer income distributions.

We model the household disposable income distribution in Lithuania and explore the drivers of the increase in income inequality between 2007 and 2015. We quantify the contributions of four factors to changes in the disposable income distribution: (i) demographics; (ii) labor market structure; (iii) returns and prices; and (iv) tax–benefit system. Results show that the effects of the factors were substantial and reflected heterogeneous developments over two subperiods: changes in the tax and benefit system cushioned a rapid rise in market income inequality because of the global financial crisis during 2007–2011, but failed to do so during the subsequent years of economic expansion, when rising returns in the labor and capital markets significantly increased disposable income inequality. We also find that declining marriage rates contributed to the increase in income inequality in Lithuania.

While providing equal opportunities to all members of society independent of an individual’s socio-economic background is a major objective of German policy makers, educational opportunities of children with a non-academic family background are still unequally obstructed. When analysing the labour market implications of this disadvantage, social capital as an additional source of inequality often lacks attention. Drawing on the instrumental value of rather loose contacts (i.e. weak ties) on the labour market as revealed by Granovetter (Getting a job. A study of contacts and careers, The University of Chicago Press, Cambridge, 1974), this paper goes beyond the human capital approach and includes a measure of instrumental social capital in the form of weak-tie career support in the earnings function. Applying an Oaxaca-Blinder decomposition and quantile regressions, we find a significant average wage gap between those with and without an academic family background. A large part can be explained by deficits that those from less educated families incur with respect to human and instrumental social capital: Lower educational attainment accounts for more than half of the wage gap between the two groups while fewer career support explains around five percent of the differential. Additionally, a non-academic family background is associated with a significant deficit in returns to their instrumental social capital along the wage distribution. The findings therefore suggest that inequalities of opportunity on the German labour market occur beyond the education system, as not only the quantity but also the quality of career supporting networks of those from a non-academic family are inferior.