This paper proposes 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 prices and market returns, and demographic composition in accounting for differences in income inequality across countries. Building upon EUROMOD (the European tax-benefit calculator) and its harmonized datasets, the model is portable and can be implemented for any cross-country comparisons within the EU. 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 roughly half 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.

Studies have shown that the previously growing inequality in China has stabilized and even declined since 2008 (Kanbur et al., 2021), nevertheless, the drivers of the latest trans-formation in income inequality remain to be unraveled. We address this research gap by examining the changes in the distribution of household disposable income and its drivers in China from 2010 to 2016. We apply the distributional decomposition method proposed by Bourguignon et al. (2008) and Sologon et al. (2021), and quantify the contribution of all factors into four general dimensions, (1) demographic composition, (2) labor market structure, (3) price and return, and (4) governmental transfers. This study considers not only the individual labor income as with existing literature, but also models other family incomes and social transfers to reflect the real economic conditions more accurately. The decomposition results show that all four factors contribute positively to the decline in income inequality during the period studied. The changes in urban labor market structure, specifically the general forms of employment, occupational and industrial structure, have been contributing as inequality augmenting factors.

The urgency of the two crises, especially the COVID-19 pandemic, revealed the inadequacy of traditional statistical datasets and models to provide a timely support to the decision-making process in times of volatility. Drawing upon advances in data analytics for public policy and the increasing availability of real-time data, we develop and evaluate a method for real-time policy evaluations of tax and social protection policies. Our method goes beyond the state-of-the-art by implementing an aligned or calibrated microsimulation approach to generate a counterfactual income distribution as a function of more timely external data than the underlying income survey. We evaluate the simulation performance between our approach and the transition matrix approach by undertaking a nowcast for a historical crisis, judging against an actual change and each other. Nowcasting emerges as a useful methodology for examining up-to-date statistics on labour force participation, income distribution, prices, and income inequality. We find significant differences between approaches when the calibration involves structural heterogenous changes. The model replicates the changes in income distribution over one year; over the longer term, the model is able to capture the trend, but the precision of the levels weakens the further we get from the estimation year.