Abstract
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.
| Original language | English (Ireland) |
|---|---|
| Pages (from-to) | 321-336 |
| Number of pages | 16 |
| Journal | Fiscal Studies |
| Volume | 41 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1 Jul 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 1 No Poverty
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SDG 10 Reduced Inequalities
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SDG 17 Partnerships for the Goals
Keywords
- COVID-19
- distributional impact
- fiscal policy
- income distribution
- income generation model
- inequality
- microsimulation
- nowcasting
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