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Modelling the Distributional Impact of the COVID‐19 Crisis

Author

Listed:
  • Cathal O'Donoghue
  • Denisa M. Sologon
  • Iryna Kyzyma
  • John McHale

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.

Suggested Citation

  • Cathal O'Donoghue & Denisa M. Sologon & Iryna Kyzyma & John McHale, 2020. "Modelling the Distributional Impact of the COVID‐19 Crisis," Fiscal Studies, John Wiley & Sons, vol. 41(2), pages 321-336, June.
    • Handle: RePEc:wly:fistud:v:41:y:2020:i:2:p:321-336
    DOI: 10.1111/1475-5890.12231
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    More about this item

    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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