IDEAS home Printed from https://ideas.repec.org/p/ese/cempwp/cempa4-20.html

Modelling the distributional impact of the Covid-19 crisis in Ireland

Author

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

Abstract

Given the rapid spread of the COVID-19 virus, the State has had to respond rapidly and quite severely to flatten the curve and slow the spread of the virus. This has had significant implications for many aspects of life with differential impacts across the population. The lack of timely available data constrains the estimation of the scale and direction of recent changes in the income distribution, which in turn constrain 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 is 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. We extend the standard definition of disposable income by adjusting for work-related expenditure, housing costs and capital losses. We find that market incomes decreased along the distribution of disposable income, but decreases in euro terms were more pronounced at the top than at the bottom. Despite this, inequality in market incomes as measured by the Gini coefficient increased over the crisis. Once we account for the decline in housing and work-related expenses, households situated among the bottom 70% of the distribution actually improved their financial situation on average, whereas losses are recorded for the top 30%.

Suggested Citation

  • O'Donoghue, Cathal & M. Sologon, Denisa & Kyzyma, Iryna & McHale, John, 2020. "Modelling the distributional impact of the Covid-19 crisis in Ireland," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA4/20, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
  • Handle: RePEc:ese:cempwp:cempa4-20
    as

    Download full text from publisher

    File URL: https://www.iser.essex.ac.uk/wp-content/uploads/files/working-papers/cempa/cempa4-20.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fran??ois Bourguignon & Francisco H. G. Ferreira & Phillippe G. Leite, 2002. "Beyond Oaxaca-Blinder: Accounting for Differences in Household Income Distributions Across Countries," William Davidson Institute Working Papers Series 478, William Davidson Institute at the University of Michigan.
    2. Cathal O'Donoghue & Jason Loughrey, 2014. "Nowcasting in Microsimulation Models: A Methodological Survey," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(4), pages 1-12.
    3. repec:bla:revinw:v:47:y:2001:i:2:p:139-63 is not listed on IDEAS
    4. Cathal O’Donoghue & Jason Loughrey & Karyn Morrissey, 2013. "Using the EU-SILC to model the impact of the economic crisis on inequality," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-26, December.
    5. Jekaterina Navicke & Olga Rastrigina & Holly Sutherland, 2014. "Nowcasting Indicators of Poverty Risk in the European Union: A Microsimulation Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(1), pages 101-119, October.
    6. SOLOGON Denisa & VAN KERM Philippe & LI Jinjing & O'DONOGHUE Cathal, 2018. "Accounting for Differences in Income Inequality across Countries: Ireland and the United Kingdom," LISER Working Paper Series 2018-01, Luxembourg Institute of Socio-Economic Research (LISER).
    7. Callan, Tim & Keane, Claire & Walsh, John R. & Lane, Marguerita, 2010. "From Data to Policy Analysis: Tax-Benefit Modelling using SILC 2008," Papers WP359, Economic and Social Research Institute (ESRI).
    8. Jinjing Li & Cathal O'Donoghue, 2014. "Evaluating Binary Alignment Methods in Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(1), pages 1-15.
    9. F. Bourguignon & M. Fournier & M. Gurgand, 2001. "Fast Development With a Stable Income Distribution: Taiwan, 1979–94," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(2), pages 139-163, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. O'Donoghue, Cathal & Sologon, Denisa M., 2023. "The Transformation of Public Policy Analysis in Times of Crisis – A Microsimulation-Nowcasting Method Using Big Data," IZA Discussion Papers 15937, IZA Network @ LISER.
    3. Cathal O’Donoghue & Denisa M Sologon & Iryna Kyzyma & John McHale, 2021. "A Microsimulation Analysis of the Distributional Impact over the Three Waves of the COVID-19 Crisis in Ireland," International Journal of Microsimulation, International Microsimulation Association, vol. 14(2), pages 81-105.
    4. Denisa M. Sologon & Cathal O’Donoghue & Iryna Kyzyma & Jinjing Li & Jules Linden & Raymond Wagener, 2022. "The COVID-19 resilience of a continental welfare regime - nowcasting the distributional impact of the crisis," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 777-809, December.
    5. Jinjing Li & Yogi Vidyattama & Hai Anh La & Riyana Miranti & Denisa M. Sologon, 2022. "Estimating the Impact of Covid-19 and Policy Responses on Australian Income Distribution Using Incomplete Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(1), pages 1-31, July.
    6. Michal Myck & Mateusz Najsztub, 2015. "Data and Model Cross-validation to Improve Accuracy of Microsimulation Results: Estimates for the Polish Household Budget Survey," International Journal of Microsimulation, International Microsimulation Association, vol. 8(1), pages 33-66.
    7. Maria Teresa Monteduro & Dalila Rosa & Chiara Subrizi, 2024. "How to Nowcast Uncertain Income Shocks in Microsimulation Models? Evidence from COVID-19 Effects on Italian Households," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 10(2), pages 871-900, July.
    8. Gary Cornwall & Marina Gindelsky, 2025. "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," AEA Papers and Proceedings, American Economic Association, vol. 115, pages 79-84, May.
    9. Herwig Immervoll & Cathal O’Donoghue & Jules Linden & Denisa Sologon, 2023. "Who pays for higher carbon prices?: Illustration for Lithuania and a research agenda," OECD Social, Employment and Migration Working Papers 283, OECD Publishing.
    10. Alari PaulusBy & Francesco Figari & Holly Sutherland, 2017. "The design of fiscal consolidation measures in the European Union: distributional effects and implications for macro-economic recovery," Oxford Economic Papers, Oxford University Press, vol. 69(3), pages 632-654.
    11. Mathias Dolls & Clemens Fuest & Dirk Neumann & Andreas Peichl, 2018. "An unemployment insurance scheme for the euro area? A comparison of different alternatives using microdata," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 25(1), pages 273-309, February.
    12. repec:ecr:col031:4965 is not listed on IDEAS
    13. Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
    14. Holly Sutherland & Francesco Figari, 2013. "EUROMOD: the European Union tax-benefit microsimulation model," International Journal of Microsimulation, International Microsimulation Association, vol. 1(6), pages 4-26.
    15. Evans Jadotte, 2006. "Income Distribution and Poverty in the Republic of Haiti," Working Papers PMMA 2006-13, PEP-PMMA.
    16. John Creedy & Norman Gemmell & Nicolas Hérault & Penny Mok, 2020. "A microsimulation analysis of marginal welfare-improving income tax reforms for New Zealand," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 27(2), pages 409-434, April.
    17. Callan, Tim & Doorley, Karina & Savage, Michael, 2018. "Inequality in EU Crisis Countries: How Effective Were Automatic Stabilisers?," IZA Discussion Papers 11439, IZA Network @ LISER.
    18. Johannes Geyer & Salmai Qari & Hermann Buslei & Peter Haan, 2021. "DySiMo Dokumentation: Version 1.0," Data Documentation 101, DIW Berlin, German Institute for Economic Research.
    19. -, 2002. "Meeting the millennium poverty reduction targets in Latin America and the Caribbean," Libros de la CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 2349 edited by Eclac.
    20. Jeong, Hyeok, 2008. "Assessment Of Relationship Between Growth And Inequality: Micro Evidence From Thailand," Macroeconomic Dynamics, Cambridge University Press, vol. 12(S2), pages 155-197, September.
    21. Malte Luebker, 2014. "Income Inequality, Redistribution, and Poverty: Contrasting Rational Choice and Behavioral Perspectives," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(1), pages 133-154, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ese:cempwp:cempa4-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jonathan Nears (email available below). General contact details of provider: https://edirc.repec.org/data/rcessuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.