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Real-Time inequality and the welfare state in motion: Evidence from COVID-19 in Spain

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Abstract
Most official economic statistics have a relatively low frequency. The measures of inequality, in particular, are not only produced with low frequency but also with significant lags. This poses an important challenge for policymakers in their objective to mitigate the effects of a rapidly moving epidemic as the COVID-19. We propose a methodology for tracking the evolution of income inequality in the aftermath of the COVID-19 pandemic using high-frequency, high-quality microdata from bank-records. Using this approach we study the evolution of inequality since the beginning of the COVID-19 pandemic, and its effect on different groups of the population. First, we show that the payroll data managed by banks are an extremely useful source of information to detect, timely and accurately, changes in the distribution of wages. Our data replicate very closely the distribution of wages from the official wage surveys. Second, we show that, in absence of public benefits schemes, inequality would have increased dramatically. The impact of the crisis on inequality is explained mostly by its effect on low-wage workers. Pre-benefits wage inequality has increased significantly among foreign-born individuals, and regions that have a heavy economic dependence on touristic activities. Finally, we show that the public benefits activated soon after the beginning of the pandemic have substantially mitigated the impact of the COVID-19 crisis on inequality.

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  • Oriol Aspachs & Ruben Durante & Alberto Graziano & Josep Mestres & José Garcia Montalvo & Marta Reynal-Querol, 2020. "Real-Time inequality and the welfare state in motion: Evidence from COVID-19 in Spain," Economics Working Papers 1741, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:1741
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    References listed on IDEAS

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    1. Scott R. Baker & Robert A Farrokhnia & Steffen Meyer & Michaela Pagel & Constantine Yannelis, 2023. "Income, Liquidity, and the Consumption Response to the 2020 Economic Stimulus Payments," Review of Finance, European Finance Association, vol. 27(6), pages 2271-2304.
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    Cited by:

    1. Ainaa, Carmen & Brunetti, Irene & Mussida, Chiara & Scicchitano, Sergio, 2021. "Who lost the most? Distributive effects of COVID-19 pandemic," GLO Discussion Paper Series 829, Global Labor Organization (GLO).
    2. Mr. Andrew Berg & Lahcen Bounader & Nikolay Gueorguiev & Hiroaki Miyamoto & Mr. Kenji Moriyama & Ryota Nakatani & Luis-Felipe Zanna, 2021. "For the Benefit of All: Fiscal Policies and Equity-Efficiency Trade-offs in the Age of Automation," IMF Working Papers 2021/187, International Monetary Fund.
    3. Davide Furceri & Prakash Loungani & Jonathan D. Ostry & Pietro Pizzuto, 2022. "Will COVID-19 Have Long-Lasting Effects on Inequality? Evidence from Past Pandemics," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 811-839, December.
    4. Monica Martinez-Bravo & Carlos Sanz, 2021. "Inequality and psychological well-being in times of COVID-19: evidence from Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(4), pages 489-548, December.
    5. Davide Furceri & Prakash Loungani & Jonathan D Ostry & Pietro Pizzuto, 2021. "The rise in inequality after pandemics: can fiscal support play a mitigating role? [Epidemics, inequality, and poverty in preindustrial and early industrial time]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 445-457.
    6. Stefanie Stantcheva, 2022. "Inequalities in the times of a pandemic," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 37(109), pages 5-41.
    7. Juan Laborda & Pilar Rivera-Torres & Vicente Salas-Fumas & Cristina Suárez, 2021. "Is there life beyond the Spanish government’s aid to furloughed employees by COVID-19?," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-21, June.
    8. Schettino, Francesco & Scicchitano, Sergio & Suppa, Domenico, 2024. "COVID 19 and Wage Polarization: A task based approach," GLO Discussion Paper Series 1398, Global Labor Organization (GLO).
    9. José Garcia Montalvo & Marta Reynal-Querol, 2020. "Distributional effects of COVID-19 on spending: A first look at the evidence from Spain," Economics Working Papers 1740, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Kosteas, Vasilios D. & Renna, Francesco & Scicchitano, Sergio, 2022. "Covid-19 and Working from Home: toward a "new normal"?," GLO Discussion Paper Series 1013, Global Labor Organization (GLO).
    11. Stefan Pollinger, 2023. "Optimal Contact Tracing and Social Distancing Policies to Suppress A New Infectious Disease," The Economic Journal, Royal Economic Society, vol. 133(654), pages 2483-2503.
    12. Oriol Aspachs & Ruben Durante & Alberto Graziano & Josep Mestres & Marta Reynal-Querol & Jose G Montalvo, 2021. "Tracking the impact of COVID-19 on economic inequality at high frequency," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-14, March.
    13. Gary Cornwall & Marina Gindelsky, 2024. "Nowcasting Distributional National Accounts for the United States: A Machine Learning Approach," BEA Papers 0130, Bureau of Economic Analysis.
    14. Francesca Carta & Marta De Philippis, 2021. "The impact of the COVID-19 shock on labour income inequality: evidence from Italy," Questioni di Economia e Finanza (Occasional Papers) 606, Bank of Italy, Economic Research and International Relations Area.
    15. Carmen Aina & Irene Brunetti & Chiara Mussida & Sergio Scicchitano, 2023. "Distributional effects of COVID-19," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(1), pages 221-256, March.

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    More about this item

    Keywords

    inequality; COVID-19; administrative data; high frequency;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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