2026-04-17T18:41:42Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/685652025-12-24T02:05:35Zcom_2072_6col_2072_452953

00925njm 22002777a 4500 dc Aspachs, Oriol author Durante, Ruben, 1978- author Graziano, Alberto author Mestres, Josep author Garcia Montalvo, José author Reynal-Querol, Marta author 2024-11-14T10:09:38Z 2024-11-14T10:09:38Z 2020-09-01 2024-11-14T10:07:15Z 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. inequality covid-19 administrative data high frequency Statistics, Econometrics and Quantitative Methods Real-Time inequality and the welfare state in motion: Evidence from COVID-19 in Spain