DP15118 Real-Time Inequality and the Welfare State in Motion: Evidence from COVID-19 in Spain

Author(s): Oriol Aspachs, Ruben Durante, Alberto Graziano, Josep Mestres, Jose G Montalvo, Marta Reynal-Querol
Publication Date: July 2020
Date Revised: January 2022
Keyword(s): Administrative data, COVID-19, High Frequency Data, Inequality
JEL(s): C81, D63, E24, J31
Programme Areas: Public Economics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=15118

Official statistics on economic inequality are only available at low frequency and with considerable delay. This makes it challenging to assess the impact on inequality of fast-unfolding crises like the COVID-19 pandemic, and to rapidly evaluate and tailor policy responses. We propose a new methodology to track income inequality at high frequency using anonymized data from bank records for over three million account holders in Spain. Using this approach, we analyze how inequality evolved between February and November 2020 (compared to the same months of 2019). We first show that the wage distribution in our data matches very closely that from official labor surveys. We then document that, in the absence of government intervention, inequality would have increased dramatically, mainly due to job losses and wage cuts experienced by low-wage workers. The increase in pre-transfer inequality was especially pronounced among the young and the foreign-born, and in regions more dependent on services. Public transfers and unemployment insurance schemes were effective at providing a safety net to the most affected segments of the population and at offsetting most of the increase in inequality. Increased inequality is primarily driven by differential changes in employment rate. Indeed, using individual-level regressions, we find that, over the course of the pandemic, the probability of being employed decreased drastically for workers in the lower part of the pre-COVID wage distribution, young cohorts, and foreign-born.