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|
|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 a high frequency using anonymized data from bank records for over three million account holders in Spain. Using this approach, we analyse how the wage distribution evolved between February and May 2020 (compared to the same months of 2019). We first show that the wage distribution in our data matches very closely that from official labour 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 foreign-born individuals and in regions more dependent on tourism. Finally, we find that public transfers and unemployment insurance schemes were very effective at providing a safety net to the most affected segments of the population and at offsetting most of the increase in inequality.