The first aggregate assessment of the impact of COVID-19 is usually made on the basis of a comparison of averages. Our goal is to combine the comparison between the averages with inequality decomposition methods. In particular, we refer to three measures of inequality between subgroups that allow an effective assessment of the inequality factors. Our analysis compares 2019 and 2020 IT-SILC consumption micro data in order to assess the impact of COVID-19 with respect to main inequality factors such as age, gender and geography.
Federico Attili, Michele Costa (2022). Covid-19 impact assessment and inequality decomposition methods. Pearson.
Covid-19 impact assessment and inequality decomposition methods
Federico Attili;Michele Costa
2022
Abstract
The first aggregate assessment of the impact of COVID-19 is usually made on the basis of a comparison of averages. Our goal is to combine the comparison between the averages with inequality decomposition methods. In particular, we refer to three measures of inequality between subgroups that allow an effective assessment of the inequality factors. Our analysis compares 2019 and 2020 IT-SILC consumption micro data in order to assess the impact of COVID-19 with respect to main inequality factors such as age, gender and geography.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
