Using real-time data and machine-learning methods, we produce monthly aggregates on gross national income (GNI) for 147 Pakistani districts between 2012 and 2021. We use them to understand whether and how the COVID-19 pandemic affected the growth and subnational distribution of income in Pakistan. Three findings emerge from our analysis. First, districts experienced a sizable decline in income during the pandemic, as their monthly growth rate dropped on average by 0.133 percentage points. Second, a larger income drop took place in districts with a higher COVID-19 incidence, which correspond to urban areas characterized by a higher population density. Third, COVID-19 caused a decline in income inequality across districts, with richer districts experiencing more negative income growth during the pandemic.

Subnational income, growth and the COVID-19 pandemic

Dal Barco, Ilaria;Lenzi, Federico;Limodio, Nicola
2025

Abstract

Using real-time data and machine-learning methods, we produce monthly aggregates on gross national income (GNI) for 147 Pakistani districts between 2012 and 2021. We use them to understand whether and how the COVID-19 pandemic affected the growth and subnational distribution of income in Pakistan. Three findings emerge from our analysis. First, districts experienced a sizable decline in income during the pandemic, as their monthly growth rate dropped on average by 0.133 percentage points. Second, a larger income drop took place in districts with a higher COVID-19 incidence, which correspond to urban areas characterized by a higher population density. Third, COVID-19 caused a decline in income inequality across districts, with richer districts experiencing more negative income growth during the pandemic.
2025
2025
Choudhary, Ali M.; Dal Barco, Ilaria; Haqqani, Ijlal A.; Lenzi, Federico; Limodio, Nicola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4074336
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