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Subnational income, growth, and the COVID-19 pandemic

Author

Listed:
  • Choudhary, M. Ali
  • Dal Barco, Ilaria
  • Haqqani, Ijlal A.
  • Lenzi, Federico
  • Limodio, Nicola

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.

Suggested Citation

  • Choudhary, M. Ali & Dal Barco, Ilaria & Haqqani, Ijlal A. & Lenzi, Federico & Limodio, Nicola, 2025. "Subnational income, growth, and the COVID-19 pandemic," LSE Research Online Documents on Economics 128131, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:128131
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    References listed on IDEAS

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    1. Nicola Limodio, 2021. "Bureaucrat Allocation in the Public Sector: Evidence from the World Bank," The Economic Journal, Royal Economic Society, vol. 131(639), pages 3012-3040.
    2. M Ali Choudhary & Nicola Limodio, 2022. "Liquidity Risk and Long-Term Finance: Evidence from a Natural Experiment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(3), pages 1278-1313.
    3. Joseph Vavra, 2021. "Tracking the Pandemic in Real Time: Administrative Micro Data in Business Cycles Enters the Spotlight," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 47-66, Summer.
    4. Moeen, Muhammad Saad & Haider, Zeeshan & Shikoh, Sania Haider & Rizwan, Noormah & Ejaz, Amna & Davies, Stephen & Rana, Abdul Wajid, 2021. "Estimating the economic impacts of the first wave of COVID-19 in Pakistan using a SAM Multiplier Model," IFPRI discussion papers 2001, International Food Policy Research Institute (IFPRI).
    5. Beyer, Robert C.M. & Franco-Bedoya, Sebastian & Galdo, Virgilio, 2021. "Examining the economic impact of COVID-19 in India through daily electricity consumption and nighttime light intensity," World Development, Elsevier, vol. 140(C).
    6. Meha Jain, 2020. "The Benefits and Pitfalls of Using Satellite Data for Causal Inference," Review of Environmental Economics and Policy, University of Chicago Press, vol. 14(1), pages 157-169.
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    Keywords

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    JEL classification:

    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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