Skip to main content

The Impact of COVID-19 on Household Welfare in the Comoros: The Experience of a Small Island Developing State

  • Chapter
  • First Online:
The Coronavirus Pandemic and Inequality

Abstract

This chapter investigates the impact of COVID-19 on the Comoros’s household welfare, poverty, and labor market outcomes. The lockdown policy coincided with data collection for the 2020 Harmonized Survey on Living Conditions of Households, lending itself to a quasi-natural experiment in which households that were interviewed before the lockdown fall into the control group, while those that were interviewed after the lockdown fall into the treated group. The chapter uses matching techniques and finds a reduction in household expenditure, increased poverty, and lower likelihood of employment. Impacts are larger at the top of the distribution suggesting COVID-19 may have reduced inequality, although the poor were also negatively affected. Additionally, the ability of households to use assets as a coping mechanism was limited. In a context of limited safety nets and government interventions, stringent lockdown policies appear to increase the vulnerability of the existing poor and push others into poverty.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Alon, T., Doepke, M., Olmstead-Rumsey, J. and Tertilt, M., 2020. The Impact of COVID-19 on Gender Equality (No. w26947). National Bureau of economic research.

    Google Scholar 

  • Andersson, C., Mekonnen, A. and Stage, J., 2011. Impacts of the Productive Safety Net Program in Ethiopia on Livestock and Tree Holdings of Rural Households. Journal of Development Economics, 94(1), pp. 119‒126.

    Google Scholar 

  • Arndt, C. and Lewis, J.D., 2001. The HIV/AIDS pandemic in South Africa: Sectoral Impacts And Unemployment. Journal of International Development: The Journal of the Development Studies Association, 13(4), pp. 427‒449.

    Google Scholar 

  • Atkeson, A., 2020. On Using SIR Models to Model Disease Scenarios for COVID-19. Quarterly Review, 41(01), pp. 1‒35.

    Google Scholar 

  • Bickel, P.J., Klaassen, C.A., Bickel, P.J., Ritov, Y.A., Klaassen, J., Wellner, J.A. and Ritov, Y.A., 1993. Efficient and Adaptive Estimation for Semiparametric Models (Vol. 4). Baltimore: Johns Hopkins University Press.

    Google Scholar 

  • Brewer, M. and Gardiner, L., 2020. The Initial Impact of COVID-19 and Policy Responses On Household Incomes. Oxford Review of Economic Policy, 36, S187‒S199.

    Google Scholar 

  • Ceballos,F., Kannan, S. and Kramer, B., 2020. Impacts of a National Lockdown on Smallholder Farmers’ Income and Food Security: Empirical Evidence from Two States in India. World Development, 136, p. 105069.

    Google Scholar 

  • Dercon, S., 2002. Income Risk, Coping Strategies, and Safety Nets. The World Bank Research Observer, 17(2), pp. 141‒166.

    Google Scholar 

  • Dixon, S., McDonald, S. and Roberts, J., 2002. The Impact of HIV and AIDS on Africa’s Economic Development. BMJ, 324(7331), pp. 232‒234.

    Google Scholar 

  • Dunford D., Dale B., Stylianou N., Lowther E., Ahmed M., De la Torres Arenas I., 2020. Coronavirus: The World in Lockdown in Maps and Charts. Retrieved from https://www.bbc.com/news/world-52103747.

  • Egger,D., Miguel, E., Warren, S.S., Shenoy, A., Collins, E., Karlan, D., Parkerson, D., Mobarak, A.M., Fink, G., Udry, C. and Walker, M., 2021. Falling Living Standards During the COVID-19 Crisis: Quantitative Evidence from Nine Developing Countries. Science Advances, 7(6), p. 0997.

    Google Scholar 

  • Firpo, S., (2007). Efficient Semiparametric Estimation of Quantile Treatment Effects. Econometrica, 75(1), pp. 259‒276.

    Google Scholar 

  • Gupta, A., Zhu, H., Doan, M.K., Michuda, A. and Majumder, B., 2021. Economic Impacts of the COVID-19 Lockdown in a Remittance‐Dependent Region. American Journal of Agricultural Economics, 103(2), pp. 466‒485.

    Google Scholar 

  • Hahn, J., 1998. On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects. Econometrica, pp.315–331.

    Google Scholar 

  • Heckman, J.J., Ichimura, H. and Todd, P.E., 1997. Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme. The Review of Economic Studies, 64(4), pp. 605‒654.

    Google Scholar 

  • Heckman, J.J., Ichimura, H. and Todd, P., 1998. Matching as an econometric evaluation estimator. The Review of Economic Studies, 65(2), pp.261–294.

    Google Scholar 

  • Janssen,M., Chang, B.P., Hristov, H., Pravst, I., Profeta, A. and Millard, J., 2021. Changes In Food Consumption During the COVID-19 Pandemic: Analysis of Consumer Survey Data From The First Lockdown Period in Denmark, Germany, and Slovenia. Frontiers in nutrition, 8, p. 60.

    Google Scholar 

  • Kikuchi, S., Kitao, S. and Mikoshiba, M., 2020. Heterogeneous Vulnerability to the Covid-19 Crisis and Implications for Inequality in Japan. Discussion Papers, 20039.

    Google Scholar 

  • Lone, S.A. and Ahmad, A., 2020. COVID-19 Pandemic–An African Perspective. Emerging microbes & Infections, 9(1), pp. 1300‒1308.

    Google Scholar 

  • Newey, W.K., 1990. Efficient Instrumental Variables Estimation of Nonlinear Models. Econometrica: Journal of the Econometric Society, pp. 809–837.

    Google Scholar 

  • Piyapromdee, S. and Spittal, P., 2020. The Income and Consumption Effects of Covid‐19 and the Role of Public Policy. Fiscal Studies, 41(4), pp. 805‒827.

    Google Scholar 

  • Porteous, O., 2020. Economics Research on Africa is Unevenly Distributed Between Countries. Africa at LSE.

    Google Scholar 

  • Rönkkö, R., Rutherford, S. and Sen, K., 2021. The Impact of the COVID-19 Pandemic on the Poor: Insights from the Hrishipara Diaries (No. wp-2021–46). World Institute for Development Economic Research (UNU-WIDER).

    Google Scholar 

  • Rosenbaum,P.R. and Rubin, D.B., 1985. Constructing a Control Group Using Multivariate Matched Sampling Methods that Incorporate the Propensity Score. The American Statistician, 39(1), pp. 33‒38.

    Google Scholar 

  • Robins, J.M., 1997. Causal Inference from Complex Longitudinal Data. In Berkane M, ed., Latent Variable Modeling with Applications to Causality. New York, Springer-Verlag, pp. 69–117.

    Google Scholar 

  • Rubin, D.B., 2001. Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation. Health Services and Outcomes Research Methodology, 2(3), pp. 169‒188.

    Google Scholar 

  • Sathyamala, C., 2020. COVID-19: A Biopolitical Odyssey. ISS Working Paper No. 667. Erasmus University ISS: The Hague.

    Google Scholar 

  • Schotte, S., Danquah, M., Osei, R.D. and Sen, K., 2021. The Labour Market Impact of COVID-19 Lockdowns: Evidence from Ghana (No. wp-2021–27). World Institute for Development Economic Research (UNU-WIDER).

    Google Scholar 

  • Smith,J.A. and Todd, P.E., 2005. Does Matching Overcome LaLonde’s Critique of Nonexperimental Estimators? Journal of Econometrics, 125(1-2), pp. 305‒353.

    Google Scholar 

  • Sumner, Andy, Chris Hoy, and Eduardo Ortiz-Juarez., 2020. Estimates of the Impact of COVID-19 on Global Poverty. UNU-WIDER, April, 800–9. https://www.wider.unu.edu/sites/default/files/Publications/Working-paper/PDF/wp2020-43.pdf.

  • Swinnen, J. and Vos, R., 2021. COVID‐19 and Impacts on Global Food Systems and Household Welfare: Introduction to a Special Issue. Agricultural Economics, 52(3), pp. 365- 374.

    Google Scholar 

  • Townsend, R.M., 1994. Risk and Insurance in Village India. Econometrica: Journal of the Econometric Society, pp. 539–591.

    Google Scholar 

  • United Nations, 2020. Sustainable Development Goals, Comoros, 2020. Comoros voluntary national review 2020.

    Google Scholar 

  • van Bergeijk, P.A., 2021. The Political Economy of the Next Pandemic. SSRN 3831710.

    Google Scholar 

  • Williams, R., 2012. Using the Margins Command to Estimate and Interpret Adjusted Predictions and Marginal Effects. The Stata Journal, 12(2), pp. 308‒331.

    Google Scholar 

  • WorldBank, 2020. The World Bank in Comoros Overview. Washington, D.C.: World Bank Group.

    Google Scholar 

  • World Population Review, 2021. Poorest Countries in the World 2021. World Population Review. https://worldpopulationreview.com/country-rankings/poorest-countries-in-africa.

Download references

Acknowledgements

The authors would like to thank Pierella Paci, Nobuo Yoshida, Alvin Etang Ndip, and Djibril Ndoye at The World Bank for helpful comments on earlier drafts. We would also like to thank the National Institute of Statistics, Economic and Demographic Studies of Comoros (INSEED), for sharing the data.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Olive Umuhire Nsababera .

Editor information

Editors and Affiliations

Appendix

Appendix

Fig. 3
A line graph compares the trends of post and pre covid treatments and controls. It has a bell-shaped curve and reaches the peak at (9, 6) and (8, 6), respectively. Values are estimated.

Post-match distribution of propensity scores across treatment and control

See Tables 11, 12, 13, 14, 15, 16, 17, and 18.

Table 11 Sample distribution of individuals interviewed by region and lockdown measure
Table 12 Summary statistics of employment distribution across the four main sectors*
Table 13 Logit PSM regression for treatment assignment
Table 14 Covariate Balancing Test using post-COVID-19 treatment measure
Table 15 Covariate Balancing Test using post-COVID-19 treatment measure-COVID-19 anticipation
Table 16 Rubin’s balancing property diagnostics
Table 17 Average Treatment Effect (ATT) of COVID-19 on selected household asset types
Table 18 Raw difference in the log of per capita household expenditure between treatment and control by quantiles

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Nsababera, O.U., Mendiratta, V., Sam, H. (2023). The Impact of COVID-19 on Household Welfare in the Comoros: The Experience of a Small Island Developing State. In: Johnson-Lans, S. (eds) The Coronavirus Pandemic and Inequality. Global Perspectives on Wealth and Distribution. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-22219-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-22219-1_7

  • Published:

  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-031-22218-4

  • Online ISBN: 978-3-031-22219-1

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)

Publish with us

Policies and ethics