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Reconstructing 2010–2022 Poverty and Inequality Trends in Bangladesh : A Statistical Matching Approach

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  • Fernandez Romero,Jaime Estuardo
  • Olivieri,Sergio Daniel
  • Wambile,Ayago Esmubancha

Abstract

The 2022 Household Income and Expenditure Survey enhances fieldwork, data management, and information quality but poses comparability challenges with previous rounds. This study proposes a two-step process based on statistical matching to fill the information gap in previous survey rounds. This methodology uses the more comprehensive 2022 information to reconstruct comparable consumption measures over time. This allows for a consistent assessment of poverty and inequality measures, providing insights into the changes for policy makers, researchers, and stakeholders over the years. The results reveal that integrating this correction into previous survey rounds would have reduced poverty rates by around 10.6 percentage points between 2010 and 2016 and a further decrease of 7.8 percentage points between 2016 and 2022. Likewise, extreme poverty rates would have witnessed a decline of approximately 3 percentage points in the earlier period and a more substantial drop of 3.6 percentage points in the more recent one. These poverty reduction trends mirror improvements in other dimensions of well-being, like reductions in infant mortality and stunting and increases in access to electricity, sanitary toilets, and literacy rates.

Suggested Citation

  • Fernandez Romero,Jaime Estuardo & Olivieri,Sergio Daniel & Wambile,Ayago Esmubancha, 2024. "Reconstructing 2010–2022 Poverty and Inequality Trends in Bangladesh : A Statistical Matching Approach," Policy Research Working Paper Series 10749, The World Bank.
    • Handle: RePEc:wbk:wbrwps:10749
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    References listed on IDEAS

    as
    1. Astrid Mathiassen & Bjørn K. Getz Wold, 2021. "Predicting poverty trends by survey-to-survey imputation: the challenge of comparability," Oxford Economic Papers, Oxford University Press, vol. 73(3), pages 1153-1174.
    2. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    3. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
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