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Does it matter which poverty measure we use to identify those left behind? Investigating poverty mismatch and overlap for Botswana

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  • Khaufelo Raymond Lekobane

    (University of Sussex
    Botswana Institute for Development Policy Analysis (BIDPA))

Abstract

This study offers the first attempt in Botswana and adds to the limited literature on poverty mismatch and overlaps in Sub-Saharan Africa. Using the 2015/16 Botswana multi-topic household survey data, the study compares the country’s current official monetary poverty measure with an individual-level multidimensional poverty measure. The results show that multidimensional poverty levels are higher than monetary poverty levels. The results also reveal that significant mismatches and overlaps exist, suggesting that individuals experiencing monetary and multidimensional poverty are not the same. However, the mismatch size and overlaps vary across different subgroups of the populations and place of residence. The econometric estimation results show that age, household size, household head’s education status, household head’s employment status, and location (place of residence) influence poverty mismatch and overlap in Botswana. The findings suggest the need to go beyond traditional monetary poverty measure and complement it with multidimensional poverty measure to identify those left behind. The results are critical for policy interventions, especially for monitoring the trends, understanding poverty dynamics, and targeting social assistance programmes.

Suggested Citation

  • Khaufelo Raymond Lekobane, 2022. "Does it matter which poverty measure we use to identify those left behind? Investigating poverty mismatch and overlap for Botswana," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 24(1), pages 171-196, June.
  • Handle: RePEc:spr:jsecdv:v:24:y:2022:i:1:d:10.1007_s40847-022-00181-5
    DOI: 10.1007/s40847-022-00181-5
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    More about this item

    Keywords

    Multidimensional poverty; Monetary poverty; Multinomial logit model; Sub-Saharan Africa; Botswana;
    All these keywords.

    JEL classification:

    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I39 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Other

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