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Measuring Distribution of Wealth in Zambia Using Census Micro Data: An Application of Principal Component Analysis

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  • Floyd Mwansa

    (University of Lusaka, Zambia.)

Abstract

Census data for Zambia was used to estimate the distribution of wealth in Zambia by constructing the Wealth Index as a measure of socioeconomic status using Principal Component Analysis. The reliability of the index is observed from three fronts; coherence, robustness and validity in representing household socioeconomic status. Classifying the households across all quartiles is highly consistent and robust. The index s performance in predicting the welfare distribution is analogous to established and most widely used methods from Demographic Health Surveys, as evidenced by similarities in the statistical distributions. Unlike other survey estimates, the index has been produced at the subnational level, such as district, enabling the classification of Zambia s districts according to their socioeconomic status. The index can be used to predict other socioeconomic outcomes, such as education and health, via Small Area Estimation techniques and determine district-level resource allocation by the central government.

Suggested Citation

  • Floyd Mwansa, 2023. "Measuring Distribution of Wealth in Zambia Using Census Micro Data: An Application of Principal Component Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 13(3), pages 126-140, May.
    • Handle: RePEc:eco:journ1:2023-03-13
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    References listed on IDEAS

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    1. Alessandro Tarozzi & Angus Deaton, 2009. "Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 773-792, November.
    2. Diana K. L. Ngo & Luc Christiaensen, 2019. "The Performance Of A Consumption Augmented Asset Index In Ranking Households And Identifying The Poor," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(4), pages 804-833, December.
    3. Isabelle CASSIERS & Géraldine THIRY, 2014. "A High-Stakes Shift: Turning the Tide From GDP to New Prosperity Indicators," LIDAM Discussion Papers IRES 2014002, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    4. Lefteris Tsoulfidis & Ioannis Athanasiadis, 2022. "A new method of identifying key industries: a principal component analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 11(1), pages 1-23, December.
    5. Alejandro de la Fuente & Andreas Murr & Ericka Rascón, 2015. "Mapping Subnational Poverty in Zambia," World Bank Publications - Reports 21783, The World Bank Group.
    6. Leonardo Gasparini & Walter Sosa Escudero & Mariana Marchionni & Sergio Olivieri, 2008. "Income, Deprivation, and Perceptions in Latin America and the Caribbean: New Evidence from the Gallup World Poll," IDB Publications (Working Papers) 45618, Inter-American Development Bank.
    7. Lovaton Davila, Rodrigo & McCarthy, Aine Seitz & Gondwe, Dorothy & Kirdruang, Phatta & Sharma, Uttam, 2022. "Water, walls, and bicycles: wealth index composition using census microdata," Journal of Demographic Economics, Cambridge University Press, vol. 88(1), pages 79-120, March.
    8. Theodore Mariolis & Lefteris Tsoulfidis, 2018. "Less Is More: Capital Theory And Almost Irregular-Uncontrollable Actual Economies," Contributions to Political Economy, Cambridge Political Economy Society, vol. 37(1), pages 65-88.
    9. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    10. Mark Montgomery & Michele Gragnolati & Kathleen Burke & Edmundo Paredes, 2000. "Measuring living standards with proxy variables," Demography, Springer;Population Association of America (PAA), vol. 37(2), pages 155-174, May.
    11. Luc Christiaensen & Peter Lanjouw & Jill Luoto & David Stifel, 2012. "Small area estimation-based prediction methods to track poverty: validation and applications," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(2), pages 267-297, June.
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    More about this item

    Keywords

    principal component analysis; Wealth Index; Socioeconomic Status;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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