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Multidimensional poverty in the Philippines, 2004–2013: How much do choices for weighting, identification and aggregation matter?

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  • Gaurav Datt

    (Monash University)

Abstract

Multidimensional poverty comparisons can be sensitive to the choice of weights assigned to the indicators as well as the aggregate poverty measure used. This paper examines the robustness of trends in multidimensional poverty in the Philippines to these choices by presenting estimates for three alternative weighting schemes and three methods of identification and aggregation. Using data for 2004–2013, the paper finds evidence of a significant decline in multidimensional poverty that is robust to these alternatives, though the magnitude of the decline in and the dimensional contributions to aggregate multidimensional poverty are quite sensitive to the alternatives considered.

Suggested Citation

  • Gaurav Datt, 2019. "Multidimensional poverty in the Philippines, 2004–2013: How much do choices for weighting, identification and aggregation matter?," Empirical Economics, Springer, vol. 57(4), pages 1103-1128, October.
    • Handle: RePEc:spr:empeco:v:57:y:2019:i:4:d:10.1007_s00181-018-1493-9
    DOI: 10.1007/s00181-018-1493-9
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    References listed on IDEAS

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    1. Gaurav Datt, 2019. "Distribution-Sensitive Multidimensional Poverty Measures," The World Bank Economic Review, World Bank, vol. 33(3), pages 551-572.
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    Cited by:

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    More about this item

    Keywords

    Multidimensional poverty; Weighting; Identification and aggregation; Philippines;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • N35 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Asia including Middle East

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