Measuring Inequality from Top to Bottom [electronic resource] / Diaz-Bazan, Tania
Material type: TextPublication details: Washington, D.C., The World Bank, 2015Description: 1 online resource (26 p.)Subject(s): Emerging Markets | Gini Coefficient | Household Surveys | Income Distribution | Inequality | Inequality Measurement | Optimal Income Threshold | Poverty Diagnostics | Poverty Impact Evaluation | Tax LawAdditional physical formats: Diaz-Bazan, Tania: Measuring Inequality from Top to Bottom.Online resources: Click here to access online Abstract: This paper presents a new methodology to measure inequality that optimally combines household survey information and tax records to construct a complete income distribution. Combining the two data sources is necessary because, on the one hand, household surveys do not accurately represent the wealthiest segment of the population, while tax records do; on the other hand, the opposite is true for the lower end of the income distribution: tax records only include incomes above a certain threshold. The key innovation of the proposed methodology-and the main difference from the existing literature-is the choice of an optimal income threshold b. The Gini coefficient for the population is then computed combining the conditional income distributions for incomes below b (using household survey data) and above b (using tax records). Central to this methodology is the fact that b is not chosen arbitrarily: it should be determined in such a way as to minimize reliance on household survey data to compute the top of the income distribution. In practice, the optimal b corresponds to the minimum income level that triggers mandatory tax filing. The proposed methodology is applied to the case of Colombia.This paper presents a new methodology to measure inequality that optimally combines household survey information and tax records to construct a complete income distribution. Combining the two data sources is necessary because, on the one hand, household surveys do not accurately represent the wealthiest segment of the population, while tax records do; on the other hand, the opposite is true for the lower end of the income distribution: tax records only include incomes above a certain threshold. The key innovation of the proposed methodology-and the main difference from the existing literature-is the choice of an optimal income threshold b. The Gini coefficient for the population is then computed combining the conditional income distributions for incomes below b (using household survey data) and above b (using tax records). Central to this methodology is the fact that b is not chosen arbitrarily: it should be determined in such a way as to minimize reliance on household survey data to compute the top of the income distribution. In practice, the optimal b corresponds to the minimum income level that triggers mandatory tax filing. The proposed methodology is applied to the case of Colombia.
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