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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 born 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.

Emerging Markets --- Gini Coefficient --- Household Surveys --- Income Distribution --- Inequality --- Inequality Measurement --- Optimal Income Threshold --- Poverty Diagnostics --- Poverty Impact Evaluation --- Tax Law

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In fragile states and areas beset by insecurity and conflict, the time available for a face-to-face interview is typically limited. That prevents administering the lengthy household consumption expenditure surveys used for measuring poverty. This paper presents a new approach to obtain unbiased estimates of poverty when the time to conduct interviews is a binding constraint. The finite list of consumption recall items is partitioned selectively into a core module and algorithmically into nonoverlapping optional modules. Each household is systematically assigned the core module and randomly assigned one of the optional modules. Multiple imputation techniques are then used to estimate total household consumption. Based on ex post simulations, the approach is demonstrated to yield reliable estimates of per capita consumption and poverty using data from a regular household budget survey collected in Hargeisa, Somaliland. The approach is then applied to a survey conducted in Mogadishu where interview time could not exceed 60 minutes.

Education --- Educational Sciences --- Hydrology --- Inequality --- Poverty And Inequality Measurement --- Poverty Assessment --- Poverty Diagnostics --- Poverty Impact Evaluation --- Poverty Lines --- Poverty Monitoring and Analysis --- Poverty Reduction --- Small Area Estimation Poverty Maps --- Survey Methods --- Water Resources

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The authors propose a modification to the conventional approach of decomposing income inequality by population sub-groups. Specifically, they propose a measure that evaluates observed between-group inequality against a benchmark of maximum between-group inequality that can be attained when the number and relative sizes of groups under examination are fixed. The authors argue that such a modification can provide a complementary perspective on the question of whether a particular population breakdown is salient to an assessment of inequality in a country. As their measure normalizes between-group inequality by the number and relative sizes of groups, it is also less subject to problems of comparability across different settings. The authors show that for a large set of countries their assessment of the importance of group differences typically increases substantially on the basis of this approach. The ranking of countries (or different population groups) can also differ from that obtained using traditional decomposition methods. Finally, they observe an interesting pattern of higher levels of overall inequality in countries where their measure finds higher between-group contributions.

Between-Group Inequality --- Differences In Income --- Economic Inequality --- Economic Policy --- Equity and Development --- Group Inequality --- Group Means --- Income --- Income Differences --- Income Distribution --- Income Inequality --- Incomes --- Inequality --- Inequality Aversion --- Inequality Decomposition --- Inequality Measurement --- Mean Differences --- Mean Income --- Mean Incomes --- Measurement Error --- Policy Research --- Population Sub-Groups --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Development --- Rural Poverty Reduction --- Services and Transfers to Poor

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The authors propose a modification to the conventional approach of decomposing income inequality by population sub-groups. Specifically, they propose a measure that evaluates observed between-group inequality against a benchmark of maximum between-group inequality that can be attained when the number and relative sizes of groups under examination are fixed. The authors argue that such a modification can provide a complementary perspective on the question of whether a particular population breakdown is salient to an assessment of inequality in a country. As their measure normalizes between-group inequality by the number and relative sizes of groups, it is also less subject to problems of comparability across different settings. The authors show that for a large set of countries their assessment of the importance of group differences typically increases substantially on the basis of this approach. The ranking of countries (or different population groups) can also differ from that obtained using traditional decomposition methods. Finally, they observe an interesting pattern of higher levels of overall inequality in countries where their measure finds higher between-group contributions.

Between-Group Inequality --- Differences In Income --- Economic Inequality --- Economic Policy --- Equity and Development --- Group Inequality --- Group Means --- Income --- Income Differences --- Income Distribution --- Income Inequality --- Incomes --- Inequality --- Inequality Aversion --- Inequality Decomposition --- Inequality Measurement --- Mean Differences --- Mean Income --- Mean Incomes --- Measurement Error --- Policy Research --- Population Sub-Groups --- Poverty Impact Evaluation --- Poverty Reduction --- Rural Development --- Rural Poverty Reduction --- Services and Transfers to Poor

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The inequality dataset compiled in the 1990s by the World Bank and extended by the United Nations has been both widely used and strongly criticized. The criticisms raise questions about conclusions drawn from secondary inequality datasets in general. The authors develop techniques to deal with national and international comparability problems intrinsic to such datasets. The result is a new dataset of consistent inequality series, allowing them to explore problems of measurement error. In addition, the new data allow the authors to perform parametric non-linear estimation of Lorenz curves from grouped data. This in turn allows them to estimate the entire income distribution, computing alternative inequality indexes and poverty estimates. Finally, the authors use their broadly comparable dataset to examine international patterns of inequality and poverty.

Cross-Country Inequality --- Data Quality --- Developing Countries --- Economic Policy --- Economic Theory and Research --- Explaining Inequality --- Gini Coefficient --- Income --- Income Distribution --- Income Inequality --- Income Study --- Inequality --- Inequality Levels --- Inequality Measurement --- Inequality Series --- Inequality Trends --- Information Security and Privacy --- International Comparability --- Macroeconomics and Economic Growth --- Measurement Error --- Measurement Problems --- Policy Research --- Poverty Estimates --- Poverty Impact Evaluation --- Poverty Reduction --- Services and Transfers to Poor --- Social Protections and Labor