Abstract
Optimal grouping of income and wealth data under the general criterion of maximizing an inequality index for the grouped data is investigated. This approach guarantees that the optimal groups correspond to nonoverlapping income ranges and minimizes the loss of distributional detail. An algorithm is provided which will identify the optimal grouping arrangement precisely when the Gini coefficient is used. The algorithm is applied to a large microdata set, Statistics Canada's 1984 Survey of Consumer Finance, which reports both income and wealth. ‘Official’ and optimal groupings are compared, and guidelines are suggested for devising groupings which may in practice approximate the optimal arrangement.
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