Abstract:The paper examines the distributional implications of selective compliance in sample surveys, whereby households with different incomes are not equally likely to participate. Poverty and inequality measurement implications are discussed for monotonically decreasing and inverted-U compliance-income relationships. We demonstrate that the latent income effect on the probability of compliance can be estimated from information on response rates across geographic areas. On implementing the method on the Current Population Survey for the United States we find that the compliance probability falls monotonically as income rises. Correcting for nonresponse appreciably increases mean income and inequality, but has only a small impact on poverty incidence up to poverty lines common in the United States.

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income distribution, poverty and inequality measurement, survey nonresponse,

We evaluate observed inequality between population groups against a benchmark of the maximum between-group inequality attainable given the number and relative sizes of those groups under examination. Because our measure is normalized by these parameters, drawing comparisons across different settings is less problematic than with conventional inequality decompositions. Moreover, our measure can decline with finer sub-partitioning of population groups. Consequently, the exact manner in which one groups the population acquires greater significance. Survey data from various countries suggest that our approach can provide a complementary perspective on the question of whether (and how much) a particular population breakdown is salient to an assessment of inequality in a country.