Estimating Permanent Income Using Indicator Variables
نویسندگان
چکیده
Household surveys in developing countries often lack modules on income and expenditure. When included, the resulting estimates show substantial measurement error and are subject to systematic reporting biases. Indicator-based indices proposed by several analysts show much promise in circumventing these difficulties but nonetheless exhibit certain limitations. We present an alternative based on a variant of the probit model, which produces a series of indicator-specific cut-points on a latent scale (permanent income). These cut-points represent values above which respondents are more likely to respond affirmatively than not, and allow estimation of household permanent income when combined with an individual household’s responses. This analysis compares estimates of permanent income using the above approach with estimates resulting from principal components analysis using household survey data from Greece, Peru and Pakistan. This new approach yields estimates of permanent income that are comparable with those of other methods in terms of rank correlation with reported income or expenditure, and offers the potential for substantially enhanced comparability across populations and greater precision and efficiency through item reduction methods.
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