An Errors-in-Variables Approach to Estimating Models with Small Area Data

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Abstract
Many important social science models are estimated with subnational units, such as states, congressional districts, or counties as the units of observation. These analyses may require estimates of population characteristics for these units that are not readily available from published sources. Frequently the size and number of these units make direct data collection, such as household surveys, prohibitively expensive or completely infeasible. The need is to develop methods for using more readily available data to estimate these subgroup attributes. This article presents such a method based on national-level survey data.

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