Abstract
Item non response is a pervasive problem in survey data, and a large literature in statistics has developed to address missing data due to item non response. Government statistical agencies regularly impute for missing values in the microdata that they make available to researchers. Unfortunately, while the imputation methods typically used by government statistical agencies may be suitable for the main objectives of the agency—usually, publishing aggregated descriptive statistics—these imputations are usually unsuitable for multivariate analysis of microdata. Using USDA’s Agricultural Resource Management Survey (ARMS), we apply a new imputation method to missing 2008ARMS data on federal government farm commodity payments and off-farm household income items. We find that the choice of imputation method can have a noticeable effect on important economic indicators, even when the rate of missingness is small.
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