Cold deck and ratio imputation

Imputation is a common procedure to compensate for nonresponse in survey problems. Using auxiliary data, imputation may produce estimators that are more efficient than the one constructed by ignoring nonrespondents and re-weighting. We study and compare the mean squared errors of survey estimators based on data imputed using three difference imputation techniques: the commonly used ratio imputation method and two cold deck imputation methods that are frequently adopted in economic area surveys conducted by the U.S. Census Bureau and the U.S. Bureau of Labor Statistics.