It is a common practice to use the auxiliary variables to impute missing values from item nonresponse in surveys. Sometimes there are few auxiliary variables for missing value imputation, but if spatial and time autocorrelations exist, we should use these correlations for better results. Recently, Lee et al. (2006) showed that spatial autocorrelation could be efficiently used for missing value imputation when spatial autocorrelation existed, using the data from the farm household economy data in Gangwon-do, 2002. In this paper, we present au evaluation of spatial and space-time nonresponse imputation methods when there exist spatial and time autocorrelations using the monthly data during 2000-2002 from the same data previously used by Lee et al. (2006). We show that space-time imputation method is more efficient than the other through the numerical simulations.