Tackling city-regional dynamics in a survey using grid sampling

Abstract

"The paper considers a Finnish human survey that takes advantage of explicit stratification. Stratification is not ordinary, since there are two types of stratification. In one, the strata are municipality based that are much used earlier. But in the second, these take advantage of the grid data base in which the grid size is 250 metres times 250 metres. Using the grid data base the two explicit strata are constructed, one consisting of such grids where the median tax income of the adults is low (called 'poor' grids), whereas the median income is high in the second explicit stratum of such grids ('rich' grids). In order to correctly handle these both stratified data, it is required first to merge them together, next to create the single sampling weights, and finally, due to 60 per cent non-response to adjust for these weights. This helps in reducing the bias of the estimates. The adjustment is strengthened with good auxiliary data both from the grid data base and other administrative sources." (author's abstract)