Analysis of Aggregated Data in Survey Sampling with Application to Fertilizer/Pesticide Usage Survey

In many cases, the public release of survey or census data at fine geographical resolution (for example, counties) may endanger the confidentiality of respondents. A strategy for such cases is to aggregate neighboring regions into larger units that satisfy confidentiality requirements. An aggregation procedure employed in a prototype system for the US National Agricultural Statistics Service is used as context to investigate the impact of aggregation on statistical properties of the data. We propose a Bayesian simulation approach for the analysis of such aggregated data. As a consequence, we are able to specify the type of additional information (such as certain sample sizes) that needs to be released in order to enable the user to perform meaningful analyses with the aggregated data.