Handling Nonresponse in Business Surveys

Abstract

Business surveys are a valuable indication of the current and the future economic situation. However refusals are very common in this context and may induce bias in the estimates of interest. In this paper the problem of adjusting for nonresponse estimators of relevant economic outcomes is considered. Using a large simulation study, we investigate how weighting adjusted procedures are influenced by the specification of the response model utilised in calculation of the weights. We consider, in particular, how trimming the weights can have an impact on the final estimates and we propose a bootstrap-based procedure to determine an optimal trimming threshold. We illustrate the procedure using a 2009 survey of a large population of Italian firms.

Keywords

• regression estimator
• nonresponse weighting adjustment
• trimming
• bootstrap
• business surveys