Using Time Series Models to Understand Survey Costs

Abstract

Survey costs are an understudied area. However, understanding survey costs is critical for making efficient decisions about cost-error trade-offs, as well as to accurately project future costs. In this article, we examine a measure of survey costs - per interview costs - over time in a repeated cross-sectional survey. We examine both measurement issues and variability in costs. The measurement issues relate to the classification of various costs into the appropriate time period. We explore several issues that make this process of classification difficult. A time series analysis is then utilized to examine the trends and seasonality in per interview costs. Under the assumptions of our model, after removing the trend and seasonality components, the remainder is variation in costs. This approach allows us to treat survey cost estimates in a manner similar to any other survey estimate.