ESRA 2027 sessions by theme
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Methods for Measuring and Predicting Survey Costs |
| Coordinator 1 | Dr James Wagner (University of Michigan) |
| Coordinator 2 | Dr Kristen Olson (University of Nebraska-Linco) |
| Coordinator 3 | Dr Jill Dematteis (Fors Marsh) |
| Coordinator 4 | Dr John Eltinge (United States Census Bureau (Retired) ) |
| Coordinator 5 | Dr Daifeng Han (Westat) |
| Coordinator 6 | Mr Chris Jackson (SSRS) |
| Coordinator 7 | Dr Eric Rancourt (Statistics Canada) |
Session Details
Accurate measurement of survey costs is critical for informed decision-making that balances costs and errors. However, there is very little research that focuses on measuring or predicting costs, particularly in relation to other research objectives. This session seeks research that addresses this gap.
Often, costs are measured with error (e.g. hours worked but not reported) or measured at levels of aggregation different from those where design decisions are made (e.g. interviewers report hours worked each day but not for each case in the sample). These issues can make it difficult to accurately assess where investment produces the best return. Accurate cost measurement from current surveys should lead to more cost-effective design decisions for future surveys.
Cost predictions can be inaccurate due to multiple factors, including inaccurate measurement of costs in previous studies, widespread inflation, changes in the survey environment such as falling response rates, or other factors external to the design of the survey. Methods for improving the accuracy and precision of cost predictions would improve the evaluation of cost-error tradeoffs.
This session seeks papers on survey cost measurement, prediction, estimation, classification, and evaluation, continuing recent interest in studying and reporting survey costs. This session has a special interest in presentations that focus on costs as an outcome – that is, the goal of the paper is to empirically examine cost measures, rather than variation of survey outcomes across methods that vary in costs. These papers may explore relationships among cost measures, variation in costs across studies, errors in cost measurement and estimation, improved cost prediction methods, and cost aggregation for evaluating cost–error tradeoffs. Topics may include cost measurement, cost classification, costs of non-survey data, cost estimation error, and the relationship between survey costs and errors.
