Using Cost-Calibration Trade-Offs in Establishment Surveys to Allocate Cases by Mode

• Activity Number: 333 - Adaptive Survey Design: Recent Advances and New Potential
• Type: Topic Contributed
• Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
• Sponsor: Survey Research Methods Section
• Author(s): Benjamin Martin Reist* and Gavin Corral and Andrew Dau and Tyler Wilson and Audra Zakzeski
• Companies: USDA, NASS and National Agricultural Statistics Service (NASS) and National Agricultural Statistics Service and USDA, NASS and National Agricultural Statistics Service

Abstract

The United States Department of Agriculture (USDA), National Agricultural Statistics Service, in conjunction with the USDA, Economic Research Service, conducts the three-part Agricultural Resource Management Survey (ARMS) to study the well-being of farm establishments. The survey instrument for the final part of ARMS (ARMS 3) is approximately 24 pages, detailed, and includes sensitive financial questions. Due to this, data collection relies heavily on expensive, in-person enumeration. Developing methods to limit the costs of data collection and decrease respondent burden while identifying possible biases is a complex task. This research explores three different strategies for identifying operations that will not be sent to field follow-up: (1) predicted impact on the calibration estimators, (2) predicted propensity to respond, and (3) using both predicted impact and propensity to respond. Simulations using prior rounds of ARMS 3 are used to evaluate the effect of these strategies on controlling cost, burden, and measures of data quality.