Theoretical and empirical support for adjustment of nonresponse by design

Recently, various indicators have been proposed as indirect measures of nonresponse error in surveys. They employ auxiliary variables to detect nonrepresentative or unbalanced response. A class of survey designs known as adaptive survey designs maximizes these indicators by applying different treatments to different subgroups. The natural question is whether the decrease in nonresponse bias caused by adaptive survey designs could also be achieved by nonresponse adjustment methods. We discuss this question and provide theoretical and empirical considerations, supported by a range of household and business surveys. We find evidence that balancing response reduces bias more than adjustment does.