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In this paper, we consider the use of auxiliary and paradata for dealing with non-response and measurement errors in household surveys. Three over-arching purposes are distinguished: response enhancement, statistical adjustment, and bias exploration. Attention is given to the varying focus at the different phases of statistical production from collection, processing to analysis, and how to select and utilize the useful auxiliary and paradata. Administrative register data provide the richest source of relevant auxiliary information, in addition to data collected in previous surveys and censuses. Due to their importance in effective dealings with non-sampling errors, one should make every effort to increase their availability in the statistical system and, at the same time, to develop efficient statistical methods that capitalize on the combined data sources.

Summary Non-response is a common source of error in many surveys. Because surveys often are costly instruments, quality-cost trade-offs play a continuing role in the design and analysis of surveys. The advances of telephone, computers, and Internet all had and still have considerable impact on the design of surveys. Recently, a strong focus on methods for survey data collection monitoring and tailoring has emerged as a new paradigm to efficiently reduce non-response error. Paradata and adaptive survey designs are key words in these new developments. Prerequisites to evaluating, comparing, monitoring, and improving quality of survey response are a conceptual framework for representative survey response, indicators to measure deviations thereof, and indicators to identify subpopulationsthatneedincreasedeffort.Inthispaper,wepresentanoverviewofrepresentativeness indicators or R-indicators that are fit for these purposes. We give several examples and provide guidelines for their use in practice.