The definition and operationalization of wealth information in population surveys and the corresponding microdata requires a wide range of more or less normative assumptions. However, the decisions made in both the pre- and post-data-collection stage may interfere considerably with the...

Population surveys around the world face the problem of declining cooperation and participation rates of respondents. Not only can item nonresponse and unit nonresponse impair important outcome measures for inequality research such as total household disposable income; there is also a further...

This paper deals with the question of selectivity of missing data on income questions in large panel surveys due to item-non-response and with imputation as one alternative strategy to cope with this issue. In contrast to cross-section surveys, the imputation of missing values in panel data can...

This paper examines the implication of the move to CAPI for data quality by analyzing the conversion from PAPI to CAPI of a subsample of the German Socio-Economic Panel (SOEP) which was done within an experimental design. The 2000 addresses for the sample E of SOEP were split into two subsamples...

Statistische Daten sind im allgemeinen - gemessen an idealtypischen Erhebungsbedingungen - nicht fehlerfrei, insbesondere können sie durch die Art, wie sie erhoben werden, beeinflusst werden ("Erhebungsartefakte"). Interviewereffekte spielen in diesem Zusammenhang in der Literatur eine...

The availability of panel data on the basis of micro data has become an indispensable component of the infrastructure of empirically oriented social scientists and economists. This is also a consequence of the fact that, for a panel survey, the quality of both content and methodological analyses...

This paper presents two new tools for the identification of faking interviewers in surveys. One method is based on Benford's Law, and the other exploits the empirical observation that fakers most often produce answers with less variability than could be expected from the whole survey. We focus...