Identification, characteristics and impact of faked interviews in surveys : an analysis by means of genuine fakes in the raw data of SOEP

To the best of our knowledge, most of the few methodological studies which analyze the impact of faked interviews on survey results are based on ?artificial fakes? generated by project students in a ?laboratory environment?. In contrast, panel data provide a unique opportunity to identify data which are actually faked by interviewers. By comparing data of two waves almost all fakes are easily identifiable. So the raw data of the German Socio- Economic Panel Study (SOEP) provide a rich source of faked interviews because it is built on several sub-samples. However, because interviewers know that panel respondents will be interviewed again over the course of time, clever interviewers will not fake panel interviews. In fact, in raw data of SOEP the share is about only 0.5 percent of all records. The fakes are used for an analysis of the potential impact of non detected fakes on survey results. The major result is that the faked records have no impact on the mean and the proportions. But in very rare, exceptional cases there may be a bias in estimates of correlations and regression coefficients if fakes would not be detected. One should note that – except for some fakes in the first two waves of sample E – faked data were never disseminated within the widely-used SOEP. The fakes were detected before the data were released

Identification, Characteristics and Impact of Faked Interviews in Surveys : An analysis by means of genuine fakes in the raw data of SOEP

To the best of our knowledge, most of the few methodological studies which analyze the impact of faked interviews on survey results are based on 'artificial fakes' generated by project students in a 'laboratory environment'. In contrast, panel data provide a unique opportunity to identify data which are actually faked by interviewers. By comparing data of two waves, unequivocal fakes are easily identifiable. However, in most surveys there is no second wave because they have a pure cross-sectional nature. In search of a method which does not need two waves of data we test an unconventional benchmark called Benford's Law, which is used by several accountants to discover frauds. Our preliminary results let us conclude that Benford's Law might be not an efficient method for detecting faked data, but it might be a new instrument for quality control of the interviewing process The raw data of the German Socio-Economic Panel Study (SOEP) provide a rich source of faked interviews because it is built on several sub-samples. However, because interviewers know that panel respondents will be interviewed again over the course of time, clever interviewers will not fake panel interviews. In fact, in raw data of SOEP the share is about only 0,5 percent of all records. The fakes are used for an analysis of the potential impact of non detected fakes on survey results. The major result is that the faked records has no impact on the mean and the proportions. But in very rare, exceptional cases there may be a bias in estimates of correlations and regression coefficients if fakes would not be detected. One should note that - except for some fakes in the first two waves of sample E - faked data were never disseminated within the widely-used SOEP. The fakes were detected before the data were released

Individual and Neighborhood Determinants of Survey Nonresponse – An Analysis Based on a New Subsample of the German Socio-Economic Panel (SOEP), Microgeographic Characteristics and Survey-Based Interviewer Characteristics

This study examines the phenomenon of nonresponse in the first wave of a refresher sample (subsample H) of the German Socio-Economic Panel Study (SOEP). Our first step is to link additional (commercial) microgeographic data on the immediate neighborhoods of the households visited by interviewers. These additional data (paradata) provide valuable information on respondents and nonrespondents, including milieu or lifestyle, dominant household structure, desire for anonymity, frequency of moves, and other important microgeographic information. This linked information is then used to analyze nonresponse. In a second step, we also use demographic variables for the interviewer from an administrative data set about the interviewers, and, in a third step, we use the results of a special interviewer survey. We use multilevel statistical modeling to examine the influence of neighborhoods and interviewers on non-contacts, inability to participate, and refusals. In our analysis, we find our additional variables useful for understanding and explaining non-contacts and refusals and the inability of some respondents to participate in surveys. These data provide an important basis for filling the information gap on response and nonresponse in panel surveys (and in cross-sectional surveys). However, the effect sizes of these effects are negligible. Ignoring these effects does not cause significant biases in statistical inferences drawn from the survey under consideration

Dissatisfied with Life or with Being Interviewed? Happiness and Motivation to Participate in a Survey

Information on the number of interviewer contacts allows insights into how people's responses to questions on happiness are connected to the difficulty of reaching potential participants. Using the paradata of the German Socio-Economic Panel Study (SOEP), this paper continues such research by revealing a strong link between respondent motivation and reported happiness. Analyses of responses by future non-respondents substantiate this finding and shed light on a key question for empirical research on subjective well-being, which is whether the unhappy tend to avoid survey participation or whether the unwilling might respond more negatively when being asked about their satisfaction with life

Die Euro-Krise. Wirtschaftliche, rechtliche und politische Aspekte

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Die Schaetzung von Reliabilitaet und Stabilitaet der Zufriedenheitsangaben im sozio-oekonomischen Panel

Available from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, Duesternbrook Weg 120, D-24105 Kiel C 195980 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Response Style und Response Set: eine Laengsschnittuntersuchung zu den Zufriedenheits- und Einstellungsfragen im sozio-oekonomischen Panel

Available from Bibliothek des Instituts fuer Weltwirtschaft, ZBW, D-21400 Kiel W 261 (96.405) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman