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Abstract
Motivated misreporting occurs when respondents give incorrect responses to survey questions to shorten the interview; studies have detected this behavior across many modes, topics, and countries. This paper tests whether motivated misreporting affects responses in a large survey of household purchases, the US Consumer Expenditure Interview Survey. The data from this survey inform the calculation of the official measure of inflation, among other uses. Using a parallel web survey and multiple imputation, this article estimates the size of the misreporting effect without experimentally manipulating questions in the survey itself. Results suggest that household purchases are underreported by approximately five percentage points in three sections of the first wave of the survey. The approach used here, involving a web survey built to mimic the expenditure survey, could be applied in other large surveys where budget or logistical constraints prevent experimentation.

AbstractSeveral studies have shown that high response rates are not associated with low bias in survey data. This paper shows that, for face-to-face surveys, the relationship between response rates and bias is moderated by the type of sampling method used. Using data from Rounds 1 through 7 of the European Social Survey, we develop two measures of selection bias, then build models to explore how sampling method, response rate, and their interaction affect selection bias. When interviewers are involved in selecting the sample of households or respondents for the survey, high reported response rates can in fact be a sign of poor data quality. We speculate that the positive association detected between response rates and selection bias is because of interviewers' incentives to select households and respondents who are likely to complete the survey.

AbstractMeasurement and analysis of change is one of the primary reasons to conduct panel surveys, but studies have shown that estimates of change from panel surveys can be subject to measurement error, most commonly overreporting of change. For this reason, many panel surveys use a technique called proactive dependent interviewing, which reminds respondents of their answer in the previous wave, and has been shown to reduce the capturing of spurious change. However, so far very little guidance exists in the literature on how such questions should be worded. Here, we use data from three experimental studies to examine question wording effects with proactive dependent interviewing. Because we link data from one of the surveys to administrative records, we can examine not only different levels of change by format, but the accuracy of the change reports as well. Our results show that how questions about current status are worded affects the reporting of change. The overall results, including comparisons with administrative records, suggest that reminding respondents of their previous answer and then asking, "Is that still the case?" produces the most accurate data on change and stability experienced by respondents.

Looping questions are used to collect data about several similar events, such as employment spells, retirement accounts, or marriages. The loops gather information about the number of events experienced as well as details about each one. The questions require respondents to think hard to recall each event and are often lengthy and repetitive. Looping questions can be asked in two formats, and which format a survey uses may aect the quality of the data collected. We develop hypotheses about the eects of format on measurement error in looping questions and test the hypotheses using experimental data from a web survey with a link to administrative records. Results show that one format collects more accurate event reports, but the other format provides higher quality data to the follow up questions. We conclude with guidance for those who write survey questions as well as those who rely on survey data for substantive analyses.

"To mitigate the effects of low survey participation rates and possible nonresponse bias in survey estimates, survey organizations often try to collect auxiliary information with which to evaluate and possibly adjust for differences between respondents and nonrespondents. Call record data and other forms of paradata are commonly used for this purpose, but these data tend to be only weakly correlated with the survey items. Follow-up surveys conducted with nonrespondents try to get around this issue by asking a subset of key items selected from the original questionnaire. However, intensive follow-up procedures are expensive and have other known limitations. In this article, we explore an alternative follow-up procedure that simply asks nonrespondents for consent to use their administrative records in lieu of taking part in a telephone survey interview. Utilizing a unique study design with administrative records available for the overall study sample, we examine characteristics of telephone nonrespondents who consent to record use in a mail follow-up survey. Interestingly, we find that many telephone nonrespondents are willing to grant access to their administrative records. These consenting nonrespondents are similar to the remaining survey nonrespondents, yet different from the telephone survey respondents, which results in reduced nonresponse bias for some key economic items. We discuss the practical implications of these findings and offer some suggestions for incorporating the collected administrative data in nonresponse bias evaluation and adjustment procedures." (Author's abstract, IAB-Doku) ((en))

"Response propensities are increasingly being used during data collection for responsive survey design applications. Better propensity models, with more predictive power, are needed to guide responsive interventions during data collection. However, available data on both respondents and nonrespondents to improve these models is limited. This analysis investigates the usefulness of a new type of paradata, in the form of an interviewer observation taken at the call-level, to increase the predictive power of propensity models. The interviewer observation investigated is the interviewer's assessment of the likelihood that a given respondent will participate in the survey, collected at each contact of a telephone study. We evaluate whether these ratings improve the fit and discrimination of 'classic' response propensity models which include call record data and interviewer characteristics. Then, the performance of the interviewer observation is tested in a simulated responsive survey design, where propensity models are generated at several dates during data collection, to determine if the observations improve the accuracy of the predictions made at these time points over using classic propensity models. The interviewer ratings not only contribute to the predictive power of the classic models overall but, on their own, appear to perform better than the classic model at predicting high probability cases in the responsive survey design context." (Author's abstract, IAB-Doku) ((en))

Panel survey participation can bring about unintended changes in respondents' behavior and/or reporting of behavior. Using administrative data linked to a large panel survey, we analyze changes in respondents' labor market behavior. We estimate the causal effect of panel participation on the take-up of federal labor market programs using instrumental variables. Results show that panel survey participation leads to a decrease in respondents' take-up of these measures. These results suggest that panel survey participation not only affects the reporting of behavior, as previous studies have demonstrated, but can also alter respondents' actual behavior. ; Die wiederholte Teilnahme an Längsschnittstudien kann zu unbeabsichtigten Verhaltensänderungen und/oder Änderungen im Antwortverhalten der Teilnehmer führen. Um solchen Verhaltensänderungen nachzugehen, haben wir Umfragedaten der Längsschnittstudie PASS mit administrativen Daten verknüpft und schätzen mittels Instrumentenvariablen den kausalen Effekt der wiederholten Umfrageteilnahme auf die Teilnahme an Maßnahmen der aktiven Arbeitsmarktpolitik. Die Ergebnisse deuten darauf hin, dass Umfrageteilnehmer aufgrund der (mehrmaligen) Teilnahme an der Befragung an weniger Maßnahmen der aktiven Arbeitsmarktpolitik teilnehmen. Diese Resultate verdeutlichen, dass die wiederholte Teilnahme an Längsschnittbefragungen sich nicht nur auf das Antwortverhalten der Teilnehmer auswirken kann, sondern auch auf deren tatsächliches Verhalten.