1. Who are the Nonresondents? An Analysis Based on a New Subsample of the German Socio-Economic Panel (SOEP) including Microgeographic Characteristics and Survey-Based Interviewer Characteristics Jörg-Peter Schräpler 12, Jürgen Schupp 23 and Gert G. Wagner 24 1 Ruhr-University Bochum, LDS NRW 2 DIW Berlin, 3 FU Berlin, 4 Berlin University of Technology Q 2008 Conference, Rome, 8th.-11th. July 2008

2. 2 Outline Introduction Reasons for Unit Nonresponse Nonresponse in Sample H Descriptive Analysis Microgeographic data Interviewer data Multilevel Analysis Consequences Summary and Conclusion

3. 3 Introduction Unit nonresponse is one of the most important issues in the empirical social science Danger of selectivity: leads to biased samples, samples are not random it is important to investigate in which manner the realized sample differ from the intended sample and to look at the consequences Main reasons for Nonresponse: Problem of Non-Accessibility Problem of Non-Ability Problem of Refusals

4. 4 Reasons for Nonresponse 1. level: Accessibility Result of impossibility to contact household members. It can be seen as (Groves/Couper 1998): a function of the physical reachability of the household the circadian rhythm of the household members contact strategies of the interviewers  Problem: Causes often can‘t be measured directly Some empirical findings: socio-economic status, household size, vocational status and age are important for mobility (cf. Goyder 1987, Schneekloth/Leven 2003, Koch 1997, Schräpler 2000) Interviewers with higher workload have less nonresponse due to non- reachability (cf. Schräpler 2000)

5. 5 Reasons for Nonresponse 2. level: Ability Unit Nonresponse depends on the ability of the household member to participate Individuals are ill and can‘t participate. Assumption: health problems increase with the age of the respondent (c.f. Schneekloth/Leven 2003) Assumption: sometimes an alibi and a „soft refusal“

6. 6 Reasons for Nonresponse 3. level: Motivation/Cooperation depends on respondents’ assessment of the interview situation and evaluation of the consequences of possible actions (RC theory) Opportunity costs  an interview takes time, survey has to serve a meaningful purpose Privacy and confidentially concerns  invasion of privacy (cf. Singer et al 1993)  critical distance and possible mistrust of surveys in more intellectual environments in Germany (Schneekloth/Leven 2003) Fear of crime  high population density areas, anonymous residential zones (cf. Schnell 1997, Koch 1997, Goyder 1987, DeMaio 1980) Interviewer  interviewer’s age, gender, motivation, attitudes and experience (cf. Esser 1986, Loosveldt et al. 1998, Schräpler 2006, 2004, 2000)

7. 7 SOEP - Sample H - Fieldwork Subsample H of SOEP started in year 2006 From 6,000 household addresses (4 per sample point) overall 3,931 household addresses were recorded by random walk The process of address recording is separated from the interviewing process: the interviewer receives fixed addresses from the fieldwork organization The first wave was launched by 234 interviewers. Of these, 143 were already members of the SOEP staff. All interviews were carried out by CAPI

8. 8 Nonresponse in Sample H

9. 9 Nonresponse Analyses – Information gap Serious problem for nonresponse analysis: Information gap on respondents and nonrespondents  to fill the gap we use commercial microgeographic data on the households‘ immediate neighbourhood demographic variables of the interviewers results of an interviewer questionnaire

10. 10 Microgeographic Information Use of additional commercial microgeograhic data on the households’ immediate neighbourhoods from the MOSAIC Data system contains more than 75 individual characteristics used to analyse and describe customer databases or markets  for instance Sinus Milieus®, Status, removal volume etc. information is available at the address level and contains 17.8 million buildings in Germany  the building level contains seven or eight households on average (at least five households)  Important: linked information is not necessary in line with the reality of the particular household (only an approximation for the neighbourhood)

11. 11 Interviewer data Use of interviewer data from the SOEP interviewer data set mainly demographic variables like gender, age, education, family status etc. Use of a dataset based on a interviewer questionnaire mainly personality variables and self assessments filled out by 165 of the 234 SOEP interviewers in sample H

12. 12 Respondents by Sinus Milieus (N=1,449) rel. Bias in % Ref.: Milieu distr. for addresses < -50 > -50 till -30 > -30 till -10 > -10 till +10 > +10 till +30 > +30 till +50 > +50

13. 13 Refusals by Sinus Milieus (N=1,435) rel. Bias in % Ref.: Milieu distr. for addresses < -50 > -50 till -30 > -30 till -10 > -10 till +10 > +10 till +30 > +30 till +50 > +50

14. 14 Noncontact by Sinus Milieus (N=470) rel. Bias in % Ref.: Milieu distr. for addresses < -50 > -50 till -30 > -30 till -10 > -10 till +10 > +10 till +30 > +30 till +50 > +50

15. 15 „Not Able to Participate“ by Sinus Milieus (N=167) rel. Bias in % Ref.: Milieu distr. for addresses < -50 > -50 till -30 > -30 till -10 > -10 till +10 > +10 till +30 > +30 till +50 > +50

16. 16 Four Multilevel Logit Models Model 1 – probability for response variable „interview“ (participation) vs. non-response Model 2 – probability for response variable „refuse to participate“ vs. „participate“ Model 3 – probability for response variable „household not reachable“ vs. „participate“ Model 4 – probability for response variable „household not able to participate“ vs. „participate“ Two sets of Predictors: 1. Model version A with demographic and household variables for the potential respondents, microgeographic variables and demographic variables for the interviewer 2. Model version B with additional interviewer variables from the interviewer questionnaire

17. 17 Two-level Logit Models Random-Intercept Model: Level 1: respondents, Level 2: interviewers

18. 18 Version A:Multilevel logit estimates – age of the potential respondents

19. 19 Version A:Multilevel logit estimates – Sinus Milieus for the potential respondents

20. 20 Version A:Multilevel logit estimates – Interviewer variables

21. 21 Version A:Multilevel logit estimates – area description

22. 22 Version A:Multilevel logit estimates –size of houses and frequency of moves

23. 23 Version A:Multilevel logit estimates – family structure in the neigbourhood

24. 24 Version A:Multilevel logit estimates – Random effects

25. 25 Version B: Variables from the interviewer data set

26. 26 Version B:Variables from the interviewer questionnaire

27. 27 Version B:Multilevel logit estimates – Random effects

28. 28 Summary (1) Refusals, noncontact and “unable to participate” relate to different respondent, area and interviewer characteristics: Respondent is easy to persuade: well-established Sinus Milieu age <= 35 years high income families, new private owned houses, old families in outskirts interviewer with high workload, with experience, with self assessment: amicable, satisfied with own life, not easy flustered

29. 29 Summary (2) Respondent refuse more likely : Sinus Milieu: new middle class, experimentalists, modern performer age > 45 – 50 years families with children cities, simple urban estate interviewer with  low workload,  with less experience,  high level education,  age < 40 & male  with self assessment: not amicable, unsatisfied with own life, patient, not reserved

30. 30 Summary (3) Respondent is difficult to contact : Sinus Milieu: experimentalists, modern performer age > 45 – 50 & age > 55 – 60 years single household cities, simple urban estate, areas with high freq. of moves interviewer with  high level education,  with self assessment: not creative, not reserved

31. 31 Summary (4) Respondent use “not able to participate” : Sinus Milieu: upper conservative, traditionalists, new middle class, modern performer smaller than cities areas with higher frequency of moves interviewer with  male  low workload,  with self assessment: not communicative, unsatisfied with own life, sluggish, not inquisitive, easy flustered, patient, not reserved  with higher need of social approval  Result does not indicate illness of respondents as expected, but that it may be an alibi used by respondents to avoid participation

32. 32 Conclusion Microgeographic data, interviewer data as well as interviewer questionnaires are an important source to fill the information gap on respondents and nonrespondents. Next step of analyses:  interaction terms between respondent, interviewer and area  Multilevel Poisson Regressions for the number of contacts used in this sample