Darkness made visible: Field management and nonresponse in the 2004 SCF

Article type: Research Article

Authors: Kennickell, Arthur B.

Affiliations: Board of Governors of the Federal Reserve System (Ret.), Washington, DC 20551, USA. E-mail: [email protected]

Abstract: Nonresponse in field surveys is the joint outcome of the decision of survey staff to apply effort to inform and persuade respondents, and the evaluation of such inputs by respondents. In most such surveys, the field staff are under great pressure to produce completed interviews. Thus, they have an incentive to apply effort to cases that are most likely, in their view, to be completed with least effort. To the extent that interviewers' perceptions are unbiased, such behavior would tend to amplify latent patterns of nonresponse. When the characteristics of respondents that affect the likelihood of participation are correlated with variables of analytical interest in the survey, bias results, unless a means can be found of discovering and adjusting for the underlying behavioral structures. But, absent constraints on the behavior of interviewers, the observed outcomes are contaminated by the endogeneity of effort, and only strong a priori assumptions could disentangle the interviewer effects from the respondent effects. To address the problem of endogenous effort, the 2004 Survey of Consumer Finances introduced a phased plan of sample management to make effort more nearly exogenous through the first two of three phases of field work. Thus, nonresponse in these controlled stages should largely reflect respondent characteristics, not a mixture of respondent and interviewer characteristics. The dual frame design of the SCF offers two classes of sample cases for modeling nonresponse. For the area-probability sample, tract-level data are available from the 2000 Census of Population. For the list sample, case-specific data based on statistical records derived from tax returns are available. For both set of cases, some interviewer observations are also available. This paper presents estimates of nonresponse models based on these data.

Keywords: Nonresponse, interviewers, paradata

DOI: 10.3233/SJI-160277

Journal: Statistical Journal of the IAOS, vol. 33, no. 1, pp. 101-111, 2017