Identifying Data Problems and Improving Data Quality in the Survey of Consumer Finances

• Activity Number: 162
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Survey Research Methods Section
• Author(s): Catherine Haggerty*+ and Micah Sjoblom and Steven Pedlow
• Companies: NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago
• Keywords: data quality ; remedial training ; data improvement ; process improvement

Abstract

Since the Survey of Consumer Finances delves into every financial detail of a household's finances, maximizing data quality is a constant challenge. NORC designed and implemented a refined data quality process and review cycle. All interviewer commentary including call record entries, interviewer comments recorded during questionnaire administration and interviewer debriefing notes recorded post-interview are reviewed for potential quality issues related to respondent identification and questionnaire administration. Along with FRB staff, the NORC team evaluates the questionnaire data and identifies potential errors and anomalies that require follow-up. These evaluations are incorporated into a timely and systematic feedback loop delivered to interviewers. This feedback triggers remedial actions designed to address quality deficiencies (e.g., broadcast memos regarding proper protocol, self-directed electronic training, and supervisor-led training) and provides an on-going assessment of interviewer performance. We will describe the processes used to identify data quality issues, our data quality improvement protocols, and data quality measures over time.