Reliability of Self-reports of Financial Data in Surveys

Abstract

This article reports an investigation of errors of measurement in self-reports of financial data in the Health and Retirement Study (HRS), one of the major social science data resources available to those who study the demography and economics of aging. Results indicate significantly lower levels of reporting reliability of the composite variables in the HRS relative to those found for “summary” income approaches used in other surveys. Levels of reliability vary by type of income source—reports of monthly benefit levels from sources such as Social Security or the Veterans Administration achieve near-perfect levels of reliability, whereas somewhat less regular sources of household income that vary across time in their amounts are measured less reliably. One major area of concern resulting from this research, which may be beneficial to users of the HRS surveys, involves the use of imputation in the handling of missing data. We found that imputation of values for top-end open income brackets can produce a substantial number of outliers that affect sample estimates of relationships and levels of reliability. Imputed income values in the HRS should be used with great care.