Estimating the Level of Underreporting of Expenditures among Expenditure Reporters: A Micro‐level Latent Class Analysis

Clyde Tucker, Brian J. Meekins, and Paul P. Biemer


This paper uses latent class analysis (LCA) to estimate the amount of underreporting on the BLS Consumer Expenditure Quarterly Survey (CEQ). Specifically, it models underreporting in a given commodity category by those reporting a purchase of any item within that category. This work builds on work presented at ASA last year and is based on an analysis of micro-level, procedural indicators. Data from the CEQ for the years 1996 to 2003 are used in the analysis. A variety of LC models are used to evaluate observed expenditure reporting patterns in several commodity categories. Model covariates include characteristics of the interview, the respondent, and the household. Best-fitting models are determined from well-known statistical tests and subjective diagnostics developed by the authors. Issues related to correlated classification errors are discussed, and methods for combining and evaluating estimates of underreporting are developed.