Estimation With Response Error and Nonresponse

2001/04/01 by Christopher R Bollinger, Christopher R. Bollinger, Martin H David +1 · 3 citations
Economics, Econometrics and Finance · Social Sciences · #Economics of Agriculture and Food Markets #Gender, Labor, and Family Dynamics #Income, Poverty, and Inequality

paper · doi:10.1198/073500101316970368

openalex publication_date 2001/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/26

Abstract

Error in survey data originates from failure to contact the sample and from false answers to verifiable questions. These errors may be systematic and associated with uncooperative or unreliable respondents. Zabel modeled attrition in the Survey of Income and Program Participation and found systematic demographic and design effects. Bollinger and David modeled response error and identified correlations to income per capita. In this analysis, we link missing interviews in a panel and response error through a trivariate probit analysis. Robustness of the correlation between attrition and response error is examined by comparing variants of the model. The joint model of response error and attrition becomes the first stage of a pseudolikelihood estimate of a model of food-stamp participation. The model is significantly different from naive probit on the survey data.

Cited by

• Estimating Program Participation with Partial Validation
• Do Non-Response Follow-Ups Improve or Reduce Data Quality?: A Review of the Existing Literature
• Inference problems in binary regression model with misclassified\n responses

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