TY  - RPRT
        AU  - Caliendo, Marco
AU  - Huber, Katrin
AU  - Isphording, Ingo E.
AU  - Wegmann, Jakob
        TI  - On the Extent, Correlates, and Consequences of Reporting Bias in Survey Wages
        PY  - 2026/Jul/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 18794
        UR  - https://www.iza.org/publications/dp18794
        AB  - We study the extent, correlates, and consequences of reporting bias in survey wages using German linked survey-administrative data (SOEP-CMI-ADIAB). Survey wages differ systematically from administrative records: mean survey wages are 7% lower, with mean-reverting discrepancies that firm context explains far better than individual characteristics. Since neither source alone is sufficient, we construct a hybrid wage combining their strengths. Measurement choice matters mainly through the treatment of administrative top-coding: when wages are outcomes, censoring at the assessment limit understates returns to education by 4-11% and the gender wage gap by up to 23%, while imputation reverses the bias for returns. When wages are regressors, wage-satisfaction gradients are 9-28% steeper with survey than administrative wages below the assessment limit, indicating non-classical, context-dependent misreporting. We provide guidance for choosing between administrative, survey, and hybrid wages, with lessons for any setting where self-reported wages are collected alongside top-coded administrative records.
        KW  - reporting bias
KW  - measurement error
KW  - wage
KW  - income
KW  - administrative data
KW  - survey data
KW  - data linkage
        ER  -