%0 Report
        %A Caliendo, Marco
%A Huber, Katrin
%A Isphording, Ingo E.
%A Wegmann, Jakob
        %T On the Extent, Correlates, and Consequences of Reporting Bias in Survey Wages
        %D 2026
        %8 2026 Jul
        %I Institute of Labor Economics (IZA)
        %C Bonn
        %7 IZA Discussion Paper
        %N 18794
        %U https://www.iza.org/index.php/publications/dp18794
        %X 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.
        %K reporting bias
%K measurement error
%K wage
%K income
%K administrative data
%K survey data
%K data linkage