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.