The prominence of surveys is based on the assumption that survey measurements are accurate. A plethora of papers and books address survey errors resulting from coverage, sampling, nonresponse, and measurement issues. However, no comprehensive review exists of the evidence on survey accuracy. The goal of this paper is to provide a thorough review of past research that provided objective evidence on the accuracy of self-reported data, across a wide spectrum of content areas including crime, demographics, economic indicators, healthcare, labor force statistics, market research, philanthropy, politics, psychology, substance abuse, media, and much more. We show how survey measurement has been evaluated using a variety of methods - comparing each respondent's self-report (e.g. hospital stays, tax evasion, home ownership, medical screenings and diagnosis) with objective individual records of the same phenomena; correlating aggregate distributions of respondents' reports with distributions of the same phenomena derived from secondary data not based on self-reports; comparing one-time aggregate survey estimates (e.g. height, weight, healthcare costs, absenteeism, cigarette smoking) with available benchmarks; and comparing trends over time between longitudinal aggregate survey estimates (e.g. NCVS crime rates, NES voter turnout rates) with available benchmarks. Taken together, the existing evidence demonstrates that the vast majority of survey measures of objective phenomena are highly accurate.