Income is a critical classification variable for policy-related analyses, and together with poverty status is often key in the development of public policy. Most federal household surveys collect some income data and provide measures of poverty status. Yet income is difficult to measure in household surveys, and poverty status depends not only on income but on how a family is defined, which differs across surveys. Mathematica conducted a comprehensive and systematic assessment of income data and their utility for policy-related analyses in eight major surveys: the Survey of Income and Program Participation (SIPP); the Annual Social and Economic Supplement to the Current Population Survey (CPS); the American Community Survey (ACS); the Household Component of the Medical Expenditure Panel Survey (MEPS); the National Health Interview Survey (NHIS); the Medicare Current Beneficiary Survey Cost and Use files (MCBS); the Health and Retirement Study (HRS); and the Panel Study of Income Dynamics (PSID). The assessment focused on three issues: (1) quality and usability of each survey’s income and poverty data for policy-related analyses; (2) overall impact of different design and methodological approaches; and (3) specific design and processing choices that may be related to the quality and utility of income and poverty data in each survey. Detailed findings address not only the measurement of income and poverty but other survey features that affect estimates of income and its distribution.