Using data from the Consumer Expenditure Survey and the March Current Population Survey, we are calculating historical poverty estimates based on the new Supplemental Poverty Measure (SPM) from 1960 to 2010, focusing particular attention on changes within 2 population subgroups--children and the elderly. We also examine how changes to social welfare policies have impacted poverty over time. Despite numerous changes to welfare state policy over the last few decades, poverty as officially measured had seemingly stagnated, prompting some policy makers and politicians to declare that expansions of the welfare state have no impact on poverty reduction. However, the official poverty measure does not account for the effect of near-cash transfers on the financial resources available to families. Additionally, the official measure does not account for medical, child care, and work expenditures, nor the financial benefit of owning a home free and clear of a mortgage, all while using a poverty threshold based on an out of date conception of family necessities. Family needs, expenditures, and income have changed dramatically over the past five decades and the use of the SPM presents an opportunity to re-evaluate historical poverty trends in a more accurate light. The SPM is based on recommendations from a 1995 National Academies of Science panel, has been validated for city, state, and national use, and  beginning is 2011 is now produced alongside the official measure by the U.S. Census Bureau beginning in 2011 (Citro & Michael 1995; Hutto et al 2011; New York City CEO 2011; Ziliak 2010). We focus on several parameters of particular interest to policymakers. First, we examine whether SPM poverty tracks OPM poverty rates over time, both overall and by major age subgroups. Second, we estimate counterfactual poverty rates subtracting out safety net resources like SNAP and the EITC, and demonstrate the extent that these programs “lift” people out of poverty over time, and whether the magnitude of this has changed. Lastly we investigate the robustness of our estimates to choices made about imputation strategies and benefit valuation.