*Names in bold indicate Presenter
The recent recession has imposed economic problems on many households, but during the same time, the safety net has expanded significantly and taxes have been lowered. This raises the question in how far the safety net was able to prevent incomes of households below or near the poverty line from falling and whether some households were overcompensated for the loss of income by the increased transfer payments. On the other hand, research by Blank and co-authors points to a large and growing share of people who do not work and are not reached by the safety net. Did the recession increase this share of disconnected households or did the expansions of the safety net close some of its holes? Both unemployment and participation in transfer programs increased during the recession, but take-up among those eligible for means-tested programs is far from complete (e.g. Currie 2006).
Analyses that attempt to answer these questions rely on survey data that is known to suffer from severe underreporting of welfare programs (e.g. Meyer, Mok, Sullivan 2009). Our previous work using administrative data on food stamp receipt in IL and MD linked to survey data found that false negative rates in major surveys ranged from 23% to 53%. We found strong evidence that misreporting is systematically related to observable characteristics. The extent of misreporting and its relation to observable characteristics is likely to lead to significant biases in studies that examine the determinants of participation in welfare programs, the distributional consequences of these programs, and other program effects.
For this project, we use administrative data on food stamps, TANF, General Assistance and housing subsidies linked to the Current Population Survey for New York State from 2007 to 2010. The accuracy of the administrative data allows us to re-examine the questions raised above regarding the effectiveness, targeting and take-up of these programs and examine how underreporting biases the conclusions we draw from survey data. The large sample allows us to draw more accurate conclusions about the determinants of misreporting. Contrary to previous studies, our data contains information on multiple programs. This is helpful to obtain a more complete assessment of the overall effect of the safety net on the income distribution, rather than the effect of a single program. It also enables us to distinguish between different causes of misreporting (e.g. stigma vs. confusing programs) and to examine multiple program participation.