New Evidence on Tax and Transfer Policies from the Universe of U.S. Tax Records

Harvard University, Cambridge MA

Investigators

Abstract

A central challenge in conducting research on policy questions in economics is a lack of high quality data. Survey datasets are limited by small sample sizes, often do not follow individuals over time, and suffer from poorly measured variables. Working in collaboration with the Internal Revenue Service (IRS) over the past two years, the PIs--comprising Raj Chetty, John Friedman, and Emmanuel Saez--recently obtained access to the universe of individual tax records of the United States. This is the first time that researchers outside the government have worked with these data, which provide an unprecedented resource for academic and policy research. The dataset spans 1996-2008 and contains 1.7 billion tax records, including all forms (e.g., 1040?s, W-2?s, 1099?s, etc). In addition to earnings, the data can be used to study housing purchases, investment decisions, business startups, college education choices of children, inter-generational income mobility, and many other outcomes. Thus, these data provide a wealth of information to study not only questions in the economics of taxation but also more broadly in public finance, labor economics, economics of education, finance, and macroeconomics. This project has two objectives. The first is to prepare these data for academic and policy research. The data are stored in many different files and must be cleaned and structured for use in research projects. Key steps include: (1) addressing problems of missing tax forms and outliers, (2) merging age and death information from other government databases, (3) creating individual employer-employee matched wage earnings histories by linking W-2?s to 1040?s, (4) linking parents to children, (5) identifying college attendance, and (6) developing clear documentation of the merged dataset for future researchers. These first steps are highly labor intensive. The second objective is to use these data to research three specific questions relevant to the effects of government policy: (1) How do income shocks affect individuals? labor and investment behavior? The PIs will investigate both traditional labor supply income effects and also the impact of income grants on entrepreneurship, homeownership, the decision to send children to college, and intergenerational income mobility. (2) What are the long-term effects of income support programs such as the Earned Income Tax Credit on earnings, children's education, and income mobility? (3) How do local economic shocks such as government stimulus or plant closures propagate through communities through general equilibrium and spillover effects? The analysis will suggest new theories and provide much more precise estimates of key parameters such as local fiscal multipliers and income elasticities. The intellectual merit of this project is twofold. First, it will pave the way for all academic researchers to make use of the IRS data to study a wide array of policy and academic questions. The IRS views this project as a demonstration of how its data can be used for academic research, and a successful demonstration may lead to wider data access through a mechanism analogous to Census data centers. Second, the PIs will contribute to knowledge about long-run and general equilibrium impacts of income support and stimulus policies, which are difficult to study using existing data. The broader impact of this project is to help policymakers design government policies that are more likely to maximize welfare. For instance, these results will help policymakers understand the long-term consequences of the Earned Income Tax Credit on the poor. Does this policy improve the income mobility of the poor or instead foster a cycle of dependence on government support? More generally, the basic investment of preparing these data for research will allow policy makers to obtain much more precise answers to a broad range of policy questions in the years to come.