No Strings Attached: The Behavioral Effects of U.S. Unconditional Cash Transfer Programs

By Ioana Marinescu |

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Providing cash directly to individuals has often been met with criticism, suspicion, and fear: the thinking goes that people who need financial assistance are not to be trusted, as their financial position reflects a moral failing rather than a societal one. These objections to cash transfer programs are rooted more in myth than empirical evidence. As the debate about a universal basic income gains prominence, it is important to set the record straight about the behavioral effects of unconditional cash assistance.

In this evidence review, we explore how unconditional cash transfers affected the behavior of recipients in three major natural experiments. While the amounts dispersed and time periods were distinct in each experiment, each provided money without set conditions and without a means test. We synthesize data for the following outcomes: consumption; labor force participation (employment, hours worked, and earnings); education; health; and other social outcomes, such as marriage or fertility choices. Each of these programs shares different components of a universal basic income (UBI), a cash transfer that everyone within a geographic/political territory receives on a regular basis with no conditions on a long-term basis. By understanding the effects of these programs, we can generate answers to how an unconditional cash transfer program might affect recipients in the future

 

Ioana Marinescu is an assistant professor at the University of Chicago Harris School of Public Policy. She has broad interests in the areas of labor and public economics. What is the impact of public policy on labor markets? How can we understand the linkages between micro-level labor market dynamics and macroeconomic outcomes such as unemployment and economic growth? She is particularly interested in understanding matching and search in the labor market, and how matching mechanisms determine unemployment and productivity. She is currently working with "big data" from CareerBuilder.com to better understand employers' and job seekers' online search behavior.