Abstract: Designing Effective Financial Tips to Guide Debt Repayment: Experimental Evidence from Tax Refund Recipients (Society for Social Work and Research 23rd Annual Conference - Ending Gender Based, Family and Community Violence)

Designing Effective Financial Tips to Guide Debt Repayment: Experimental Evidence from Tax Refund Recipients

Thursday, January 17, 2019: 3:15 PM
Union Square 1 Tower 3, 4th Floor (Hilton San Francisco)
* noted as presenting author
Sam Bufe, MS, Statistical Data Analyst, Washington University in Saint Louis, St. Louis, MO
Olga Kondratjeva, PhD, Postdoctoral Research Associate, Washington University in St. Louis, St. Louis, MO
Stephen Roll, PhD, Research Assistant Professor, Washington University in Saint Louis, St Louis, MO
Michal Grinstein-Weiss, PhD, Professor, Director, Envolve Center for Health Behavior Change, Associate Director, Center for Social Development, Washington University in Saint Louis, St. Louis, MO
Mathieu Despard, PhD, Assistant Professor, Washington University in Saint Louis, St. Louis, MO

Recent evidence indicates that traditional financial education has limited impacts on financial behaviors (Fernandes, Lynch, & Netemeyer, 2014). However, this research also finds that effective financial education is tailored to recipient needs and occurs at the point of an important financial decision. Building on this evidence and other recent work on the efficacy of providing rules of thumb around debt management (Theodos et al., 2016), we administered a randomized, controlled trial that provided financial tips for low- and moderate-income (LMI) tax filers after they learned their tax refund amount. For many LMI households, the tax refund is the household’s largest single check of the year, and the most common usage of the tax refund is to pay down existing debt (Grinstein-Weiss et al., 2015). How they choose to pay down that debt may impact the amount they pay in interest and fees and other indicators of financial health. In order to understand the potential for simple financial tips to impact how households use the refund to manage their debts, this experiment tests the salience and utility of four financial tips with strategies on using the refund to pay down existing debt.


Data for this paper come from a survey administered to low- and moderate-income households using TurboTax Freedom Edition in 2018. In addition to detailed questions on tax household demographic and financial characteristics, the survey also randomized respondents into a control group that received no financial tips, a treatment group that randomly saw one of four possible tips, and a treatment group in which respondents were asked to select which of the four financial tips was most relevant to their lives. Respondents in the treatment groups answered questions about their tip, including its usefulness, if they had ever used it in the past, and if they would commit to following it in the future. At the end of the survey, these respondents were tested on their recollection of the tip.


Preliminary findings showed notable differences across treatment groups in the usefulness of, willingness to commit to, and ability to recall the debt repayment tips. Those asked to choose their own tip were 14% more likely to commit to following their tip than people shown a randomly selected tip. People in the former group were also 9% more likely to report finding their tip useful and nearly 5% more likely to accurately recall their tip at the survey’s end. We also observe variation in the content of the financial tip and the perceived utility. Future analysis will incorporate a follow-up survey to assess the degree to which respondents used these tips to manage their debt.


This paper contributes to the emerging research on the use of tips and rules of thumb as tools to impact behaviors. As financial education moves away from traditional classes and towards well-timed, low-touch interventions, it is important to understand what interventions are most effective. This research presents guidance on how simple, message-based interventions can be optimized.