Assessing the impact of financial education programs: A quantitative model |
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| Institution: | 1. The George Washington University School of Business & NBER, United States;2. HEC Montreal, CIRANO and NBER, Canada;3. Wharton School, The University of Pennsylvania & NBER, United States;1. University of North Carolina at Greensboro, United States, and IZA Institute of LaborEconomics;2. University of Strathclyde, Scotland, United Kingdom;1. Ghent University;2. KU Leuven;3. GLO;4. Research Foundation - Flanders;5. University of Antwerp;6. Université catholique de Louvain;7. IZA;8. IMISCOE;1. University of Lille, CNRS, UMR 9221 – Lem – Lille Économie Management, Lille F-59000, France;2. Statistical Department of the French Ministry of Labor (DARES), France;1. Division of Social Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;2. Institute for Economic and Social Research, Jinan University, Guangzhou, China |
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| Abstract: | Prior studies disagree regarding the effectiveness of financial education programs, especially those offered in the workplace. To explain such measurement differences in evaluation and outcomes, we employ a stochastic life cycle model with endogenous financial knowledge accumulation and investigate how financial education programs optimally shape key economic outcomes. This approach permits us to measure how such programs shape wealth accumulation, financial knowledge, and participation in sophisticated assets (e.g. stocks) across heterogeneous consumers. We apply conventional program evaluation econometric techniques to simulated data, distinguishing selection and treatment effects. We show that the more effective programs provide follow-up in order to sustain the knowledge acquired by employees via the program; in such an instance, financial education delivered to employees around the age of 40 can raise savings at retirement by close to 10%. By contrast, one-time education programs do produce short-term but few long-term effects. We also measure how accounting for selection affects estimates of program effectiveness for those who participate. Comparisons of participants and non-participants can be misleading, even using a difference-in-difference strategy when the common-trend assumption is unlikely to hold. Random program assignment is needed to evaluate program effects on those who participate. |
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