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Personalized Information as a Tool to Improve Pension Savings: Results from a Randomized Control Trial in Chile

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  • Olga Fuentes
  • Jeanne Lafortune
  • Julio Riutort
  • José Tessada
  • Félix Villatoro

Abstract

Forecasting of the outcome of saving for retirement is challenging, particularly for individuals who have limited financial literacy. We explore how reducing that barrier by offering personalized information affects long-term savings. To this end, we randomly offered personalized information or general information within the context of individual retirement accounts in Chile. Personalized information increased voluntary pension savings. Heterogeneity analysis suggests that the updating of priors by information recipients played an important role. However, despite the significant short-term response to the intervention, its temporary nature and limited magnitude are not enough to meaningfully alter the annuity payment that would be obtained from the savings stock.

Suggested Citation

  • Olga Fuentes & Jeanne Lafortune & Julio Riutort & José Tessada & Félix Villatoro, 2024. "Personalized Information as a Tool to Improve Pension Savings: Results from a Randomized Control Trial in Chile," Economic Development and Cultural Change, University of Chicago Press, vol. 72(2), pages 725-770.
    • Handle: RePEc:ucp:ecdecc:doi:10.1086/720718
    DOI: 10.1086/720718
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    Cited by:

    1. Damian Pierri & Enrique Kawamura, 2022. "Life cycle, financial frictions and informal labor markets: the case of Chile," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 93-120, December.
    2. Olckers, Matthew, 2021. "On track for retirement?," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 76-88.
    3. Azevedo, Viviane & Lafortune, Jeanne & Olarte, Liliana & Tessada, José, 2024. "Personalizing or reminding? How to better incentivize savings among underbanked individuals," Journal of Economic Behavior & Organization, Elsevier, vol. 222(C), pages 25-63.
    4. Zhu, Alex Yue Feng, 2024. "Optimizing financial decision-making for emerging adults: A compact Python-based personalized financial projection approach," Technology in Society, Elsevier, vol. 77(C).

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