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

Author

Listed:
  • Olga Fuentes
  • Jeanne Lafortune
  • Julio Riutort
  • José Tessada
  • Félix Villatoro
Abstract
We randomly offer to workers in Chile personalized versus generalized information about their pension savings and forecasted pension income. Personalized information increased the probability and amounts of voluntary contributions after one year without crowding-out other forms of savings. Personalization appears to be very important: individuals who overestimated their pension at the time of the intervention saved more. Thus, a person’s inability to understand how the pension system affects them may partially explain low pension savings. Despite the significant response to the intervention, its temporary nature and size suggest that information should be combined with other elements to increase its efficiency.

Suggested Citation

  • Olga Fuentes & Jeanne Lafortune & Julio Riutort & José Tessada & Félix Villatoro, 2017. "Personalized Information as a Tool to Improve Pension Savings: Results from a Randomized Control Trial in Chile," Documentos de Trabajo 483, Instituto de Economia. Pontificia Universidad Católica de Chile..
    • Handle: RePEc:ioe:doctra:483
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    File URL: https://www.economia.uc.cl/docs/doctra/dt-483.pdf
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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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