Automatic Adjustment Mechanisms (AAM) are legal instruments that help social security systems respond to demographic and economic changes. In Brazil, the Social Security Factor (SSF) was introduced in the late 1990s as an AAM to link retirement benefits to life expectancy at the retirement age, with the hope of promoting contributory justice and discouraging early retirement. Recent research has highlighted the limitations of right-censored life tables, such as those used in Brazil. It has recommended using the gamma-Gompertz-Makeham (GGM) model to estimate adult and old-age mortality. This study investigated the impact of right-censoring on the SSF by comparing the official SSF and other social security metrics with a counterfactual scenario computed based on fitted GGM models. The results indicate that from 2004 to 2012, official life tables may have negatively impacted retirees' income, particularly for those who delayed their retirement. Furthermore, the GGM-fitted models' life expectancies had more stable paths over time, which could have helped with long-term planning. This study's findings are significant for policymakers as they highlight the importance of using appropriate mortality metrics in AAMs to ensure accurate retirement benefit payments. They also underscore the need to consider the potential impacts of seemingly innocuous hypotheses on public action outcomes. Overall, this study provides valuable insights for public planners and policymakers looking to enhance the effectiveness and fairness of social security systems.

翻译：自动调整机制（AAM）是帮助社会保障体系应对人口与经济变化的法律工具。巴西于20世纪90年代末引入社保因子（SSF）作为自动调整机制，将退休待遇与退休年龄预期寿命挂钩，旨在促进缴费公平并抑制提前退休。近期研究指出了右删失生命表（如巴西使用的版本）的局限性，建议采用gamma-Gompertz-Makeham（GGM）模型估算成年及老年死亡率。本研究通过对比官方社保因子及其他社保指标与基于拟合GGM模型计算的反事实情景，探讨了右删失对社保因子的影响。结果表明，2004年至2012年间，官方生命表可能对退休人员收入产生负面影响，尤其是对延迟退休者。此外，基于GGM拟合模型的预期寿命随时间呈现更稳定的路径，这有助于长期规划。本研究结论对政策制定者具有重要启示：在自动调整机制中采用恰当的死亡率指标对确保退休待遇精准支付至关重要，同时需警惕看似无害的假设对公共政策结果可能产生的潜在影响。总体而言，本研究为致力于提升社保体系效能与公平性的公共规划者及政策制定者提供了宝贵见解。