NON-PECUNIARY ASPECTS OF THE RETIREMENT DECISION

拟议的研究将调查非金钱因素如何 可能会影响退休决定。重点关注的领域将是 照顾的责任和态度。现有文献记录了 财务激励对退休决策的影响(例如，养老金、 社会保障)；拟议研究的一个目标是为 (相对较新的)包含“非经济”因素的文学作品。这个 拟议的研究将延长退休、照看和意图 关于内生决策的文献。建议的另一个方面 研究将把预期和不确定性纳入退休模型。 通过改进数据来源和新的计量经济学，这些目标变得可行 技巧。本研究将从以下几个方面进行：1)考虑差异 在不同人口和性别的态度和照顾责任方面 分组，2)检查主观概率评估之间的关系 和实际结果，注意到个人的“总体”态度将 影响这些评估，3)调查照顾之间的内生性 和退休决策，4)修改动态的基本情况行为模型 退休，以纳入这些非金钱的影响，5)模拟 公共和公司政策变化对退休决策的影响。 分析中使用的主要数据集是HRA(HRS/AHEAD)调查。 HRA是分析的自然选择，因为它的大样本 处于退休年龄的个人。它还包含丰富的金融产品集合 在个人层面上的信息，支持影响的模型 为控制财务影响而采取的非金钱激励 在以前的研究中显示是相当重要的。该数据集还包含一个 一组可用于预测结果的主观概率问题 在随后的几波调查中。

The proposed research will investigate how non-pecuniary factors potentially influence the retirement decision. The key areas of focus will be caregiving responsibilities and attitudes. Existing literature documents the effects of financial incentives on the retirement decision (e.g., pensions, Social Security); one goal of the proposed research is to contribute to the (relatively new) literature that incorporates "non-economic" factors. The proposed research will extend the retirement, caregiving, and intentions literatures of endogenous decision making. Another facet of the proposed research will incorporate expectations and uncertainty into retirement models. These goals are made feasible by improved data sources and new econometric techniques. The research will proceed as follows: 1) consider the differences in attitudes and caregiving responsibilities across demographic and gender groups, 2) examine the relationship between subjective probability assessments and actual outcomes, noting that the "overall" attitude of the individual will affect these assessments, 3) investigate the endogeneity between the caregiving and retirement decisions, 4) modify a dynamic "base case" behavioral model of retirement to incorporate these non-pecuniary influences, 5) simulate the effects on the retirement decision of changes in public and corporate policy. The principal dataset to be used in the analysis is the HRA (HRS/AHEAD) survey. The HRA is a natural choice for the analysis because of its large sample of retirement-age individuals. It also contains a rich collection of financial information at the individual level, enabling models of the effects of non-pecuniary incentives to control for the financial effects which have been shown in previous studies to be quite important. The dataset also contains a set of subjective probability questions which can be used to predict outcomes in subsequent waves of the surveys.