Precautionary Saving in a Dynamic Model of Consumption and Labor Supply

大多数经济学家认为， 美国在过去二十年中的表现令人担忧。 但 关于美国储蓄率如此之低的原因，存在相互矛盾的证据。 这些证据大部分都是基于完美条件下的储蓄模型 确定性，因为现实的跨期储蓄模型， 不确定性是难以解决的。 本项目的贡献来自于开发软件 在超级计算机上进行矢量计算， 跨期模型的计算和编程要求 消费和劳动力供给的不确定性来源重叠 以及模型中实际上大量的周期。 数值 方法将被用来估计预防性储蓄的规模， 即对未来事件的不确定性导致的储蓄。 预防性储蓄的规模在很大程度上取决于 现有的私人和公共保险计划 减少个人的不确定性。 现有和潜在的未来 政府保险计划，如社会保障，失业 医疗保险、医疗补助、医疗保险和灾难性医疗保险， 产生高度非线性或扭曲的预算约束， 无法在标准分析框架中建模。 数值 该项目开发的解决方案技术将允许影响 这些非线性的保险和税收计划 准确地

Most economists agree that the decline in the savings rate in the United States over the past two decades is a cause for concern. But there is conflicting evidence as to the reasons U.S. saving are so low. Much of this evidence is based on models of savings under perfect certainty because realistic intertemporal models of saving under uncertainty are intractable. The contribution of this project comes from developing software for vector calculations on a supercomputer that meet the substantial computing and programming requirements of an intertemporal model of consumption and labor supply with overlapping sources of uncertainty and a realistically large number of periods in the model. Numerical methods will be used to estimate the magnitude of precautionary saving, that is, saving caused by uncertainty about future events. The magnitude of precautionary saving depends in an important way on the extent that existing private and public insurance programs reduce individual uncertainty. Existing and potential future government insurance programs, such as Social Security, unemployment insurance, Medicaid, Medicare, and catastrophic health insurance, create highly nonlinear or kinked budget constraints which are impossible to model in the standard analytic framework. The numerical solution techniques developed by this project will permit the effects of these nonlinear insurance and tax programs to be measured accurately.