Macroeconomic Implications of Cross-Sectional Variation

这个项目的议程是围绕两个主要想法组织的。首先，与非交易资产相关的风险对个人的选择有重要影响，因此对个人如何评估与交易资产相关的风险具有重要影响。其次，这些未交易的风险具有重要的生命周期成分。到目前为止，在大多数调查人员的工作中，“非交易资产”一直是人力资本：个人未来将获得的所有劳动收入的价值。许多正在进行的工作涉及扩大我们所指的非交易资产，将住房和耐用消费品包括在内。人力资本是不可交易的，因为个人很难以未来的工资收入为抵押借款，同样重要的是，他们很难确保这些收入的不确定性。人力资本有一个基本的生命周期组成部分，因为年轻人比老年人拥有更多的人力资本，因此面临与人力资本相关的更多风险。研究人员的工作表明，这些因素对经济学中的许多悬而未决的问题都可能是重要的。例如，他们在资产定价模型方面的研究表明，人力资本风险的生命周期模式可以抑制总风险的代际分担，从而有助于解决股权溢价之谜。他们关于消费不平等的研究利用这种生命周期模式来推导出对收入、消费和劳动力供应的横截面差异如何相互关联的强烈限制。该提案描述了类似的新工作，包括纳入特定群体的风险和这些风险的代际分担、社会保障发挥的相关作用以及婴儿潮等人口冲击的影响。与人力资本一样，个人持有的大多数非人力资本要么是不可交易的，要么很难在不产生重大成本的情况下进行交易。例如，住房约占总财富的四分之一，在私人拥有的财富中所占比例要大得多。调整住房存量的成本是巨大的。与人力资本一样，住房资本也有一个重要的生命周期组成部分：年轻家庭将更多的财富作为房地产持有，而不是年长的家庭。与人力资本不同，与住房相关的风险要有形得多，也更容易衡量。研究人员开发了一个模型，将住房纳入现有框架，并探索其影响。在之前的工作中，他们强调了特殊性冲击，他们将房地产财富的冲击建模为本质上的总和，但在整个人口中并不均匀分布。他们认为，这与生命周期问题一起，对资产定价、投资组合选择和各种政策问题具有重要影响。沿着类似的思路，我们讨论了耐用品的纳入(比住房定义更广泛)，并提供了一些来自消费者支出调查的初步经验证据。该项目的一个重要部分是，并将继续纳入关于劳动力市场活动、消费和财富的大规模小组数据集。这项工作的显著特点是与年龄有关的限制--这是由我们的生命周期模型驱动的。例如，它们表明，通过对任何面板数据集中每个年龄段的人经历的特定宏观经济历史进行条件调整，人们可以发现许多关于特殊冲击和聚合冲击如何相互作用的问题。他们还表明，消费横截面方差中年龄相关的变化可以揭示出支配劳动收入的随机过程的许多信息。

This project's agenda is organized around two main ideas. First, that the risks associated with non-traded assets have an important impact on individual choices and, therefore on how individuals value the risks associated with traded assets. Second, that these non-traded risks have an important life-cycle component to them. In most of the investigators' work-to-date the 'non-traded asset' has been human capital: the value of all future labor income that an individual will receive. Much of the ongoing work involves expanding what we mean by non-traded assets to include housing and consumer durables. Human capital is non-tradable in the sense that it is difficult for individuals to borrow against future wage income and, just as importantly, to insure them against the uncertainty of what this income will be. Human capital has a fundamental life cycle component in that young people have more of it than old people and, therefore, face more of the risks associated with it. The investigators' work has shown that these factors can be important for many outstanding issues in economics. For instance, their work on asset pricing models shows that the life-cycle pattern in human-capital risk can inhibit the intergenerational sharing of aggregate risks and thereby helps to resolve the equity premium puzzle. Their work on consumption inequality exploits this life-cycle pattern to deduce strong restrictions on how the cross-sectional variance in income, consumption, and labor supply are related to one another. This proposal describes new work along similar lines, including the incorporation of cohort-specific risks and the intergenerational sharing of these risks, the associated role played by social security, and the impact of demographic shocks such as the Baby Boom. Like human capital, most non-human capital held by individuals is either non-tradable or is difficult to trade without incurring substantial costs. Housing, for instance, accounts for roughly one fourth of aggregate wealth and a much larger fraction of privately-held wealth. The costs of adjusting one's housing stock are large. Also like human capital, housing capital also has an important life-cycle component: young households hold much more of their wealth as real estate than older households. Unlike human capital the risks associated with housing are much more tangible and easily measured. The investigators develop a model, which incorporates housing into the existing framework, and they explore the implications. Where the previous work has emphasized idiosyncratic shocks, they model shocks to housing wealth as aggregate in nature, but non-uniformly distributed across the population. They argue that this, in conjunction with life-cycle issues, has important implications for asset pricing, portfolio choice, and various policy questions. Along similar lines, we discuss the incorporation of durable goods (more broadly defined than housing), and present some preliminary empirical evidence from the Consumer Expenditure Survey. An important part of this project has been, and will continue to be, the incorporation of large- scale panel datasets on labor market activity, consumption and wealth. The distinguishing feature of this work is restrictions -motivated by our life-cycle models - that are related to age. They show, for instance, that one can uncover much about how idiosyncratic and aggregate shocks interact by conditioning on the particular macroeconomic history experienced by each age-cohort in any panel dataset. They also show that age-dependent changes in the cross-sectional variance of consumption can reveal a great deal about the stochastic process that governs labor earnings.