Models and Measurement: (S,s) Inventories and Investment Under Adjustment Costs

这项建议包括两个项目，探讨调整费用与投资之间的关系。每一个都使用新的模型和方法来研究对理解经济如何随时间变化至关重要的问题。第一个项目是与费城联邦储备银行的奥比克·汗联合进行的，考虑了这样一个问题：“库存会加剧商业周期吗？“它研究了内生广义（S，S）库存投资的总体影响，重点是在一个动态随机一般均衡模型与资本积累的中间产品库存。首先，模型的能力，重现观察到的库存投资，最终销售和生产之间的周期性关系进行评估。接下来，研究这种库存对整个商业周期的影响。 第二个项目考虑的是，“关于公司贴现率的不同假设如何影响资本调整成本的结构性估计？“它探讨了研究人员估计调整成本和解释投资波动的波动性和持续性的能力，这些波动性和持续性是在不同的假设下进行的，这些假设是关于公司利润受到冲击的过程与跨期利润估值的过程之间的关系。这两个项目都涉及到工厂之间相当大的异质性。由于决策规则通过价格的标准反馈，这使得均衡价格的确定变得困难。 均衡价格的解决，允许代理人的预测未来的状态，使用一个子集的总状态向量。 企业的决策规则，这是高度非线性的，使用多元样条插值来解决。智力优点：库存的话题一直是突出的讨论的商业周期，但它在很大程度上被忽视了现代商业周期理论。大多数宏观经济库存研究集中在线性二次代表性企业模型，是部分均衡的设计和普遍令人失望的经验预测。相比之下，库存的主要微观经济模型，即最初由Scarf（1960）解决的（S，s）模型，几乎没有受到宏观经济的关注。更广泛的影响：这项研究可能会大大改变政策制定者对库存在总体波动中的作用的理解。 例如，初步结果表明，最近在库存管理方面取得的进展，减少了平均库存的规模，可能是商业周期受到抑制的原因。当这些库存来自非凸订货或交货成本时，这种摩擦的减少导致平均库存-销售比率的降低和库存投资波动的抑制，实际上可能会增加GDP的总体波动，因为库存积累的减少伴随着最终销售的更大波动。

This proposal includes two projects exploring the relation between adjustment costs and investment. Each uses new models and methods to examine questions central to understanding how the economy changes over time. The first project, joint with Aubhik Khan of the Federal Reserve Bank of Philadelphia, considers the question: "Do inventories exacerbate the business cycle?" It examines the aggregate implications of endogenous generalized (S,s) inventory investment, focusing on inventories of intermediate goods in a dynamic stochastic general equilibrium model with capital accumulation. First, the model's ability to reproduce observed cyclical relations between inventory investment, final sales and production is assessed. Next, the effects of such inventories for the overall business cycle are studied. The second project considers, "How do differing assumptions about firms' discount rates influence structural estimates of capital adjustment costs?" It explores a researcher's ability to estimate adjustment costs and explain the volatility and persistence of investment fluctuations under varying assumptions about the relation between the process governing shocks to firms' profits and that governing their intertemporal profit valuations. Both projects involve considerable heterogeneity across plants. This makes the determination of equilibrium prices difficult, due to the standard feedback of decision rules through prices. Equilibrium prices are solved by allowing agents' to forecast the future state using a subset of the aggregate state vector. Firms' decision rules, which are highly nonlinear, are solved using multivariate spline interpolation.Intellectual Merits: The topic of inventories has long been prominent in discussions of the business cycle, yet it has been largely ignored by modern business cycle theory. Most macroeconomic inventory research has focused on linear quadratic representative firm models that are partial equilibrium by design and generally disappointing in their empirical predictions. By contrast, the leading microeconomic model of inventories, the (S,s) model originally solved by Scarf (1960), has received almost no macroeconomic attention. The project corrects this important omission.Broader Impacts: The research may substantially alter policymakers' understanding of the role of inventories in aggregate fluctuations. For example, preliminary results suggest that recent advances in inventory management, in reducing the size of average stocks, may be responsible for dampened business cycles. When these stocks arise from nonconvex ordering or delivery costs, a reduction in such frictions that leads to reduced average inventory-sales ratios and dampened fluctuations in inventory investment may actually raise the overall volatility in GDP, because reduced inventory accumulation is accompanied by larger fluctuations in final sales.