Understanding the Decline in U.S. Output Volatility: An Analysis of the Automobile Industry

为什么1984年后的产出波动比之前的时期要低得多？仅仅是因为运气好、货币政策好转，还是经济结构发生了变化？了解产出波动性下降的根源不仅有助于预测未来的波动模式，还有助于阐明货币政策和企业行为的潜在改善。拟议的研究旨在通过对美国汽车行业产量和销售波动性变化的案例研究，揭示波动性下降的原因。美国汽车行业是波动性下降的理想研究案例，因为它的模式与总体数据相似，但比总体数据更引人注目。Kahn、McConnell和Perez-Quiros之前的研究表明，生产和库存行为的变化是波动性下降的关键来源。在1984年之后的时期，生产差异的下降幅度远远大于销售差异。此外，库存投资和销售的协方差从正（这增加了波动性）变为负。这些事实提供了间接证据，证明波动性下降的关键是生产和库存管理的结构性变化。更具体地说，本研究探讨了另一种假设，即这些观察到的变化主要源于销售过程的变化，而不是企业生产和库存安排的结构性变化。美国汽车工业和许多其他行业一样，面临着非凸成本和不稳定的生产利润，这可能导致生产和销售之间的非线性关系。因此，销售过程的动态变化可能导致生产计划的根本变化。项目的第一部分使用模拟演示了销售动态和输出动态之间的复杂关系。采用与汽车装配厂所面临的成本函数类似的成本函数，将推导出响应各种销售过程的最优生产计划。该项目的第二部分收集和分析详细的每周汽车装配厂数据，以调查生产行为的变化在多大程度上是由于工厂层面的结构变化和销售过程性质的变化。由于销售过程可能受到货币政策规则变化或公司定价行为的影响，确定生产行为变化中有多少仅仅是对销售动态变化的反应，是追踪波动性下降来源的关键。

Why has output volatility in the post-1984 period been so much lower than in earlier periods? Is it just good luck, better monetary policy, or structural change in the economy? Understanding the source the decline in output volatility not only helps forecast future volatility patterns, but also sheds light on potential improvements in monetary policy and firm behavior. The proposed research seeks to shed light on the source of the decline in volatility by conducting a case study of changes in output and sales volatility in the U.S. automobile industry. The U.S. automobile industry represents an ideal case study of the decline in volatility because it exhibits patterns similar to, but more dramatic than, the aggregate data. Previous work by Kahn, McConnell and Perez-Quiros presents evidence that changes in production and inventory behavior are a key source of the decline in volatility. In the post-1984 period, the variance of production fell much more than the variance of sales. Furthermore, the covariance of inventory investment and sales has changed from being positive (which adds to volatility) to being negative. These facts represent circumstantial evidence that the key to the decline in volatility is structural change in production and inventory management. More specificially, this research explores the alternative hypothesis that these observed changes stem mostly from changes in the sales process rather than structural changes in firms' production and inventory scheduling. The U.S. automobile industry, as well as many other industries, face nonconvex costs and lumpy production margins that can lead to a very nonlinear relationship between the variance of production and the variance of sales. Thus, a change in the dynamics of the sales process can lead to radical changes in the way production is scheduled. The first part of the project demonstrates the complex relationship between sales dynamics and output dynamics using simulations. Employing a cost function similar to the one faced by automobile assembly plants, optimal production schedules in response to various sales processes will be derived. The second part of the project gathers and analyzes detailed weekly automobile assembly plant data to investigate how much of the change in production behavior is due to structural changes at the plant level versus changes in the nature of the sales process. Since the sales process can be affected by changes in monetary policy rules or by firms' pricing behavior, identifying how much of the change in production behavior is simply a response to changes in the dynamics of sales is key to tracking the source of the decline in volatility.