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

为什么1984年后时期的产出波动性比之前时期要低得多？这仅仅是好运、更好的货币政策，还是经济的结构性变化？了解产出波动性下降的根源不仅有助于预测未来的波动性模式，还有助于揭示货币政策和企业行为的潜在改善。这项拟议的研究试图通过对美国汽车业产量和销售波动性的变化进行案例研究，来揭示波动性下降的根源。美国汽车业是波动性下降的理想案例，因为它呈现出与总体数据相似但更具戏剧性的模式。卡恩、麦康奈尔和佩雷斯-基罗斯之前的工作提供了证据，证明生产和库存行为的变化是波动性下降的关键来源。在1984年后的时期，生产的差异比销售的差异下降得更多。此外，库存投资和销售的协方差已从正值(这增加了波动性)变为负值。这些事实是间接证据，表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，本研究探索了另一种假设，即这些观察到的变化主要源于销售过程的变化，而不是公司生产和库存计划的结构性变化。美国汽车业和许多其他行业一样，面临着非凸性成本和不稳定的生产利润率，这可能导致生产差异和销售差异之间存在非常非线性的关系。因此，销售过程的动态变化可能会导致生产计划的根本变化。该项目的第一部分通过模拟演示了销售动态和产出动态之间的复杂关系。采用类似于汽车装配厂面临的成本函数，将得到响应于不同销售过程的最优生产计划。该项目的第二部分收集和分析每周详细的汽车组装厂数据，以调查生产行为的变化中有多少是由于工厂层面的结构性变化与销售过程性质的变化造成的。由于销售过程可能会受到货币政策规则变化或公司定价行为的影响，因此确定生产行为的变化在多大程度上只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.