Federal Reserve Bank of New York Staff Reports Durable Goods Inventories and the Great Moderation

This paper revisits the hypothesis that changes in inventory management were an important contributor to volatility reductions during the Great Moderation. It documents how changes in inventory behavior contributed to the stabilization of the U.S. economy within the durable goods sector, in particular, and develops a model of inventory behavior that is consistent with the key facts about volatility decline in that sector. The model is calibrated to evidence from survey data showing that lead times for materials orders in manufacturing shrank after the early 1980s. Simulations of the model show large reductions in the volatility of output growth and more modest reductions in the volatility of sales growth. In addition, the model addresses concerns raised by a number of researchers who criticize the inventory literature’s focus on finished goods inventories, given that stocks of works-in-process and materials are actually larger and more volatile that those of finished goods. The model adapts the stockout-avoidance concept to a production-to-order setting and shows that much of the intuition and results regarding production volatility still apply. Key words: Great Moderation, inventories, volatility Kahn: Federal Reserve Bank of New York and Stern School of Business, Economics Department, New York University (email: jkahn@stern.nyu.edu). The author thanks Meg McConnell and Steve Davis for beneficial comments, and Doug Elmendorf, Nick Bloom, and Valerie Ramey for comments on an earlier version of the paper. The views expressed in this paper are those of the author and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. The large reduction in the volatility of GDP and other economic aggregates since the early 1980s, now commonly referred to as the Great Moderation, has spawned a number of hypotheses about its cause. But there have been surprisingly few truly structural explanations as an alternative to the hypothesis that volatility just exogenously fell. The primary alternative to the good luck view is that monetary policy changed discretely in the early 1980s and stabilized both output and ination.1 As discussed in Davis and Kahn (2008), this theory has a number of weaknesses: First, given the importance of credibility and transparency in determining monetary policys impact on the economy, it is implausible that the results of a policy change could have been felt so rapidly as to bring about an immediate drop in volatility. Second, some have argued that the policy adopted in the 1980s was not fundamentally di¤erent from that of the 1950s and early 1960s, when GDP volatility was considerably higher than it was post-1983.2 In addition, structural econometric models of aggregate output and ination have typically found that monetary policy has most of its impact on ination volatility, and comparatively modest e¤ects on the volatility of GDP growth.3 Hence there is little scope in these models for policy changes to account quantitatively for the much of the reduction in real volatility especially if one compares the 1950s and 1960s to the post-1983 era. This paper revisits the hypothesis, rst conjectured in McConnell and Perez-Quiros (1999) and Blanchard and Simon (2001), that changes in inventory management were an important contributor to volatility reductions. The rst part of the paper documents the disproportionate statistical contribution of changes in inventory behavior to the stabilization of the U.S. economy, within the durable goods sector in particular. The remainder of the paper develops a model of inventory behavior that is consistent with the key facts about the volatility decline in that sector. The model is calibrated to evidence from survey data showing that lead times for materials orders in manufacturing shrank after the early 1980s. Simulations of the model show that it implies large reductions in the volatility of output growth, and more modest reductions in the volatility of sales growth. The model also addresses concerns raised by a number of researchers (e.g. Blinder and Maccini, 1991; Humphries et al., 2001) who criticize the inventory literatures focus on nished goods inventories, given that stocks of work-in-process and materials are actually larger and more volatile than those of nished goods. In addition, durable goods manufacturing in particular consists primarily of industries best characterized as production-to-order industries rather than production-to-stock (see Belsley, 1969). One contribution of the model, aside from its contribution to understanding the Great Moderation, is to adapt the stockout-avoidance concept (as in Kahn, 1987) to a production-to-order setting, and to show that much of the intuition and results regarding production volatility still apply. In particular, the model shows that the need to make 1See, for example, Clarida, Gali, and Gertler (2000). 2See Romer and Romer (2000) 3See, for example, Stock and Watson (2002); Ahmed et al. (2004).