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Modelling the behaviour of U.S. Inventories: A Cointegration-Euler Approach

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  • Iris Claus

Abstract

Cyclical contractions are often referred to as inventory cycles, in part because movements in inventories can amplify cyclical fluctuations in output. An unanticipated slowing in demand generally leads to an unintended buildup of inventories: only with a lag do firms adjust production and their actual holding of inventories relative to the desired level. A possible explanation for this accumulation is that the costs of adjusting inventory holdings outweigh the disequilibrium costs, i.e., the cost of temporarily deviating from the equilibrium level of inventories. In this paper, the relative importance of the disequilibrium costs to adjustment costs of inventories is evaluated. An estimate of the rate of inventory adjustment towards its long-run equilibrium level is provided in the United States by means of a linear-quadratic model with integrated processes. A limited-information approach allows the time-series properties of the data to be exploited and consistent estimates of the structural parameters of the Euler equation obtained. Evidence is provided that the actual level of U.S. inventories was generally above the target level during the past six recession periods and that inventories fell below their desired level following an economic downturn. Furthermore, the actual level of inventories appears to have been at desired levels between the 1960 and the 1969-70 recessions and since the last recession in 1990­1991--two periods of sustained economic growth. These findings support the view that inventory imbalances can amplify the business cycle. The empirical estimates also imply that adjustment costs are substantially more important than disequilibrium costs. The estimate of the speed of adjustment suggests that firms adjust their holdings of inventories slowly as it takes about a year for 95 per cent of the adjustment of the actual level to the target level to be completed.

Suggested Citation

  • Iris Claus, 1997. "Modelling the behaviour of U.S. Inventories: A Cointegration-Euler Approach," Staff Working Papers 97-19, Bank of Canada.
  • Handle: RePEc:bca:bocawp:97-19
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    References listed on IDEAS

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    1. Christiano, Lawrence J. & Eichenbaum, Martin, 1987. "Temporal aggregation and structural inference in macroeconomics," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 26(1), pages 63-130, January.
    2. Robert Amano, "undated". "Empirical Evidence on the Cost of Adjustment and Dynamic Labour Demand," Staff Working Papers 95-3, Bank of Canada.
    3. Donald S. Allen, 1995. "Changes in inventory management and the business cycle," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 17-26.
    4. Blinder, Alan S, 1986. "More on the Speed of Adjustment in Inventory Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(3), pages 355-365, August.
    5. Blanchard, Olivier J, 1983. "The Production and Inventory Behavior of the American Automobile Industry," Journal of Political Economy, University of Chicago Press, vol. 91(3), pages 365-400, June.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Eichenbaum, Martin S., 1984. "Rational expectations and the smoothing properties of inventories of finished goods," Journal of Monetary Economics, Elsevier, vol. 14(1), pages 71-96, July.
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    Cited by:

    1. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, March.
    2. Marwan Chacra & Maral Kichian, 2004. "A Forecasting Model for Inventory Investments in Canada," Staff Working Papers 04-39, Bank of Canada.

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    More about this item

    Keywords

    International topics;

    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

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