Measuring Noise in Inventory Models

38 Pages Posted: 17 Oct 2007

See all articles by Steven N. Durlauf

Steven N. Durlauf

University of Chicago; National Bureau of Economic Research (NBER)

Louis J. Maccini

Johns Hopkins University - Department of Economics

Date Written: October 1993

Abstract

This paper has two purposes. One is to assess different models of inventory behavior in terms of their ability to well approximate the realized data on inventories. We do this initially for the pure production smoothing model and then for a sequence of generalizations of the model. Our analysis both performs specification tests as well as measures the deviations of the data from each null model, which we refer to as model noise. This involves the introduction of a noise ratio which provides a metric for measuring the magnitude of the noise component of the data. A second purpose is to explore whether observed cost shocks, including in particular carefully measured series on raw materials prices, can be helpful in explaining inventory movements. We find that the basic production level smoothing model of inventories, augmented by buffer stock motives, observed cost shocks, properly measured, and to a lesser extent stockout avoidance motives, appears to well approximate monthly inventory data.

Suggested Citation

Durlauf, Steven N. and Maccini, Louis J., Measuring Noise in Inventory Models (October 1993). NBER Working Paper No. w4487. Available at SSRN: https://ssrn.com/abstract=480259

Steven N. Durlauf (Contact Author)

University of Chicago ( email )

1155 East 60th Street
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER)

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Louis J. Maccini

Johns Hopkins University - Department of Economics ( email )

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Baltimore, MD 21218-2685
United States
410-516-7601 (Phone)
410-516-7600 (Fax)

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