Inventories, Fluctuations and Business Cycles. Working paper #4

The paper looks at the role of inventories in U.S. business cycles and fluctuations. It concentrates upon the goods producing sector and constructs a model that features both input and output inventories. A range of shocks are present in the model, including sales, technology and inventory cost shocks. It is found that the presence of inventories does not change the average business cycle characteristics in the U.S. very much. The model is also used to examine whether new techniques for inventory control might have been an important contributing factor to the decline in the volatility of US GDP growth. It is found that these would have had little impact upon the level of volatility.

Measuring Noise in Inventory Models

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.

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed