Abstract
While the transmission mechanism of inventory behavior in the business cycle has been studied, less effort has been devoted to applied forecasting of inventory change. Inventory fluctuations have accounted for a sizable portion of the changes in U.S. GDP during recessions over the past fifty years. In this paper, we report on out-of-sample forecasts of manufacturing and trade inventories generated by regression and neural network methodology. Our forecasting model is Metzlerian in approach, in that the divergence between actual and targeted sales is hypothesized as the primary cause of inventory imbalance. Our forecasts also rely on the slow adjustment of inventory investment to sales surprises. However, the likely presence of money illusion is a caveat to users, and we address several distortions it introduces to inventory management measures.
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