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Cyclical Behavior of Inventories and Growth Projections Recent Evidence From Europe and the United States

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  • Alexander W. Hoffmaister
  • Jens R. Clausen

Abstract

In the United States and a few European countries, inventory behavior is mainly the outcome of demand shocks: a standard buffer-stock model best characterizes these economies. But most European countries are described by a modified buffer-stock model where supply shocks dominate. In contrast to the United States, inventories boost growth with a one-year lag in Europe. Moreover, inventories provide limited information to improve growth forecasts particularly when a modified buffer-stock model characterizes inventory behavior.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 10/212.

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Length: 38
Date of creation: 01 Sep 2010
Date of revision:
Handle: RePEc:imf:imfwpa:10/212

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Keywords: Forecasting models; Manufacturing sector; Production growth; inventories; inventory; forecasting; correlation; statistics; mean square; predictions; statistic; prediction; inventory management; correlations; absolute error; equation; polynomial; explanatory power; standard error; time series; outlier; statistical significance; covariance; dummy variable; integral; cross-country variation; significance levels; empirical framework;

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  1. Aubhik Khan & Julia Thomas, 2003. "Inventories and the Business Cycle: An Equilibrium Analysis of (S,s) Policies," NBER Working Papers 10078, National Bureau of Economic Research, Inc.
  2. Oleksiy Kryvtsov & Virgiliu Midrigan, 2013. "Inventories, Markups, and Real Rigidities in Menu Cost Models," Review of Economic Studies, Oxford University Press, vol. 80(1), pages 249-276.
  3. Tatiana Cesaroni & Louis Maccini & Marco Malgarini, 2009. "Business cycle volatility and inventories behavior:new evidence for the Euro Area," ISAE Working Papers 108, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
  4. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
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