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Hedging price volatility using fast transport

  • Hummels, David L.
  • Schaur, Georg

Purchasing goods from distant locations introduces a significant lag between when a product is shipped and when it arrives. These transit lags are trade barriers for firms facing volatile demand, who must place orders before knowing the resolution of demand uncertainty. We provide a model in which airplanes bring producers and consumers together in time. Fast transport allows firms to respond quickly to favorable demand realizations and to limit the risk of unprofitably large quantities during low demand periods. The model predicts that the likelihood and extent to which firms employ air shipments is increasing in the volatility of demand they face, decreasing in the air premium they must pay, and increasing in the contemporaneous realization of demand. We confirm all three conjectures using detailed US import data. Fast transport thus provides firms with a real option to smooth demand volatility on international markets, and we provide simple calculations of that option value. This enables us to identify how the option value relates to goods characteristics, and to changes in air transport premia associated with technological and policy change including the introduction of jet engines, and liberalization of trade in air services.

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Article provided by Elsevier in its journal Journal of International Economics.

Volume (Year): 82 (2010)
Issue (Month): 1 (September)
Pages: 15-25

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Handle: RePEc:eee:inecon:v:82:y:2010:i:1:p:15-25
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/505552

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  1. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2011. "Robust Inference With Multiway Clustering," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 238-249, April.
  2. Micco, Alejandro & Serebrisky, Tomas, 2006. "Competition regimes and air transport costs: The effects of open skies agreements," Journal of International Economics, Elsevier, vol. 70(1), pages 25-51, September.
  3. Joshua Aizenman, 2000. "Endogenous Pricing to Market and Financing Costs," NBER Working Papers 7914, National Bureau of Economic Research, Inc.
  4. Harrigan, James & Venables, Anthony J., 2006. "Timeliness and agglomeration," Journal of Urban Economics, Elsevier, vol. 59(2), pages 300-316, March.
  5. David Hummels, 2007. "Transportation Costs and International Trade in the Second Era of Globalization," Journal of Economic Perspectives, American Economic Association, vol. 21(3), pages 131-154, Summer.
  6. Jonah B. Gelbach & Doug Miller, 2009. "Robust Inference with Multi-way Clustering," Working Papers 99, University of California, Davis, Department of Economics.
  7. W. J. Baumol & H. D. Vinod, 1970. "An Inventory Theoretic Model of Freight Transport Demand," Management Science, INFORMS, vol. 16(7), pages 413-421, March.
  8. David L. Hummels & Georg Schaur, 2013. "Time as a Trade Barrier," American Economic Review, American Economic Association, vol. 103(7), pages 2935-59, December.
  9. Carolyn L. Evans & James Harrigan, 2005. "Distance, Time, and Specialization: Lean Retailing in General Equilibrium," American Economic Review, American Economic Association, vol. 95(1), pages 292-313, March.
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