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Shocking Escapes

  • Bruce McGough

Sargent's (1999) model of inflation is amended to include real oil prices and used to study the impact of exogenous supply shocks on the inflation time-series. We analyse whether these shocks can trigger escape-like episodes. We consider unobserved permanent shocks to the natural rate of unemployment and observed permanent shocks to the mean real oil price. Favourable shocks to unemployment decrease the time to first escape; that is, escapes tend to occur much sooner in the presence of these shocks. Shocks to the mean real oil price cause the economy to move quickly to its new equilibrium. Copyright 2006 Royal Economic Society.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2003 with number 294.

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Date of creation: 01 Aug 2003
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Handle: RePEc:sce:scecf3:294
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  1. Cho, In-Koo & Sargent, Thomas J., 2000. "Escaping Nash inflation," Working Paper Series 0023, European Central Bank.
  2. Thomas Sargent & Noah Williams & Tao Zha, 2006. "The Conquest of South American Inflation," NBER Working Papers 12606, National Bureau of Economic Research, Inc.
  3. Kydland, Finn E & Prescott, Edward C, 1977. "Rules Rather Than Discretion: The Inconsistency of Optimal Plans," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 473-91, June.
  4. Noah Williams, 2003. "Small Noise Asymptotics for a Stochastic Growth Model," NBER Working Papers 10194, National Bureau of Economic Research, Inc.
  5. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
  6. Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996. "Mechanics of forming and estimating dynamic linear economies," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 4, pages 171-252 Elsevier.
  7. Song Chen, 2000. "Probability Density Function Estimation Using Gamma Kernels," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 471-480, September.
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