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A Toolbox for the Numerical Study of Linear Dynamic Rational Expectations Models

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  • Oviedo, P. Marcelo

Abstract

By simplifying the computational tasks and by providing step-by-step explanations of the procedures required to study a linear dynamic rational expectations (LDRE) model, this paper and the accompanying ``LDRE Toolbox" of Matalb functions guide a researcher with almost no experience in computational work to resolve and study his own model. After coding the model following specific guidelines, a single function call is all that is needed to log-linearize the model; simulate it under exogenous sequences of shocks; compute sample and population moment conditions; and obtain impulse-response functions. Three classical models in the Real-Business-Cycles literature are solved and studied throughout to give detailed examples of the steps involved in solving and studying LDRE models using the LDRE Toolbox. Namely, the economies in Brock and Mirman (Optimal Growth and Uncertainty: the Discounted Case, Journal of Economic Theory, 4(3): 479-513; 1972); King, Plosser, and Rebelo (Production, Growth and Business Cycles I: The Basic Neoclassical Model, Journal of Monetary Economics 21: 195-232; 1988); and Mendoza (Real Business Cycles in a Small Open Economy, American Economic Review 81(4): 797-818; 1991).

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Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12235.

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Date of creation: 26 Jan 2005
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Handle: RePEc:isu:genres:12235

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  1. Söderlind, Paul, 1998. "Solution and Estimation of RE Macromodels with Optimal Policy," Working Paper Series in Economics and Finance 256, Stockholm School of Economics.
  2. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, Econometric Society, vol. 50(6), pages 1345-70, November.
  3. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
  4. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 91(1), pages 39-69, February.
  5. Robert J. Barro & Paul Romer, 1993. "Economic Growth," NBER Books, National Bureau of Economic Research, Inc, number barr93-1, January.
    • Robert J. Barro & Paul M. Romer, 1991. "Economic Growth," NBER Books, National Bureau of Economic Research, Inc, number barr91-1, January.
  6. Schmitt-Grohe, Stephanie & Uribe, Martin, 2003. "Closing small open economy models," Journal of International Economics, Elsevier, vol. 61(1), pages 163-185, October.
  7. Epstein, Larry G., 1983. "Stationary cardinal utility and optimal growth under uncertainty," Journal of Economic Theory, Elsevier, vol. 31(1), pages 133-152, October.
  8. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  9. Danthine, Jean-Pierre & Donaldson, John B. & Mehra, Rajnish, 1989. "On some computational aspects of equilibrium business cycle theory," Journal of Economic Dynamics and Control, Elsevier, vol. 13(3), pages 449-470, July.
  10. Mendoza, Enrique G, 1991. "Real Business Cycles in a Small Open Economy," American Economic Review, American Economic Association, vol. 81(4), pages 797-818, September.
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Cited by:
  1. Echeverria Garaigorta, Paulina Elisa & Iza Padilla, María Amaya, 2011. "Business cycles in a small open economy: The case of Hong Kong," DFAEII Working Papers 2011-07, University of the Basque Country - Department of Foundations of Economic Analysis II.

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