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Terminal conditions in forward-looking economic models

  • Richard Pierse

    (University of Surrey)

In this paper we show how the popular L-B-J algorithm for solving forward-looking economic models using Newton methods can be gen- eralised to allow for a block of terminal equations for variables that appear with a lead. The e¤ect of choosing di¤erent types of termi- nal condition is explored in a simple stochastic growth model using WinSolve, a general nonlinear model solution package.

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File URL: http://www.fahs.surrey.ac.uk/economics/discussion_papers/2006/DP10-06.pdf
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Paper provided by School of Economics, University of Surrey in its series School of Economics Discussion Papers with number 1006.

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Length: 12 pages
Date of creation: Mar 2006
Date of revision:
Handle: RePEc:sur:surrec:1006
Contact details of provider: Postal: Guildford, Surrey GU2 5XH
Phone: (01483) 259380
Fax: (01483) 259548
Web page: http://www.surrey.ac.uk/economics/
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  1. John B. Taylor & Harald Uhlig, 1990. "Solving Nonlinear Stochastic Growth Models: A Comparison of Alternative Solution Methods," NBER Working Papers 3117, National Bureau of Economic Research, Inc.
  2. Juillard, Michel, 1996. "Dynare : a program for the resolution and simulation of dynamic models with forward variables through the use of a relaxation algorithm," CEPREMAP Working Papers (Couverture Orange) 9602, CEPREMAP.
  3. Juillard, Michel & Laxton, Douglas & McAdam, Peter & Pioro, Hope, 1998. "An algorithm competition: First-order iterations versus Newton-based techniques," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1291-1318, August.
  4. Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(4), pages 711-734, May.
  5. Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models," NBER Technical Working Papers 0005, National Bureau of Economic Research, Inc.
  6. den Haan, Wouter J & Marcet, Albert, 1990. "Solving the Stochastic Growth Model by Parameterizing Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 31-34, January.
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