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Algorithms for solving dynamic models with occasionally binding constraints

  • Lawrence J. Christiano
  • Jonas D.M. Fisher

We describe and compare several algorithms for approximating the solution to a model in which inequality constraints occasionally bind. Their performance is evaluated and compared using various parameterizations of the one sector growth model with irreversible investment. We develop parameterized expectation algorithms which, on the basis of speed, accuracy and convenience of implementation, appear to dominate the other algorithms.

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Paper provided by Federal Reserve Bank of Chicago in its series Working Paper Series, Macroeconomic Issues with number WP-97-15.

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Date of creation: 1997
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Handle: RePEc:fip:fedhma:wp-97-15
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  44. repec:cup:macdyn:v:1:y:1997:i:2:p:355-86 is not listed on IDEAS
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