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Dynamic Perturbation
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DOI：10.1093/restud/rdae037.png)
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摘要
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We present a novel algorithm called Dynamic Perturbation for solving large-scale macroeconomic models. Our approach involves computing first-order Taylor expansions of the policy functions along the entire equilibrium path. This method applies to a wide range of models and offers significantly higher accuracy than traditional perturbation approaches. Remarkably, even when utilising first-order approximations, our method can effectively handle models with strong nonlinearities and occasionally binding constraints, such as the zero lower bound.
Keyword:
Large-scale models
Nonlinearities
Transition
Business cycle
Computational economics
期刊
IF:
6.4
论文数:
2.5K
被引数:
2.1W
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引用论文
SOLUTION AND MAXIMUM-LIKELIHOOD ESTIMATION OF DYNAMIC NONLINEAR RATIONAL-EXPECTATIONS MODELS.png)
ECONOMETRICA
OAAI
ECONOMETRICAIF7.1
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