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Inequality Constraints and Euler Equation-based Solution Methods
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DOI：10.1111/ecoj.12115.png)
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Abstract
En 中文
Solving dynamic models with inequality constraints poses a challenging problem for two major reasons: dynamic programming techniques are reliable but often slow, whereas Euler equation-based methods are faster but have problematic or unknown convergence properties. This study attempts to bridge this gap. I show that a common iterative procedure on the first-order conditions - usually referred to as time iteration - delivers a sequence of approximate policy functions that converges to the true solution under a wide range of circumstances. These circumstances extend to a large set of endogenous and exogenous state variables as well as a very broad spectrum of occasionally binding constraints.
Keywords:
STOCHASTIC GROWTH-MODEL
BUSINESS CYCLES
EQUILIBRIUM
ECONOMY
CREDIT
CHOICE
INCOME
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