Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195556
Authors: 
Judd, Kenneth L.
Maliar, Lilia
Maliar, Serguei
Tsener, Inna
Year of Publication: 
2017
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 8 [Year:] 2017 [Issue:] 3 [Pages:] 851-893
Abstract: 
We introduce a computational technique- precomputation of integrals - that makes it possible to construct conditional expectation functions in dynamic stochastic models in the initial stage of a solution procedure. This technique is very general: it works for a broad class of approximating functions, including piecewise polynomials; it can be applied to both Bellman and Euler equations; and it is compatible with both continuous-state and discrete-state shocks. In the case of normally distributed shocks, the integrals can be constructed in a closed form. After the integrals are precomputed, we can solve stochastic models as if they were deterministic. We illustrate this technique using one- and multi-agent growth models with continuous-state shocks (and up to 60 state variables), as well as Aiyagari's ( 1994) model with discrete-state shocks. Precomputation of integrals saves programming efforts, reduces computational burden, and increases the accuracy of solutions. It is of special value in computationally intense applications. MATLAB codes are provided.
Subjects: 
Dynamic model
precomputation
numerical integration
dynamic programming
value function iteration
Bellman equation
Euler equation
envelope condition method
endogenous grid method
Aiyagari model
JEL: 
C61
C63
C68
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/4.0/
Document Type: 
Article
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