Approximating High-Dimensional Dynamic Models: Sieve Value Function Iteration

43 Pages Posted: 2 Mar 2012 Last revised: 21 May 2021

See all articles by Peter Arcidiacono

Peter Arcidiacono

Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Patrick J. Bayer

Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Federico A Bugni

Duke University, Dept. of Economics

Jonathan James

Duke University

Multiple version iconThere are 3 versions of this paper

Date Written: March 2012

Abstract

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the model's parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated.

Suggested Citation

Arcidiacono, Peter and Bayer, Patrick J. and Bugni, Federico Andres and James, Jonathan, Approximating High-Dimensional Dynamic Models: Sieve Value Function Iteration (March 2012). NBER Working Paper No. w17890, Available at SSRN: https://ssrn.com/abstract=2014584

Peter Arcidiacono (Contact Author)

Duke University - Department of Economics ( email )

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
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National Bureau of Economic Research (NBER) ( email )

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Patrick J. Bayer

Duke University - Department of Economics ( email )

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Federico Andres Bugni

Duke University, Dept. of Economics ( email )

Duke University Dept. of Economics
213 Social Sciences Box 90097
Durham, NC 27708-0204
United States
919-660-1887 (Phone)

HOME PAGE: http://econ.duke.edu/~fb32/index.html

Jonathan James

Duke University ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

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