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Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution

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Christopher Ferrall ()

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Abstract

Many economic models are completed by finding a parameter vector θ that optimizes a function f(θ), a task that can only be accomplished by iterating from a starting vector θ0. Use of a generic iterative optimizer to carry out this task can waste enormous amounts of computation when applied to a class of problems defined here as finite mixture models. The finite mixture class is large and important in economics and eliminating wasted computations requires only limited changes to standard code. Further, the approach described here greatly increases gains from parallel execution and opens possibilities for re-writing objective functions to make further efficiency gains. Copyright Springer Science + Business Media, Inc. 2005

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File URL: http://hdl.handle.net/10.1007/s10614-005-6413-3
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Publisher Info
Article provided by Springer in its journal Computational Economics.

Volume (Year): 25 (2005)
Issue (Month): 4 (June)
Pages: 343-379
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Handle: RePEc:kap:compec:v:25:y:2005:i:4:p:343-379

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Web page: http://www.springerlink.com/link.asp?id=100248

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Related research
Keywords: heterogeneous agent models; numerical optimization;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Susumu Imai & Neelam Jain & Andrew Ching, 2006. "Bayesian Estimation of Dynamic Discrete Choice Models," Working Papers 1118, Queen's University, Department of Economics. [Downloadable!]
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  2. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July. [Downloadable!] (restricted)
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  3. Nagurney, Anna, 1996. "Parallel computation," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 7, pages 335-404 Elsevier. [Downloadable!] (restricted)
  4. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470. [Downloadable!]
  5. Peter Arcidiacono & John Bailey Jones, 2003. "Finite Mixture Distributions, Sequential Likelihood and the EM Algorithm," Econometrica, Econometric Society, vol. 71(3), pages 933-946, 05. [Downloadable!] (restricted)
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  6. Jurgen A. Doornik & David F. Hendry & Neil Shephard, . "Computationally-intensive Econometrics using a Distributed Matrix-programming Language," Economics Papers 2001-W22, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
  7. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March. [Downloadable!]
  8. Christopher A. Swann, 2001. "Software for parallel computing: the LAM implementation of MPI," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 185-194. [Downloadable!]
  9. Hotz, V Joseph & Miller, Robert A, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," Review of Economic Studies, Blackwell Publishing, vol. 60(3), pages 497-529, July. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Donghoon Lee & Matthew Wiswall, 2007. "A Parallel Implementation of the Simplex Function Minimization Routine," Computational Economics, Springer, vol. 30(2), pages 171-187, September. [Downloadable!] (restricted)
  2. Victor Aguirregabiria & Pedro mira, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers tecipa-297, University of Toronto, Department of Economics. [Downloadable!]
    Other versions:
  3. Christopher Ferrall, 2008. "Explaining and Forecasting Results of The Self-Sufficiency Project," Working Papers 1165, Queen's University, Department of Economics. [Downloadable!]
  4. Michael Creel & William Goffe, 2008. "Multi-core CPUs, Clusters, and Grid Computing: A Tutorial," Computational Economics, Springer, vol. 32(4), pages 353-382, November. [Downloadable!] (restricted)
    Other versions:
  5. Alexander W. Cappelen & Astri Drange Hole & Erik Ø Sørensen & Bertil Tungodden, 2007. "The Pluralism of Fairness Ideals: An Experimental Approach," American Economic Review, American Economic Association, vol. 97(3), pages 818-827, June. [Downloadable!]
    Other versions:
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