IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v26y2005i2p107-128.html
   My bibliography  Save this article

User-Friendly Parallel Computations with Econometric Examples

Author

Listed:
  • Michael Creel

Abstract

This paper shows how a high-level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of parallelization is done in a way such that an investigator may use the programs without any knowledge of parallel programming. A bootable CD that allows rapid creation of a cluster for parallel computing is introduced. Examples show that parallelization can lead to important reductions in computational time. Detailed discussion of how the Monte Carlo problem was parallelized is included as an example for learning to write parallel programs for Octave. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Michael Creel, 2005. "User-Friendly Parallel Computations with Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 26(2), pages 107-128, October.
    • Handle: RePEc:kap:compec:v:26:y:2005:i:2:p:107-128
    DOI: 10.1007/s10614-005-6868-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-005-6868-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-005-6868-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(4), pages 657-681, October.
    2. Dirk Eddelbuettel, 2000. "Econometrics with Octave," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 531-542.
    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.
    4. Racine, Jeff, 2002. "Parallel distributed kernel estimation," Computational Statistics & Data Analysis, Elsevier, vol. 40(2), pages 293-302, August.
    5. Swann, Christopher A, 2002. "Maximum Likelihood Estimation Using Parallel Computing: An Introduction to MPI," Computational Economics, Springer;Society for Computational Economics, vol. 19(2), pages 145-178, April.
    6. Michael Creel, 2005. "ParallelKnoppix," Grecs Computer Code 003.05, Research Group in Computation and Simulations (GRECS).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2015. "Parallel Sequential Monte Carlo for Efficient Density Combination: The DeCo MATLAB Toolbox," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i03).
    2. Oancea, Bogdan, 2014. "Parallel Computing in Economics - An Overview of the Software Frameworks," MPRA Paper 72039, University Library of Munich, Germany.
    3. Michael Creel, 2008. "Using Parallelization to Solve a Macroeconomic Model: A Parallel Parameterized Expectations Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 343-352, November.
    4. Michael Creel & William Goffe, 2008. "Multi-core CPUs, Clusters, and Grid Computing: A Tutorial," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 353-382, November.
    5. Donghoon Lee & Matthew Wiswall, 2007. "A Parallel Implementation of the Simplex Function Minimization Routine," Computational Economics, Springer;Society for Computational Economics, vol. 30(2), pages 171-187, September.
    6. Michael S. Delgado & Christopher F. Parmeter, 2013. "Embarrassingly Easy Embarrassingly Parallel Processing in R: Implementation and Reproducibility," Working Papers 2013-06, University of Miami, Department of Economics.
    7. Morozov, Sergei & Mathur, Sudhanshu, 2009. "Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control," MPRA Paper 30298, University Library of Munich, Germany, revised 04 Apr 2011.
    8. Kyle Klein & Julian Neira, 2014. "Nelder-Mead Simplex Optimization Routine for Large-Scale Problems: A Distributed Memory Implementation," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 447-461, April.
    9. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2019. "Density Forecasting," BEMPS - Bozen Economics & Management Paper Series BEMPS59, Faculty of Economics and Management at the Free University of Bozen.
    10. Sergei Morozov & Sudhanshu Mathur, 2012. "Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 151-182, August.
    11. Matt Dziubinski & Stefano Grassi, 2014. "Heterogeneous Computing in Economics: A Simplified Approach," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 485-495, April.
    12. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    13. Lilia Maliar, 2015. "Assessing gains from parallel computation on a supercomputer," Economics Bulletin, AccessEcon, vol. 35(1), pages 159-167.
    14. Mathur, Sudhanshu & Morozov, Sergei, 2009. "Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control," MPRA Paper 16721, University Library of Munich, Germany.
    15. Michael Creel, 2009. "A Data Mining Approach to Indirect Inference," UFAE and IAE Working Papers 788.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 25 Oct 2009.
    16. Yongyang Cai & Kenneth Judd & Greg Thain & Stephen Wright, 2015. "Solving Dynamic Programming Problems on a Computational Grid," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 261-284, February.
    17. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.
    18. Simon Peters & Ken Clark & Pascal Ekin & Anja Le Blanc & Stephen Pickles, 2007. "Grid Enabling Empirical Economics: A Microdata Application," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 349-370, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michael Creel, 2005. "User-Friendly Parallel Computations with Econometric Examples," UFAE and IAE Working Papers 637.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    2. Michael Creel & William Goffe, 2008. "Multi-core CPUs, Clusters, and Grid Computing: A Tutorial," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 353-382, November.
    3. Christopher Ferrall, 2005. "Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution," Computational Economics, Springer;Society for Computational Economics, vol. 25(4), pages 343-379, June.
    4. Creel, Michael & Kristensen, Dennis, 2011. "Indirect Likelihood Inference," Dynare Working Papers 8, CEPREMAP.
    5. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    6. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.
    7. Nakano, Junji, 2004. "Parallel computing techniques," Papers 2004,27, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    8. Chéron, Arnaud & Hairault, Jean-Olivier & Langot, François, 2004. "Labor Market Institutions and the Employment-Productivity Trade-Off: A Wage Posting Approach," IZA Discussion Papers 1364, Institute of Labor Economics (IZA).
    9. Peter Fuleky & Eric Zivot, 2014. "Indirect inference based on the score," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 383-393, October.
    10. Lombardi, Marco J. & Calzolari, Giorgio, 2009. "Indirect estimation of [alpha]-stable stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2298-2308, April.
    11. Coenen, Gunter & Wieland, Volker, 2005. "A small estimated euro area model with rational expectations and nominal rigidities," European Economic Review, Elsevier, vol. 49(5), pages 1081-1104, July.
    12. Asai, Manabu & McAleer, Michael, 2015. "Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance," Journal of Econometrics, Elsevier, vol. 189(2), pages 251-262.
    13. Klein, A. & Urbig, D. & Kirn, S., 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 14433, University Library of Munich, Germany.
    14. Thomas D. Tallarini, Jr. & Harold H. Zhang, 2005. "External Habit and the Cyclicality of Expected Stock Returns," The Journal of Business, University of Chicago Press, vol. 78(3), pages 1023-1048, May.
    15. Calvet, Laurent E. & Czellar, Veronika, 2015. "Through the looking glass: Indirect inference via simple equilibria," Journal of Econometrics, Elsevier, vol. 185(2), pages 343-358.
    16. Bollerslev, Tim & Kretschmer, Uta & Pigorsch, Christian & Tauchen, George, 2009. "A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects," Journal of Econometrics, Elsevier, vol. 150(2), pages 151-166, June.
    17. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(4), pages 737-774, August.
    18. Almunia, Miguel & Guceri, Irem & Lockwood, Ben & Scharf, Kimberley, 2020. "More giving or more givers? The effects of tax incentives on charitable donations in the UK," Journal of Public Economics, Elsevier, vol. 183(C).
    19. Maican, Florin G., 2012. "From Boom to Bust and Back Again: A dynamic analysis of IT services," Working Papers in Economics 543, University of Gothenburg, Department of Economics.
    20. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2004. "Estimating nonlinear dynamic equilibrium economies: a likelihood approach," FRB Atlanta Working Paper 2004-1, Federal Reserve Bank of Atlanta.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:26:y:2005:i:2:p:107-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.