IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v32y2008i4p343-352.html
   My bibliography  Save this article

Using Parallelization to Solve a Macroeconomic Model: A Parallel Parameterized Expectations Algorithm

Author

Listed:
  • Michael Creel

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:32:y:2008:i:4:p:343-352
    DOI: 10.1007/s10614-008-9142-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-008-9142-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-008-9142-6?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. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
    2. Michael Creel, 2007. "I ran four million probits last night: HPC clustering with ParallelKnoppix," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 215-223.
    3. Albert Marcet & David A. Marshall, 1994. "Solving nonlinear rational expectations models by parameterized expectations: convergence to stationary solutions," Discussion Paper / Institute for Empirical Macroeconomics 91, Federal Reserve Bank of Minneapolis.
    4. 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).
    5. Albert Marcet & Guido Lorenzoni, 1998. "Parameterized expectations approach; Some practical issues," Economics Working Papers 296, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979.
    7. Maliar, Lilia & Maliar, Serguei, 2003. "Parameterized Expectations Algorithm and the Moving Bounds," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 88-92, January.
    8. Michael Creel, 2005. "User-Friendly Parallel Computations with Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 26(2), pages 107-128, October.
    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. Kenneth Judd & Lilia Maliar & Serguei Maliar, 2009. "Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models," NBER Working Papers 15296, National Bureau of Economic Research, Inc.
    2. Yi-Ting Chen & Edward W. Sun & Yi-Bing Lin, 2020. "Machine learning with parallel neural networks for analyzing and forecasting electricity demand," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 569-597, August.
    3. Lilia Maliar, 2015. "Assessing gains from parallel computation on a supercomputer," Economics Bulletin, AccessEcon, vol. 35(1), pages 159-167.

    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. Maliar, Lilia & Maliar, Serguei, 2005. "Solving nonlinear dynamic stochastic models: an algorithm computing value function by simulations," Economics Letters, Elsevier, vol. 87(1), pages 135-140, April.
    2. Kenneth Judd & Lilia Maliar & Serguei Maliar, 2009. "Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models," NBER Working Papers 15296, National Bureau of Economic Research, Inc.
    3. Lilia Maliar & Serguei Maliar, 2005. "Parameterized Expectations Algorithm: How to Solve for Labor Easily," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 269-274, June.
    4. Ángel Gavilán & Juan A. Rojas, 2009. "Solving Portfolio Problems with the Smolyak-Parameterized Expectations Algorithm," Working Papers 0838, Banco de España.
    5. Alfonso Novales & Javier J. PÈrez, 2004. "Is It Worth Refining Linear Approximations to Non-Linear Rational Expectations Models?," Computational Economics, Springer;Society for Computational Economics, vol. 23(4), pages 343-377, June.
    6. Kenneth L. Judd & Lilia Maliar & Serguei Maliar & Inna Tsener, 2017. "How to solve dynamic stochastic models computing expectations just once," Quantitative Economics, Econometric Society, vol. 8(3), pages 851-893, November.
    7. Gary S. Anderson, 2018. "Reliably Computing Nonlinear Dynamic Stochastic Model Solutions: An Algorithm with Error Formulas," Finance and Economics Discussion Series 2018-070, Board of Governors of the Federal Reserve System (U.S.).
    8. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    9. repec:hal:spmain:info:hdl:2441/3ug0u3qte39q7rqvbmij9rb993 is not listed on IDEAS
    10. Jean Barthélemy & Magali Marx, 2012. "Solving Rational Expectations Models," Sciences Po publications info:hdl:2441/3ug0u3qte39, Sciences Po.
    11. 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.
    12. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    13. 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.
    14. Paul Pichler, 2005. "Evaluating Approximate Equilibria of Dynamic Economic Models," Vienna Economics Papers 0510, University of Vienna, Department of Economics.
    15. Javier J. Pérez, 2004. "A Log-Linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 24(1), pages 59-75, August.
    16. Maliar, Lilia & Maliar, Serguei, 2004. "Endogenous Growth And Endogenous Business Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 8(5), pages 559-581, November.
    17. repec:hal:spmain:info:hdl:2441/7l23tbn4rd9539sljmp8of2hcb is not listed on IDEAS
    18. Gianluca Femminis, 2007. "From simple growth to numerical simulations: a primer in dynamic programming," DISCE - Quaderni dell'Istituto di Teoria Economica e Metodi Quantitativi itemq0745, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    19. Richard W. Evans & Kerk L. Phillips, 2018. "Advantages of an Ellipse when Modeling Leisure Utility," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 513-533, March.
    20. Posch, Olaf & Trimborn, Timo, 2013. "Numerical solution of dynamic equilibrium models under Poisson uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2602-2622.
    21. Fabrice Collard & Carole Haritchabalet, 2012. "Valuing satellite systems to support fishing in a dynamic competitive model," Applied Economics, Taylor & Francis Journals, vol. 44(7), pages 899-916, March.
    22. Gáti, Laura, 2023. "Monetary policy & anchored expectations—An endogenous gain learning model," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 37-47.

    More about this item

    Keywords

    Solving macroeconomic models; Parameterized expectations algorithm; Parallel computing; Nonlinear rational expectations; E20; C63; C88;
    All these keywords.

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    Statistics

    Access and download statistics

    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:32:y:2008:i:4:p:343-352. 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.