IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v41y2013i4p517-524.html
   My bibliography  Save this article

SIMUL 3.2: An Econometric Tool for Multidimensional Modelling

Author

Listed:
  • Rodolphe Buda

Abstract

Initially developed in the context of $${\tt REGILINK}$$ project, $${\tt SIMUL 3.2}$$ econometric software is able to estimate and to run large-scale dynamic multi-regional, multi-sectoral models. The package includes a data bank management module, $${\tt GEBANK}$$ which performs the usual data import/export functions, and transformations (especially the RAS and the aggregation one), a graphic module, $${\tt GRAPHE}$$ , a cartographic module, $${\tt GEOGRA}$$ for a “typical use”. For an “atypical use” the package includes $${\tt CHRONO}$$ to help for the WDC (Working Days Correction) estimation and $${\tt GNOMBR}$$ to replace the floating point arithmetic by a multi-precision one in a program. Although the current package includes a basic estimation’s (OLS) and solving’s (Gauss–Seidel) algorithms, it allows user to implement the equations in their reduced form $${Y_{r,b}=X_{r,b} + \varepsilon}$$ and to use alternative econometric equations. $${\tt SIMUL}$$ provides results and reports documentation in ASCII and $${\hbox{\LaTeX}}$$ formats. The next releases of $${\tt SIMUL}$$ should improve the OLS procedure according to the Wilkinson’s criteria, include Hildreth–Lu’s algorithm and comparative statics option. Later, the package should allow other models implementations (Input–Output, VAR etc.). Even if it’s probably outclassed by the major softwares in terms of design and statistic tests sets, $${\tt SIMUL}$$ provides freely basic evolutive tools to estimate and run easily and safety some large scale multi-sectoral, multi-regional, econometric models. Copyright Springer Science+Business Media, LLC. 2013

Suggested Citation

  • Rodolphe Buda, 2013. "SIMUL 3.2: An Econometric Tool for Multidimensional Modelling," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 517-524, April.
  • Handle: RePEc:kap:compec:v:41:y:2013:i:4:p:517-524
    DOI: 10.1007/s10614-011-9291-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-011-9291-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10614-011-9291-x?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. Kendrick, David A & Amman, Hans M, 1999. "Programming Languages in Economics," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 151-181, October.
    2. Dorofeenko, Victor & Lee, Gabriel S. & Salyer, Kevin D., 2010. "A new algorithm for solving dynamic stochastic macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 388-403, March.
    3. Nepomiastchy, Pierre & Rechenmann, Francois, 1983. "The equation writing external language of the MODULECO software," Journal of Economic Dynamics and Control, Elsevier, vol. 5(1), pages 37-57, February.
    4. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
    6. A. Yalta & A. Yalta, 2010. "Should Economists Use Open Source Software for Doing Research?," Computational Economics, Springer;Society for Computational Economics, vol. 35(4), pages 371-394, April.
    7. Buda, Rodolphe, 2005. "Numerical Analysis in Econom(etr)ic Softwares: the Data-Memory Shortage Management," MPRA Paper 9145, University Library of Munich, Germany, revised 2007.
    8. Michael Lahr & Louis de Mesnard, 2004. "Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 115-134.
    9. Buda, Rodolphe, 2005. "Relevance of an accuracy control module - implementation into an economic modelling software," MPRA Paper 36520, University Library of Munich, Germany.
    10. Dorofeenko, Victor & Lee, Gabriel S. & Salyer, Kevin D., 2010. "A new algorithm for solving dynamic stochastic macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 388-403, March.
    11. Rodolphe Buda, 2008. "Two Dimensional Aggregation Procedure: An Alternative to the Matrix Algebraic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 31(4), pages 397-408, May.
    Full references (including those not matched with items on IDEAS)

    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. Rodolphe Buda, 2015. "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 325-357, August.
    2. 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.
    3. Olaf Posch & Timo Trimborn, 2010. "Numerical solution of continuous-time DSGE models under Poisson uncertainty," Economics Working Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    4. Ryoji Hasegawa & Shigemi Kagawa & Makiko Tsukui, 2015. "Carbon footprint analysis through constructing a multi-region input–output table: a case study of Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 4(1), pages 1-20, December.
    5. Choi, Jun-Ki & Bakshi, Bhavik R. & Haab, Timothy, 2010. "Effects of a carbon price in the U.S. on economic sectors, resource use, and emissions: An input-output approach," Energy Policy, Elsevier, vol. 38(7), pages 3527-3536, July.
    6. Michael L. Lahr & João Pedro Ferreira & Johannes R. Többen, 2020. "Intraregional trade shares for goods‐producing industries: RPC estimates using EU data," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1583-1605, December.
    7. Le Zhang & Andreas Ortmann, 2012. "A reproduction and replication of Engel’s meta-study of dictator game experiments," Discussion Papers 2012-44, School of Economics, The University of New South Wales.
    8. Nicolas Vallois & Dorian Jullien, 2017. "Replication in experimental economics: A historical and quantitative approach focused on public good game experiments," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01651080, HAL.
    9. Umed Temursho, 2018. "Entropy‐based benchmarking methods," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 421-446, November.
    10. Buda, Rodolphe, 2008. "Contrôle des systèmes de modélisation : un exemple de codage et de traçabilité des données [Modelling System Checking : An Example of Data Encoding and Traceability]," MPRA Paper 47209, University Library of Munich, Germany.
    11. Valérie Orozco & Christophe Bontemps & Élise Maigné & Virginie Piguet & Annie Hofstetter & Anne Marie Lacroix & Fabrice Levert & Jean-Marc Rousselle, 2017. "How to make a pie? Reproducible Research for Empirical Economics & Econometrics," Post-Print hal-01939942, HAL.
    12. repec:ilo:ilowps:464252 is not listed on IDEAS
    13. mercado, p. ruben, 2003. "Empirical economywide modeling in argentina," MPRA Paper 58611, University Library of Munich, Germany.
    14. Peters, Jeffrey C. & Hertel, Thomas W., 2016. "The database–modeling nexus in integrated assessment modeling of electric power generation," Energy Economics, Elsevier, vol. 56(C), pages 107-116.
    15. Seyit Kerimkhulle & Natalia Obrosova & Alexander Shananin & Gulmira Azieva, 2022. "The Nonlinear Model of Intersectoral Linkages of Kazakhstan for Macroeconomic Decision-Making Processes in Sustainable Supply Chain Management," Sustainability, MDPI, vol. 14(21), pages 1-21, November.
    16. Kleiber Christian & Zeileis Achim, 2013. "Reproducible Econometric Simulations," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 89-99, July.
    17. Joachim Wagner, 2016. "From Estimation Results to Stylized Facts: Twelve Recommendations for Empirical Research in International Activities of Heterogeneous Firms," World Scientific Book Chapters, in: Microeconometrics of International Trade, chapter 15, pages 479-514, World Scientific Publishing Co. Pte. Ltd..
    18. Mahmood Arai & Jonas Karlsson & Michael Lundholm, 2011. "On Fragile Grounds: A Replication Of “Are Muslim Immigrants Different In Terms Of Cultural Integration?”," Journal of the European Economic Association, European Economic Association, vol. 9(5), pages 1002-1011, October.
    19. Buda, Rodolphe, 2011. "Séries longues d'emploi salarié régional sectoriel français 1967–2006 [French sectoral and regional salaried employment long run time series 1967-2006]," MPRA Paper 34888, University Library of Munich, Germany.
    20. Francisco Cribari-Neto & Spyros Zarkos, 2003. "Econometric and Statistical Computing Using Ox," Computational Economics, Springer;Society for Computational Economics, vol. 21(3), pages 277-295, June.
    21. A. M. P. Santos & R. Salvador & C. Guedes Soares, 2018. "A dynamic view of the socioeconomic significance of ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(2), pages 169-189, June.

    More about this item

    Keywords

    Econometrics; Econometric software; Multi-sectoral multi-regional modelling; Econometric modelling; C51; C52; C53; C63; C82; C87; C88;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Simul in Wikipedia English

    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:41:y:2013:i:4:p:517-524. 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.