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SIMUL 3.2: An Econometric Tool for Multidimensional Modelling

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  • Rodolphe Buda

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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
    5. 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.
    6. 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.
    7. 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.
    8. Buda, Rodolphe, 2005. "Relevance of an accuracy control module - implementation into an economic modelling software," MPRA Paper 36520, University Library of Munich, Germany.
    9. 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.
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    More about this item

    Keywords

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

    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

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