IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03464125.html
   My bibliography  Save this paper

Simulation macroéconomique appliquée

Author

Listed:
  • Jacques Fontanel

    (CESICE - Centre d'études sur la sécurité internationale et les coopérations européennes - UPMF - Université Pierre Mendès France - Grenoble 2 - IEPG - Sciences Po Grenoble - Institut d'études politiques de Grenoble)

Abstract

Simulation techniques are well suited to macroeconomic analysis, both for teaching, economic policy and research. It develops the path of scientific preparation of decisions and the analytical and synthetic understanding of the national economy, even if it tends to simplify the complexity of a national economy whose economic variables are influenced by the erratic behavior of the economic agents, the power relationships and the normal behaviors of men that the economy sometimes considers irrational. Computer science can also be used in heuristic analysis, as an instrument of creativity. In the framework of this analysis, systems of macroeconomic equations have been tested, before being used for theoretical experimentation, through simulation over several periods. The models are always built under the "ceteris paribus" hypothesis, but they allow a better understanding of the interactions between the macroeconomic variables under study.

Suggested Citation

  • Jacques Fontanel, 1977. "Simulation macroéconomique appliquée," Post-Print hal-03464125, HAL.
  • Handle: RePEc:hal:journl:hal-03464125
    Note: View the original document on HAL open archive server: https://hal.univ-grenoble-alpes.fr/hal-03464125
    as

    Download full text from publisher

    File URL: https://hal.univ-grenoble-alpes.fr/hal-03464125/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. R. W. Conway, 1963. "Some Tactical Problems in Digital Simulation," Management Science, INFORMS, vol. 10(1), pages 47-61, October.
    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. Enver Yücesan, 1993. "Randomization tests for initialization bias in simulation output," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(5), pages 643-663, August.
    2. Xuefei Lu & Alessandro Rudi & Emanuele Borgonovo & Lorenzo Rosasco, 2020. "Faster Kriging: Facing High-Dimensional Simulators," Operations Research, INFORMS, vol. 68(1), pages 233-249, January.
    3. Kleijnen, Jack P.C., 1992. "Sensitivity analysis of simulation experiments: regression analysis and statistical design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 34(3), pages 297-315.
    4. Richard E. Nance & Robert G. Sargent, 2002. "Perspectives on the Evolution of Simulation," Operations Research, INFORMS, vol. 50(1), pages 161-172, February.
    5. Mingchang Chih, 2019. "An Insight into the Data Structure of the Dynamic Batch Means Algorithm with Binary Tree Code," Mathematics, MDPI, vol. 7(9), pages 1-8, August.
    6. Pat-Anthony Federico & Paul W. Figliozzi, 1981. "Computer Simulation of Social Systems," Sociological Methods & Research, , vol. 9(4), pages 513-533, May.
    7. Leroudier, Jacques & Parent, Michel, 1979. "Discrete event simulation modelling of computer systems for performance evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 21(1), pages 50-79.
    8. Wright, A. & Dent, J. Barry, 1969. "The Application Of Simulation Techniques To The Study Of Grazing Systems," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 13(2), pages 1-10, December.
    9. Song, Wheyming T. & Chih, Mingchang, 2010. "Extended dynamic partial-overlapping batch means estimators for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 203(3), pages 640-651, June.
    10. Kleijnen, J.P.C., 2006. "Regression Models and Experimental Designs : A Tutorial for Simulation Analaysts," Discussion Paper 2006-10, Tilburg University, Center for Economic Research.
    11. Alberto Ferreira Pereira, 2011. "Evaluating The Performance Of An Agv Fleet In An Fms Under Minimizing Part Movement And Balancing Workload Rules," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 79-96.
    12. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2020. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," LEM Papers Series 2020/31, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    13. Song, Wheyming Tina & Chih, Mingchang, 2013. "Run length not required: Optimal-mse dynamic batch means estimators for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 229(1), pages 114-123.
    14. Robinson, Stewart, 2007. "A statistical process control approach to selecting a warm-up period for a discrete-event simulation," European Journal of Operational Research, Elsevier, vol. 176(1), pages 332-346, January.
    15. B W Hollocks, 2006. "Forty years of discrete-event simulation—a personal reflection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(12), pages 1383-1399, December.
    16. K Hoad & S Robinson & R Davies, 2010. "Automating warm-up length estimation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(9), pages 1389-1403, September.
    17. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    18. Halkos, George & Kevork, Ilias, 2002. "Confidence intervals in stationary autocorrelated time series," MPRA Paper 31840, University Library of Munich, Germany.
    19. Natalie M. Steiger & James R. Wilson, 2002. "An Improved Batch Means Procedure for Simulation Output Analysis," Management Science, INFORMS, vol. 48(12), pages 1569-1586, December.
    20. Garcia, Rosanna & Rummel, Paul & Hauser, John, 2007. "Validating agent-based marketing models through conjoint analysis," Journal of Business Research, Elsevier, vol. 60(8), pages 848-857, August.

    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:hal:journl:hal-03464125. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.