IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/35446.html
   My bibliography  Save this paper

Estimation of a system of national accounts: implementation with mathematica

Author

Listed:
  • Temel, Tugrul

Abstract

This study implements Mathematica to estimate a system of national accounts. The estimation methods applied are portrayed in Danilov and Magnus (2008), including the Bayesian estimation, restricted and unrestricted least-squares estimation and best linear unbiased estimation. Operationalizing these methods in the Mathematica environment is the main contribution of the current study. In light of the United Nations�e¤orts aimed to standardize across countries the compilation of national accounts, the Mathematica codes developed here should provide an important tool both for the estimation of unrealized or unavailable national accounts data and for conducting cross-country and within-country macroeconomic policy analysis.

Suggested Citation

  • Temel, Tugrul, 2011. "Estimation of a system of national accounts: implementation with mathematica," MPRA Paper 35446, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:35446
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/35446/1/MPRA_paper_35446.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:bla:revinw:v:46:y:2000:i:3:p:329-50 is not listed on IDEAS
    2. Danilov, Dmitry & Magnus, Jan R., 2008. "On the estimation of a large sparse Bayesian system: The Snaer program," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4203-4224, May.
    3. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Other publications TiSEM 7a0ed98e-134b-4fa4-a97c-4, Tilburg University, School of Economics and Management.
    4. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Discussion Paper 2011-022, Tilburg University, Center for Economic Research.
    5. Dmitry Danilov & Jan R. Magnus, 2007. "Some equivalences in linear estimation (in Russian)," Quantile, Quantile, issue 3, pages 83-90, September.
    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. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Other publications TiSEM 7a0ed98e-134b-4fa4-a97c-4, Tilburg University, School of Economics and Management.
    2. Van Tongeren, J.W., 2011. "From national accounting to the design, compilation, and use of bayesian policy and analysis frameworks," Other publications TiSEM e2d6399b-fdf5-4147-b414-3, Tilburg University, School of Economics and Management.
    3. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Discussion Paper 2011-022, Tilburg University, Center for Economic Research.
    4. Dmitry Danilov & Jan R. Magnus, 2007. "Some equivalences in linear estimation (in Russian)," Quantile, Quantile, issue 3, pages 83-90, September.
    5. Di Fonzo, Tommaso & Girolimetto, Daniele, 2023. "Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives," International Journal of Forecasting, Elsevier, vol. 39(1), pages 39-57.
    6. Danilov, Dmitry & Magnus, Jan R., 2008. "On the estimation of a large sparse Bayesian system: The Snaer program," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4203-4224, May.
    7. van Tongeren, Jan W. & Bruil, Arjan, 2022. "Projections to 2025 of the household sector within the Dutch economy," The Journal of the Economics of Ageing, Elsevier, vol. 23(C).
    8. Umed Temurshoev, 2015. "Uncertainty treatment in input-output analysis," Working Papers 2015-004, Universidad Loyola Andalucía, Department of Economics.

    More about this item

    Keywords

    System of national accounts; Social Accounting Matrix; Bayesian estimation; Least-squares estimation; Best linear unbiased estimation; Linear programming;
    All these keywords.

    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    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:pra:mprapa:35446. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.