IDEAS home Printed from https://ideas.repec.org/a/aes/infoec/v18y2014i4p154-164.html
   My bibliography  Save this article

Using Grey Production Functions in the Macroeconomic Modelling: An Empirical Application for Romania

Author

Listed:
  • Ana Michaela ANDREI
  • Irina GEORGESCU

Abstract

The work is a development of our earlier studies containing empirical application of models with representative agent. The extensions developed in this paper consist of the following: the introduction of the labor market via the use of labor as the second production factor, the use of the GM(1,1) algorithm in order to adjust the capital and labor data series and to compute grey Cobb-Douglas production function, and finally the comparison of the results obtained applying the model to the actual data and the grey data. The grey production function is estimated using GM(1,1) adjusted statistical series of the GDP, capital stock and labor data. For the two vari-ants we computed the predictions of the indicators: real GDP, consumption, government ex-penditures, trade balance, and burden of debt.

Suggested Citation

  • Ana Michaela ANDREI & Irina GEORGESCU, 2014. "Using Grey Production Functions in the Macroeconomic Modelling: An Empirical Application for Romania," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 18(4), pages 154-164.
    • Handle: RePEc:aes:infoec:v:18:y:2014:i:4:p:154-164
    as

    Download full text from publisher

    File URL: http://www.revistaie.ase.ro/content/72/14%20-%20Andrei,%20Georgescu.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    2. Hansen, Lars Peter & Sargent, Thomas J., 1980. "Formulating and estimating dynamic linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 2(1), pages 7-46, 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. Quah, Danny, 1994. "One business cycle and one trend from (many,) many disaggregates," European Economic Review, Elsevier, vol. 38(3-4), pages 605-614, April.
    2. Filippo Altissimo & Stefano Siviero & Daniele Terlizzese, 2002. "How Deep are the Deep Parameters?," Annals of Economics and Statistics, GENES, issue 67-68, pages 207-226.
    3. Greg Hannsgen, 2006. "The Disutility of International Debt: Analytical Results and Methodological Implications," Palgrave Macmillan Books, in: Philip Arestis & Jesus Ferreiro & Felipe Serrano (ed.), Financial Developments in National and International Markets, chapter 1, pages 1-24, Palgrave Macmillan.
    4. Bodo Herzog, 2019. "Dynamic Expectation Theory: Insights for Market Participants," JRFM, MDPI, vol. 12(2), pages 1-14, May.
    5. Kevin D. Hoover & Òscar Jordà, 2001. "Measuring systematic monetary policy," Review, Federal Reserve Bank of St. Louis, vol. 83(Jul), pages 113-144.
    6. Alessio Moneta, 2005. "Causality in macroeconometrics: some considerations about reductionism and realism," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(3), pages 433-453.
    7. James J. Heckman, 2005. "Micro Data, Heterogeneity and the Evaluation of Public Policy Part 2," The American Economist, Sage Publications, vol. 49(1), pages 16-44, March.
    8. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Yashiv, Eran & Perets, Gadi, 2018. "Lie Symmetries and Essential Restrictions in Economic Optimization," CEPR Discussion Papers 12611, C.E.P.R. Discussion Papers.
    10. Miao, Jianjun & Wu, Jieran & Young, Eric R., 2021. "Macro-financial volatility under dispersed information," Theoretical Economics, Econometric Society, vol. 16(1), January.
    11. Otto Eckstein & Allen Sinai, 1986. "The Mechanisms of the Business Cycle in the Postwar Era," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 39-122, National Bureau of Economic Research, Inc.
    12. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    13. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    14. TUSHAJ Arjin & SINAJ Valentina, 2012. "A Decomposition Of Stock Index Futures Mispricing And The Price Effect Of Index Arbitrage," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 7(2), pages 184-196, August.
    15. Jorg Dopke & Sebastian Weber, 2010. "The within-distribution business cycle dynamics of German firms," Applied Economics, Taylor & Francis Journals, vol. 42(29), pages 3789-3802.
    16. John Davis, 2006. "Social identity strategies in recent economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 13(3), pages 371-390.
    17. Benatia, David & Carrasco, Marine & Florens, Jean-Pierre, 2017. "Functional linear regression with functional response," Journal of Econometrics, Elsevier, vol. 201(2), pages 269-291.
    18. Mauro Napoletano & Jean-Luc Gaffard & Zakaria Babutsidze, 2012. "Agent Based Models A New Tool for Economic and Policy Analysis," Working Papers hal-01070338, HAL.
    19. Palumbo, Michael & Rudd, Jeremy & Whelan, Karl, 2006. "On the Relationships Between Real Consumption, Income, and Wealth," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 1-11, January.
    20. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.

    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:aes:infoec:v:18:y:2014:i:4:p:154-164. 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: Paul Pocatilu (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.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.