IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-01499642.html
   My bibliography  Save this paper

Computational tools in econometric modeling for macroeconomics and finance

Author

Listed:
  • Gilles Dufrénot

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, Centre de recherche de la Banque de France - Banque de France, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique)

  • Fredj Jawadi

    (Amiens School of Management - Amiens School of Management, EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique, UEVE - Université d'Évry-Val-d'Essonne, LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - EESC-GEM Grenoble Ecole de Management - UEVE - Université d'Évry-Val-d'Essonne - TEM - Télécom Ecole de Management)

Abstract

This paper presents the evolution of structural and non-structural macroeconomic models and discusses the progress of quantitative macroeconomics. We also present and discuss several empirical studies that model the statistical properties of the macroeconomic and financial series under consideration in different ways, using diverse econometric and computational tools. We examine the challenges of quantitative macroeconomics. These elements are illustrated by the different contributions of this special issue.

Suggested Citation

  • Gilles Dufrénot & Fredj Jawadi, 2013. "Computational tools in econometric modeling for macroeconomics and finance," Post-Print hal-01499642, HAL.
    • Handle: RePEc:hal:journl:hal-01499642
    DOI: 10.1016/j.econmod.2013.05.008
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
    2. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    3. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    4. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    5. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    6. Sargent, Thomas J & Wallace, Neil, 1975. ""Rational" Expectations, the Optimal Monetary Instrument, and the Optimal Money Supply Rule," Journal of Political Economy, University of Chicago Press, vol. 83(2), pages 241-254, April.
    7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    8. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    9. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    10. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    11. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    12. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    14. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    15. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Icaro Romolo Sousa Agostino & Wesley Vieira da Silva & Claudimar Pereira da Veiga & Adriano Mendonça Souza, 2020. "Forecasting models in the manufacturing processes and operations management: Systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1043-1056, November.

    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. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
    2. Francis X. Diebold, 1998. "The Past, Present, and Future of Macroeconomic Forecasting," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 175-192, Spring.
    3. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    4. Allen, P. Geoffrey & Morzuch, Bernard J., 2006. "Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?," International Journal of Forecasting, Elsevier, vol. 22(3), pages 475-492.
    5. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    6. Christopher L. Gilbert & Duo Qin, 2007. "Representation in Econometrics: A Historical Perspective," Working Papers 583, Queen Mary University of London, School of Economics and Finance.
    7. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    8. David F. Hendry & Grayham E. Mizon, 2016. "Improving the teaching of econometrics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170096-117, December.
    9. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    10. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412.
    11. Abhijit Sharma & Theodore Panagiotidis, 2003. "An Analysis of Exports and Growth in India: Some Empirical Evidence (1971-2001)," Working Papers 2003004, The University of Sheffield, Department of Economics, revised Nov 2003.
    12. Committee, Nobel Prize, 2011. "Thomas J. Sargent and Christopher A. Sims: Empirical Macroeconomics," Nobel Prize in Economics documents 2011-2, Nobel Prize Committee.
    13. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5.
    14. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, September.
    15. Kim, Kun Ho, 2011. "Density forecasting through disaggregation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 394-412, April.
    16. Christopher L. Gilbert & Duo Qin, 2007. "Representation in Econometrics: A Historical Perspective," Working Papers 583, Queen Mary University of London, School of Economics and Finance.
    17. Lucia BALDI & Massimo PERI & Daniela VANDONE, 2010. "Is wine a financial parachute?," Departmental Working Papers 2010-01, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    18. Bothwell Nyoni & Andrew Phiri, 2018. "The Electricity-growth Nexus in South Africa: Evidence from Asymmetric Cointegration and Co-feature Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 80-88.
    19. KAMKOUM, Arnaud Cedric, 2023. "The Federal Reserve’s Response to the Global Financial Crisis and its Effects: An Interrupted Time-Series Analysis of the Impact of its Quantitative Easing Programs," Thesis Commons d7pvg, Center for Open Science.
    20. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.

    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-01499642. 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.