IDEAS home Printed from https://ideas.repec.org/a/erv/contri/y2014i2014-053.html
   My bibliography  Save this article

Economic models: comparative analysis of their adjustment and prediction capacities

Author

Listed:
  • José Antonio Gibanel Salazar

Abstract

This work investigates different kinds of models for economic time series and compares the ability of these models to fit the observed data and their predictive power in the short term, both for single-series models and for multivariate models. Both capabilities are analyzed and classified according to the type of economic series and the degree of stationariness of the series.

Suggested Citation

  • José Antonio Gibanel Salazar, 2014. "Economic models: comparative analysis of their adjustment and prediction capacities," Contribuciones a la Economía, Servicios Académicos Intercontinentales SL, issue 2014-05, November.
    • Handle: RePEc:erv:contri:y:2014:i:2014-05:3
    as

    Download full text from publisher

    File URL: http://eumed.net/ce/2014/4/economic-models.html
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Papers (Old Series) 1218, Federal Reserve Bank of Cleveland.
    2. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    3. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    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. Matheson, Troy & Stavrev, Emil, 2013. "The Great Recession and the inflation puzzle," Economics Letters, Elsevier, vol. 120(3), pages 468-472.
    6. Wieland, Volker & Cwik, Tobias & Müller, Gernot J. & Schmidt, Sebastian & Wolters, Maik, 2012. "A new comparative approach to macroeconomic modeling and policy analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 523-541.
    7. Davidson, James, 1998. "Structural relations, cointegration and identification: some simple results and their application," Journal of Econometrics, Elsevier, vol. 87(1), pages 87-113, August.
    8. Stephen G. Hall & Jennifer V. Greenslade & S. G. Brian Henry, 1999. "On the Identification of Cointegrated Systems in Small Samples: Practical Procedures with an Application to UK Wages and Prices," Computing in Economics and Finance 1999 643, Society for Computational Economics.
    9. Panayiotis Diamantis & Dimitris Georgoutsos & George Kouretas, 2001. "The Monetary Approach in the Presence of I(2) Components: A Cointegration Analysis of the Official and Black Market for Foreign Currency in Latin America," Working Papers 0108, University of Crete, Department of Economics.
    10. Peter Winker & Dietmar Maringer, 2004. "Optimal Lag Structure Selection in VEC-Models," Contributions to Economic Analysis, in: New Directions in Macromodelling, pages 213-234, Emerald Group Publishing Limited.
    11. Pfaff, Bernhard, 2008. "VAR, SVAR and SVEC Models: Implementation Within R Package vars," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i04).
    12. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    13. H. Peter Boswijk & Jurgen A. Doornik, 2004. "Identifying, estimating and testing restricted cointegrated systems: An overview," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 440-465, November.
    14. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    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. Jurgen A. Doornik, 2018. "Accelerated Estimation of Switching Algorithms: The Cointegrated VAR Model and Other Applications," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(2), pages 283-300, June.
    2. Kaufmann, Robert K. & Dees, Stephane & Mann, Micheal, 2009. "Horizontal and vertical transmissions in the US oil supply chain," Energy Policy, Elsevier, vol. 37(2), pages 644-650, February.
    3. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    4. Marçal, Emerson Fernandes & Zimmermann, Beatrice Aline & Mendonça, Diogo de Prince & Merlin, Giovanni Tondin, 2015. "Addressing important econometric issues on how to construct theoretical based exchange rate misalignment estimates," Textos para discussão 401, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    5. Lahura, Erick, 2017. "El efecto traspaso de la tasa de interés de política monetaria en Perú: evidencia reciente," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 33, pages 9-27.
    6. Søren Johansen, 2014. "Times Series: Cointegration," Discussion Papers 14-24, University of Copenhagen. Department of Economics.
    7. Jurgen A. Doornik, 2017. "Maximum Likelihood Estimation of the I(2) Model under Linear Restrictions," Econometrics, MDPI, vol. 5(2), pages 1-20, May.
    8. Hafsa Hina & Abdul Qayyum, 2015. "Re-estimation of Keynesian Model by Considering Critical Events and Multiple Cointegrating Vectors," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 54(2), pages 123-145.
    9. Christian Schoder, 2012. "Effective demand, exogenous normal utilization and endogenous capacity in the long run. Evidence from a CVAR analysis for the US," IMK Working Paper 103-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    10. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    11. Pablo de la Vega & Guido Zack & Jimena Calvo & Emiliano Libman, 2024. "Inflation Determinants in Argentina (2004-2022)," Papers 2405.20822, arXiv.org.
    12. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    13. Frauke Dobnik, 2013. "Long-run money demand in OECD countries: what role do common factors play?," Empirical Economics, Springer, vol. 45(1), pages 89-113, August.
    14. Emmanouil Mavrakis & Christos Alexakis, 2018. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 159-185, August.
    15. María Lorena Marí Del Cristo & Marta Gómez-Puig, 2013. "Fiscal dynamics in a dollarized, oil-exporting country: Ecuador," Working Papers 13-06, Asociación Española de Economía y Finanzas Internacionales.
    16. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    17. Møller, Niels Framroze, 2008. "Bridging Economic Theory Models and the Cointegrated Vector Autoregressive Model," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-29.
    18. Paul Plummer & Daisaku Yamamoto, 2019. "Economic resilience of Japanese nuclear host communities: A quasi-experimental modeling approach," Environment and Planning A, , vol. 51(7), pages 1586-1608, October.
    19. Colombage, Sisira R.N., 2009. "Financial markets and economic performances: Empirical evidence from five industrialized economies," Research in International Business and Finance, Elsevier, vol. 23(3), pages 339-348, September.
    20. Fakhri, Hasanov, 2010. "The Impact of Real Effective Exchange Rate on the Non-oil Export: The Case of Azerbaijan," MPRA Paper 29556, University Library of Munich, Germany.

    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:erv:contri:y:2014:i:2014-05:3. 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: Lisette Villamizar (email available below). General contact details of provider: http://www.eumed.net/ce/ .

    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.