IDEAS home Printed from https://ideas.repec.org/a/aes/amfeco/v1y2014i35p390.html

A Hybrid Forecasting Approach

Author

Listed:
  • Emilian Dobrescu

    (Center of Macroeconomic Modelling, Romanian Academy)

Abstract

The objective of the paper is to establish the appropriateness of integrating in predictive simulation an econometric estimation of a given variable into a standard moving average process (a linear algorithm with constant positive weights of distributed lags). The empirical search relates to the Romanian input-output tables collapsed into ten sectors. The database concerning the final output during 1989-2009 years is herein analyzed

Suggested Citation

  • Emilian Dobrescu, 2014. "A Hybrid Forecasting Approach," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(35), pages 390-390, February.
    • Handle: RePEc:aes:amfeco:v:1:y:2014:i:35:p:390
    as

    Download full text from publisher

    File URL: http://www.amfiteatrueconomic.ro/temp/Article_1273.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gregory, Allan W & Smith, Gregor W & Yetman, James, 2001. "Testing for Forecast Consensus," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 34-43, January.
    2. Dobrescu, Emilian, 2013. "Modelling the Sectoral Structure of the Final Output," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 59-89, October.
    3. David C. Schirm, 2003. "A Comparative Analysis of the Rationality of Consensus Forecasts of U.S. Economic Indicators," The Journal of Business, University of Chicago Press, vol. 76(4), pages 547-562, October.
    4. Mariola Pilatowska, 2009. "The Combined Forecasts Using the Akaike Weights," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 5-16.
    5. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521517133.
    6. Gary Koop & Dimitris Korobilis, 2012. "Forecasting Inflation Using Dynamic Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 867-886, August.
    7. Ravazzolo, F. & van Dijk, H.K. & Verbeek, M.J.C.M., 2007. "Predictive gains from forecast combinations using time-varying model weights," Econometric Institute Research Papers EI 2007-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Robert L. Winkler & Robert T. Clemen, 1992. "Sensitivity of Weights in Combining Forecasts," Operations Research, INFORMS, vol. 40(3), pages 609-614, June.
    9. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521739023.
    10. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    11. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    12. Emilian Dobrescu & Viorel Gaftea, 2012. "On the Accuracy of RAS Method in an Emergent Economy," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 14(32), pages 502-521, June.
    13. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.
    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. Herwig Immervoll & Cathal O’Donoghue & Jules Linden & Denisa Sologon, 2023. "Who pays for higher carbon prices?: Illustration for Lithuania and a research agenda," OECD Social, Employment and Migration Working Papers 283, OECD Publishing.
    2. Eduardo Haddad & Juan Manuel Samaniego & Alexandre Porsse & Santiago Ochoa & Luiz Gustavo Souza, 2011. "Interregional Interdependence among Ecuadorian Provinces: An Input-Output Analysis," ERSA conference papers ersa11p836, European Regional Science Association.
    3. Boratyński, Jakub, . "Ekonomiczne skutki eksploatacji gazu łupkowego," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2015(1).
    4. Maurizio Ciaschini & Francesca Severini, 2010. "The Economic Impact of the Green Certificate Market through the Macro Multiplier Approach," Working Papers 2010.105, Fondazione Eni Enrico Mattei.
    5. Ferrari, Alessandro, 2019. "Global Value Chains and the Business Cycle," CEPREMAP Working Papers (Docweb) 1908, CEPREMAP.
    6. Dobrescu, Emilian, 2013. "Modelling the Sectoral Structure of the Final Output," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 59-89, October.
    7. Daniel Croner & Ivan Frankovic, 2018. "A Structural Decomposition Analysis of Global and NationalEnergy Intensity Trends," The Energy Journal, , vol. 39(2), pages 103-122, March.
    8. Lach, Łukasz, 2022. "Optimization based structural decomposition analysis as a tool for supporting environmental policymaking," Energy Economics, Elsevier, vol. 115(C).
    9. Arne J. Nagengast & Robert Stehrer, 2016. "Accounting for the Differences Between Gross and Value Added Trade Balances," The World Economy, Wiley Blackwell, vol. 39(9), pages 1276-1306, September.
    10. Lee, Frederic, 2011. "Old controversy revisited: pricing, market structure, and competition," MPRA Paper 30490, University Library of Munich, Germany.
    11. Manuel Alejandro Cardenete & Ferran Sancho, 2012. "The Role Of Supply Constraints In Multiplier Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 24(1), pages 21-34, June.
    12. Murray, Michael/ M J, 2011. "A critical perspective on heterodox production modeling," MPRA Paper 34255, University Library of Munich, Germany.
    13. Takuro Uehara & Mateo Cordier & Bertrand Hamaide, 2018. "Fully Dynamic Input-Output/System Dynamics Modeling for Ecological-Economic System Analysis," Sustainability, MDPI, vol. 10(6), pages 1-22, May.
    14. Faggio, Giulia & Overman, Henry, 2014. "The effect of public sector employment on local labour markets," Journal of Urban Economics, Elsevier, vol. 79(C), pages 91-107.
    15. José Manuel Rueda-Cantuche & Iñaki Arto & Valeria Andreoni & José M. Rueda-Cantuche, 2012. "Worldwide economic effects of disruptions in the production chain: the 2011 Japanese disasters," EcoMod2012 4088, EcoMod.
    16. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    17. Andrzej Torój & Joscha Beckmann & Michał Rubaszek, 2026. "The role of global value chains for the propagation of global and domestic PMI shocks," Empirical Economics, Springer, vol. 70(3), pages 1-23, March.
    18. Robert C. Johnson, 2018. "Measuring Global Value Chains," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 207-236, August.
    19. Varela Vázquez, Pedro & Sánchez Carreira, María del Carmen & Pereira López, Xesús, 2014. "Estimación del impacto económico del sector eólico en Galicia en el periodo 2000-2010 || Estimation of the Economic Impact of the Wind Energy Sector in Galicia during 2000-2010," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 18-33, December.
    20. Daria Ciriaci & Sandro Montresor & Daniela Palma, 2013. "Do KIBS make manufacturing more innovative? An empirical investigation for four European countries," JRC Working Papers on Corporate R&D and Innovation 2013-04, Joint Research Centre.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

    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:aes:amfeco:v:1:y:2014:i:35:p:390. 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: Valentin Dumitru (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.