IDEAS home Printed from https://ideas.repec.org/a/ove/journl/aid10969.html
   My bibliography  Save this article

Forecasting the sectoral GVA of a small Spanish region

Author

Listed:
  • Federico Lampis

Abstract

Our main goal in this paper is to evaluate the point forecasting accuracy of several time series econometric models when applied to a small Spanish region. The variable of interest is the sectoral GVA of the Basque Country. The results support the use of univariate models, such as ARMA and SETAR, which outperform the causal model in forecasting accuracy. Â The use of a causal model, such as the Transfer Function model, does not offer a systematic advantage, even if it makes use of the regional statistical information available for the Basque Country.

Suggested Citation

  • Federico Lampis, 2016. "Forecasting the sectoral GVA of a small Spanish region," Economics and Business Letters, Oviedo University Press, vol. 5(2), pages 38-44.
    • Handle: RePEc:ove:journl:aid:10969
    as

    Download full text from publisher

    File URL: https://reunido.uniovi.es/index.php/EBL/article/view/10969
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Terui, Nobuhiko & van Dijk, Herman K., 2002. "Combined forecasts from linear and nonlinear time series models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 421-438.
    2. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    3. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    4. Anonymous, 2014. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 9(1), pages 1-2, May.
    5. Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, May.
    6. Robert Lehmann & Klaus Wohlrabe, 2014. "Regional economic forecasting: state-of-the-art methodology and future challenges," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.
    7. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155, Decembrie.
    8. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    9. Robert Lehmann & Klaus Wohlrabe, 2014. "Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 34(1), pages 61-90, February.
    10. Kopoin, Alexandre & Moran, Kevin & Paré, Jean-Pierre, 2013. "Forecasting regional GDP with factor models: How useful are national and international data?," Economics Letters, Elsevier, vol. 121(2), pages 267-270.
    11. Bernard Fingleton, 2014. "Forecasting with dynamic spatial panel data: practical implementation methods," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 194-207.
    12. Richard J. Smith & Timo Terasvirta, 1991. "Testing Linearity of Economic Time Series against Cyclical Asymmetry," Annals of Economics and Statistics, GENES, issue 20-21, pages 125-142.
    13. Anonymous, 2014. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 9(2), pages 109-110, August.
    14. Carol Taylor West & Thomas M. Fullerton Jr., 2004. "Assessing the Historical Accuracy of Regional Economic Forecasts," Urban/Regional 0404009, University Library of Munich, Germany.
    15. repec:adr:anecst:y:1991:i:20-21:p:06 is not listed on IDEAS
    16. Gianna Boero & Federico Lampis, 2017. "The Forecasting Performance Of Setar Models: An Empirical Application," Bulletin of Economic Research, Wiley Blackwell, vol. 69(3), pages 216-228, July.
    17. Fullerton, Thomas Jr. & Laaksonen, Mika M. & West, Carol T., 2001. "Regional multi-family housing start forecast accuracy," International Journal of Forecasting, Elsevier, vol. 17(2), pages 171-180.
    18. Matias Mayor & Ana Jesus Lopez & Rigoberto Perez, 2007. "Forecasting Regional Employment with Shift-Share and ARIMA Modelling," Regional Studies, Taylor & Francis Journals, vol. 41(4), pages 543-551.
    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. Gabisa, Elias W. & Gheewala, Shabbir H., 2020. "Can substitution of imported gasoline by locally produced molasses ethanol in Ethiopia be sustainable? An eco-efficiency assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).

    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. Robert Lehmann & Klaus Wohlrabe, 2014. "Regional economic forecasting: state-of-the-art methodology and future challenges," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 218-231.
    2. Robert Lehmann, 2023. "The Forecasting Power of the ifo Business Survey," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(1), pages 43-94, March.
    3. Robert Lehmann & Klaus Wohlrabe, 2017. "Boosting and regional economic forecasting: the case of Germany," Letters in Spatial and Resource Sciences, Springer, vol. 10(2), pages 161-175, July.
    4. Henzel Steffen R. & Wohlrabe Klaus & Lehmann Robert, 2015. "Nowcasting Regional GDP: The Case of the Free State of Saxony," Review of Economics, De Gruyter, vol. 66(1), pages 71-98, April.
    5. Valerij Gamukin, 2017. "Structural Change of Gross Regional Product in the Subjects of Ural Federal District," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 410-421.
    6. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65.
    7. Robert Lehmann & Felix Leiss & Simon Litsche & Stefan Sauer & Michael Weber & Annette Weichselberger & Klaus Wohlrabe, 2019. "Mit den ifo-Umfragen regionale Konjunktur verstehen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(09), pages 45-49, May.
    8. João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
    9. CHEN, Helen S.Y., 2020. "Designing Sustainable Humanitarian Supply Chains," OSF Preprints m82ar, Center for Open Science.
    10. Jochen Wulf, 2020. "Development of an AHP hierarchy for managing omnichannel capabilities: a design science research approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 39-68, April.
    11. Maggie O’Neill & Ruth Penfold-Mounce & David Honeywell & Matt Coward-Gibbs & Harriet Crowder & Ivan Hill, 2021. "Creative Methodologies for a Mobile Criminology: Walking as Critical Pedagogy," Sociological Research Online, , vol. 26(2), pages 247-268, June.
    12. Getz, Donald & Page, Stephen J., 2016. "Progress and prospects for event tourism research," Tourism Management, Elsevier, vol. 52(C), pages 593-631.
    13. Schipper, Burkhard C., 2021. "Discovery and equilibrium in games with unawareness," Journal of Economic Theory, Elsevier, vol. 198(C).
    14. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    15. Kumar, Kaushalendra & Shukla, Ankita & Singh, Abhishek & Ram, Faujdar & Kowal, Paul, 2016. "Association between wealth and health among older adults in rural China and India," The Journal of the Economics of Ageing, Elsevier, vol. 7(C), pages 43-52.
    16. Urša Golob & Mark A. P. Davies & Joachim Kernstock & Shaun M. Powell, 2020. "Trending topics plus future challenges and opportunities in brand management," Journal of Brand Management, Palgrave Macmillan, vol. 27(2), pages 123-129, March.
    17. Eunae Yoo & Elliot Rabinovich & Bin Gu, 2020. "The Growth of Follower Networks on Social Media Platforms for Humanitarian Operations," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2696-2715, December.
    18. Mitze, Timo & Makkonen, Teemu, 2023. "Can large-scale RDI funding stimulate post-crisis recovery growth? Evidence for Finland during COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    19. Ya Sun & Gongyuan Wang & Haiying Feng, 2021. "Linguistic Studies on Social Media: A Bibliometric Analysis," SAGE Open, , vol. 11(3), pages 21582440211, September.
    20. Winskell, Kate & Sabben, Gaëlle, 2016. "Sexual stigma and symbolic violence experienced, enacted, and counteracted in young Africans’ writing about same-sex attraction," Social Science & Medicine, Elsevier, vol. 161(C), pages 143-150.

    More about this item

    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:ove:journl:aid:10969. 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: Francisco J. Delgado (email available below). General contact details of provider: https://edirc.repec.org/data/deovies.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.