IDEAS home Printed from https://ideas.repec.org/a/rrs/journl/v14y2020i1p1-24.html
   My bibliography  Save this article

Regionalizing National-Level Growth Projections in the Visegrad Countries – The Issue Of Ex-Post Rescaling

Author

Listed:
  • Balazs Pager

    (Centre for Economic and Regional Studies, Hungary)

  • Zsuzsanna Zsibókb

    (Centre for Economic and Regional Studies, Hungary)

Abstract

Regional economic inequalities in the countries of the Visegrad Group appear to be persistent in the long run, and many empirical studies suggest that their further increase is expected, at least in the medium run. Our study provides empirical results with a methodological focus concerning the long-term prediction of regional economic growth in the Visegrad countries. Our method delivers sub-national gross domestic product projections in a spatial downscaling approach according to which a selected national-level predicted growth path is downscaled to the regional level. In order to keep the regional results consistent with the national-level prediction, an ex-post proportional rescaling is needed which assures that the regional GDP values sum up to the projected national-level aggregate. This article examines the issues emerging from the practice of ex-post rescaling and uses out-of-sample tests on historical data sets to analyse the consequences of various methodological options. Taking into account the pros and cons, our study argues for the usefulness of ex-post rescaling in the case of the regional GDP downscaling in the Visegrad countries.

Suggested Citation

  • Balazs Pager & Zsuzsanna Zsibókb, 2020. "Regionalizing National-Level Growth Projections in the Visegrad Countries – The Issue Of Ex-Post Rescaling," Romanian Journal of Regional Science, Romanian Regional Science Association, vol. 14(1), pages 1-24, JUNE.
  • Handle: RePEc:rrs:journl:v:14:y:2020:i:1:p:1-24
    as

    Download full text from publisher

    File URL: http://rjrs.ase.ro/wp-content/uploads/2017/03/V141/V1411.Pager.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zheng Wang & Jing Wu & Changxin Liu & Gaoxiang Gu, 2017. "Integrated Assessment Models of Climate Change Economics," Springer Books, Springer, number 978-981-10-3945-4, January.
    2. Ben Gardiner & Ron Martin & Peter Sunley & Peter Tyler, 2013. "Spatially unbalanced growth in the British economy," Journal of Economic Geography, Oxford University Press, vol. 13(6), pages 889-928, November.
    3. Owyang, Michael T. & Rapach, David E. & Wall, Howard J., 2009. "States and the business cycle," Journal of Urban Economics, Elsevier, vol. 65(2), pages 181-194, March.
    4. Harry Garretsen & Philip McCann & Ron Martin & Peter Tyler, 2013. "The future of regional policy," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 6(2), pages 179-186.
    5. Goodwin, Paul & Lawton, Richard, 1999. "On the asymmetry of the symmetric MAPE," International Journal of Forecasting, Elsevier, vol. 15(4), pages 405-408, October.
    6. Makridakis, Spyros, 1993. "Accuracy measures: theoretical and practical concerns," International Journal of Forecasting, Elsevier, vol. 9(4), pages 527-529, December.
    7. Detlef P. van Vuuren & Steve J. Smith & Keywan Riahi, 2010. "Downscaling socioeconomic and emissions scenarios for global environmental change research: a review," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 1(3), pages 393-404, May.
    8. Roberta Capello & Andrea Caragliu & Ugo Fratesi, 2017. "Advances in Regional Growth Forecasting Models," International Regional Science Review, , vol. 40(1), pages 3-11, January.
    9. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    10. Mark Horridge & Bartlomiej Rokicki, 2018. "The impact of European Union accession on regional income convergence within the Visegrad countries," Regional Studies, Taylor & Francis Journals, vol. 52(4), pages 503-515, April.
    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. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    2. Maria Tzitiridou-Chatzopoulou & Georgia Zournatzidou & Michael Kourakos, 2024. "Predicting Future Birth Rates with the Use of an Adaptive Machine Learning Algorithm: A Forecasting Experiment for Scotland," IJERPH, MDPI, vol. 21(7), pages 1-13, June.
    3. Bunn, Derek W. & Taylor, James W., 2001. "Setting accuracy targets for short-term judgemental sales forecasting," International Journal of Forecasting, Elsevier, vol. 17(2), pages 159-169.
    4. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
    5. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    6. McKenzie, Jordi, 2011. "Mean absolute percentage error and bias in economic forecasting," Economics Letters, Elsevier, vol. 113(3), pages 259-262.
    7. repec:kap:iaecre:v:15:y:2009:i:4:p:409-420 is not listed on IDEAS
    8. Semenoglou, Artemios-Anargyros & Spiliotis, Evangelos & Makridakis, Spyros & Assimakopoulos, Vassilios, 2021. "Investigating the accuracy of cross-learning time series forecasting methods," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1072-1084.
    9. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
    10. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
    11. Syntetos, Aris A. & Boylan, John E., 2005. "The accuracy of intermittent demand estimates," International Journal of Forecasting, Elsevier, vol. 21(2), pages 303-314.
    12. Huang, Tao & Fildes, Robert & Soopramanien, Didier, 2014. "The value of competitive information in forecasting FMCG retail product sales and the variable selection problem," European Journal of Operational Research, Elsevier, vol. 237(2), pages 738-748.
    13. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2022. "M5 accuracy competition: Results, findings, and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1346-1364.
    14. Louie Ren & Yong Glasure, 2009. "Applicability of the Revised Mean Absolute Percentage Errors (MAPE) Approach to Some Popular Normal and Non-normal Independent Time Series," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(4), pages 409-420, November.
    15. Dominik Martin & Philipp Spitzer & Niklas Kuhl, 2020. "A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs," Papers 2004.10537, arXiv.org.
    16. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    17. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    18. Che-Yu Hung & Chien-Chih Wang & Shi-Woei Lin & Bernard C. Jiang, 2022. "An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    19. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
    20. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
    21. Juan José Echavarría & Andrés González, 2012. "Choques internacionales reales y financieros y su impacto sobre la economía colombiana," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 30(69), pages 14-66, December.

    More about this item

    Keywords

    Regionalization; projections; predictive capacity; gross domestic product; Visegrad countries;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    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:rrs:journl:v:14:y:2020:i:1:p:1-24. 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: Bogdan-Vasile Ileanu (email available below). General contact details of provider: .

    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.