IDEAS home Printed from https://ideas.repec.org/a/cys/ecocyb/v50y2016i3p45-62.html
   My bibliography  Save this article

Revision Policy Of Seasonally Adjusted Series – Case Study On Romanian Quarterly Gdp

Author

Listed:
  • Andreea MIRICĂ
  • Tudorel ANDREI

    (The Bucharest University of Economic Studies)

  • Elena-Doina DASCĂLU

    (“Spiru-Haret” University and Romanian Court of Accounts, Bucharest)

  • George-Ioan MINCU RĂDULESCU
  • Ionela-Roxana GLĂVA

    (The Bucharest University of Economic Studies)

Abstract

Seasonally adjusted data may change due to a revision of the unadjusted (raw) data or the addition of new data. These changes are called revisions and one of the key challenges for the National Statistical Offices is to balance the trade-off between the need for the best possible seasonally adjusted data, especially at the end of the series – the accuracy of seasonally adjusted data – and the need to avoid insignificant revisions that may later be reversed – series stability over time (Eurostat, 2015a, van Velsen et.al 2011). Thus, designing an accurate and transparent revision policy is mandatory for any Official Statistical Office. This policy should contain: method and software choice for seasonal adjustment, dissemination and storage, methods and timing of reanalysis and revisions, means of aggregation of series, treatment of outliers, requirements for documentation both internal and for users, guidelines for releasing seasonally adjusted data (UNECE, 2012a). This study focuses of the revision policy of seasonal adjustment procedure of the Romanian Quarterly GDP (constant prices 2000). The calculations were performed using JDemetra+ v. 2.0, the official software (Eurostat, 2015b).

Suggested Citation

  • Andreea MIRICĂ & Tudorel ANDREI & Elena-Doina DASCĂLU & George-Ioan MINCU RĂDULESCU & Ionela-Roxana GLĂVA, 2016. "Revision Policy Of Seasonally Adjusted Series – Case Study On Romanian Quarterly Gdp," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 45-62.
    • Handle: RePEc:cys:ecocyb:v:50:y:2016:i:3:p:45-62
    as

    Download full text from publisher

    File URL: ftp://www.eadr.ro/RePEc/cys/ecocyb_pdf/ecocyb3_2016p45-62.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    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. Philip Hans Franses, 2021. "Estimating persistence for irregularly spaced historical data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 2177-2187, December.
    2. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Adriana Scrioșteanu & Maria Magdalena Criveanu, 2023. "Reverse Logistics of Packaging Waste under the Conditions of a Sustainable Circular Economy at the Level of the European Union States," Sustainability, MDPI, vol. 15(20), pages 1-15, October.
    4. Bartosz Kozicki & Grzegorz Mizura & Artur Stopka & Mateusz Andrzej Jędryka, 2021. "Metodyka planowania potrzeb finansowych z wykorzystaniem prognozowania danych retrospektywnych w aspekcie bezpieczeństwa ekonomicznego," Nowoczesne Systemy Zarządzania. Modern Management Systems, Military University of Technology, Faculty of Security, Logistics and Management, Institute of Organization and Management, issue 4, pages 95-108.
    5. Philip Hans Franses, 2018. "Prediction Intervals For Expert-Adjusted Forecasts," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 308-320, December.
    6. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    7. Stefanescu, Răzvan & Dumitriu, Ramona, 2019. "Obiective ale analizei trendurilor seriilor de timp discrete [Objectives of the analysis of trends in discrete time series]," MPRA Paper 97821, University Library of Munich, Germany, revised 23 Dec 2019.
    8. Philip Hans Franses, 2020. "IMA(1,1) as a new benchmark for forecast evaluation," Applied Economics Letters, Taylor & Francis Journals, vol. 27(17), pages 1419-1423, October.

    More about this item

    Keywords

    Seasonal adjustment; GDP; revision policy; JDemetra;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    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:cys:ecocyb:v:50:y:2016:i:3:p:45-62. 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: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/feasero.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.