Advanced Search
MyIDEAS: Login to save this paper or follow this series

Future Prediction of the Prefectural Economy in Japan: Using a Stochastic Model

Contents:

Author Info

  • Hiroshi Sakamoto

    ()

Registered author(s):

    Abstract

    This study develops an easy forecasting model using prefectural data in Japan. The Markov chain known as a stochastic model corresponds to the vector auto-regressive (VAR) model of the first order. If the transition probability matrix can be appropriately estimated, the forecasting model using the Markov chain can be constructed. Therefore, this study introduces the methodology to estimate the transition probability matrix of the Markov chain using the least-squares optimization. For application, firstly change of the all-prefectures economy by 2020 is analyzed using this model. Secondly, in order to investigate the influence to other prefecture, a specific prefectureÂfs shock is put into a transition probability matrix. Lastly, in order to take out the width of prediction, the Monte Carlo experiment is conducted. Despite this model is very simple, we provide the more sophisticated forecasting information of the prefectural economy in Japan through the complicated extension. JEL classification: C15, C53, C61, O53, R12 Keywords: Prefectural economy, Japan, Stochastic model, Markov chain

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www-sre.wu.ac.at/ersa/ersaconfs/ersa12/e120821aFinal00141.pdf
    Download Restriction: no

    Bibliographic Info

    Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa12p139.

    as in new window
    Length:
    Date of creation: Oct 2012
    Date of revision:
    Handle: RePEc:wiw:wiwrsa:ersa12p139

    Contact details of provider:
    Postal: Welthandelsplatz 1, 1020 Vienna, Austria
    Web page: http://www.ersa.org

    Related research

    Keywords:

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Danny Quah, 1992. "Empirical cross-section dynamics in economic growth," Discussion Paper / Institute for Empirical Macroeconomics, Federal Reserve Bank of Minneapolis 75, Federal Reserve Bank of Minneapolis.
    2. Sakamoto, Hiroshi & Islam, Nazrul, 2008. "Convergence across Chinese provinces: An analysis using Markov transition matrix," China Economic Review, Elsevier, Elsevier, vol. 19(1), pages 66-79, March.
    3. Quah, Danny T., 1996. "Empirics for economic growth and convergence," European Economic Review, Elsevier, Elsevier, vol. 40(6), pages 1353-1375, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa12p139. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gunther Maier).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.