IDEAS home Printed from https://ideas.repec.org/p/fth/demoec/97-02.html
   My bibliography  Save this paper

Vector Autoregression Modelling and Forecasting Growth of South Korea

Author

Listed:
  • Ghatak, A.

Abstract

In this paper we have estimated Vector Autoregression (VAR), Bayesian VAR and Vector Error Correction models (VECMs) using annual time series data of SOuth Korea for 1950-1994. We find evidence supporting the view that growth of real per capita income has been aided by income, investment and export growth and government spending and exchange rate policies. VECMs provide better forecasts of growth than the VAR and BVAR models for both short-period and long-period ahead forecasts.

Suggested Citation

  • Ghatak, A., 1997. "Vector Autoregression Modelling and Forecasting Growth of South Korea," Department of Economics, De Montford University 97-02, Department of Economics, De Montfort University.
    • Handle: RePEc:fth:demoec:97-02
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anita Ghatak & Ferda Halicioglu, 2007. "Foreign direct investment and economic growth: some evidence from across the world," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 9(4), pages 381-394.
    2. Yuanyuan Chen & Changhe Lu, 2019. "Future Grain Consumption Trends and Implications on Grain Security in China," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    3. Bakari, Sayef, 2021. "Reinvest the relationship between exports and economic growth in African countries: New insights from innovative econometric methods," MPRA Paper 108785, University Library of Munich, Germany.

    More about this item

    Keywords

    COINTEGRATION ; UNIT ROOTS ; ECONOMETRICS;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:fth:demoec:97-02. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/ssdmuuk.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.