IDEAS home Printed from https://ideas.repec.org/a/ine/journl/v2(bis)y2011i42p56-72.html
   My bibliography  Save this article

Modeling And Forecasting The Exchange Rate In Romania

Author

Listed:
  • Mihaela BRATU

    (Academy of Economic Studies)

Abstract

Econometric modeling of the exchange rate saw successive progresses, the forecasts based on the ‘70s models having a rather good accuracy, as recent researches showed. In order to explain the monthly evolution of RON/USA exchange rate during 2007-June 2011, I used three econometric models: a simultaneous equations model, an autoregressive model of order 1 and a model respecting the sense of Granger causality. From the statistical analysis of forecasting accuracy for one-month-ahead forecasts for July and August 2011 based on these models I found that the best predictions are those based on the model that is compatible with the sense of Granger causality. The higher errors are those of the forecasts based on the AR(1) model. The importance of knowing the best exchange rate forecasts is related to the improvement of decision-making and the building of the monetary policy.

Suggested Citation

  • Mihaela BRATU, 2011. "Modeling And Forecasting The Exchange Rate In Romania," Romanian Journal of Economics, Institute of National Economy, vol. 33(2(bis)(42), pages 56-72, December.
  • Handle: RePEc:ine:journl:v:2(bis):y:2011:i:42:p:56-72
    as

    Download full text from publisher

    File URL: http://www.revecon.ro/articles/2011-2(bis)/2011-2(bis)-5.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    exchange rate; forecasts; accuracy; Granger causality;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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:ine:journl:v:2(bis):y:2011:i:42:p:56-72. 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: Valentina Vasile (email available below). General contact details of provider: https://edirc.repec.org/data/inacaro.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.