IDEAS home Printed from https://ideas.repec.org/a/zag/zirebs/v15y2012i2p87-100.html
   My bibliography  Save this article

Econometric Models or Smoothing Exponential Techniques to Predict Macroeconomic Indicators in Romania

Author

Listed:
  • Mihaela Bratu

    (Faculty of Cybernetics, Statistics and Economic Informatics, Bucharest, Romania)

Abstract

Inflation rate, unemployment rate and interest rate are some of the most important indicators used at macroeconomic level. These variables present an important interest for the central banks that establish the monetary policy (infl ation target), but also for the government interested in public policies. Macroeconometric modeling offers the advantage of using more models to describe the evolution of a single variable and also the advantage of predicting it. But it is important to choose the forecast with the higher degree of accuracy. Calculating some indicators of accuracy we may know the best forecast that will be used to establish the macroeconomic policies. For the interest rate and unemployment rate in Romania VAR(2) models generated more accurate forecasts than ARMA models or models with lags. For the infl ation rate the model with lag, which is consistent with Granger causality, determined the most accurate forecasts. The predictions based on all these models are better than those got using smoothing exponential techniques.

Suggested Citation

  • Mihaela Bratu, 2012. "Econometric Models or Smoothing Exponential Techniques to Predict Macroeconomic Indicators in Romania," Zagreb International Review of Economics and Business, Faculty of Economics and Business, University of Zagreb, vol. 15(2), pages 87-100, November.
  • Handle: RePEc:zag:zirebs:v:15:y:2012:i:2:p:87-100
    as

    Download full text from publisher

    File URL: http://www.efzg.hr/default.aspx?id=17770
    Download Restriction: Abstract only available on-line
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Shobande Olatunji Abdul & Shodipe Oladimeji Tomiwa, 2020. "Re-Evaluation of World Population Figures: Politics and Forecasting Mechanics," Economics and Business, Sciendo, vol. 34(1), pages 104-125, February.

    More about this item

    Keywords

    forecasts; accuracy; econometric models; smoothing exponential techniques;
    All these keywords.

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • 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
    • 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:zag:zirebs:v:15:y:2012:i:2:p:87-100. 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: Jurica Šimurina (email available below). General contact details of provider: https://edirc.repec.org/data/fefzghr.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.