IDEAS home Printed from
   My bibliography  Save this article

Modelling And Predicting The Real Money Demand In Romania


  • PELINESCU, Elena

    (Institute for Economic Forecasting, Romanian Academy)

  • SIMIONESCU, Mihaela

    (Institute for Economic Forecasting, Romanian Academy)


The main aim of this article is to model the quarterly real money demand in Romania and to make short-run forecasts for 2014:Q1-2015:Q1. A vector-autoregressive model (VAR(1)) was built for stationary data series of real money demand, real GDP and spread between active and pasive interest rate of the credit institutions over the period from 2000:Q1 to 2013:Q4. In the first period the variations in the double differentiated real money demand are exclusivly generated by the changes in this variable. The short-term forecasts based on this model indicated a slow variation in the rate of real money demand. For the first quarter of 2014 the comparison of the forecast with the actual value is made and an error of 0.94 percentage point was obtained. Starting with the second quarter of 2014, a slow decrease is anticpated for the rate of real money demand.

Suggested Citation

  • PELINESCU, Elena & SIMIONESCU, Mihaela, 2014. "Modelling And Predicting The Real Money Demand In Romania," Journal of Financial and Monetary Economics, Centre of Financial and Monetary Research "Victor Slavescu", vol. 1(1), pages 117-124.
  • Handle: RePEc:vls:rojfme:v:1:y:2014:i:1:p:117-124

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Pelinescu, Elena, 2012. "Transmission Mechanism of Monetary Policy in Romania. Insights into the Economic Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-21, September.
    2. Ragot, Xavier, 2014. "The case for a financial approach to money demand," Journal of Monetary Economics, Elsevier, vol. 62(C), pages 94-107.
    3. Scutaru, Cornelia & Pelinescu, Elena, 2001. "A Dynamic Model Of The Money Demand In Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 32-47, June.
    4. Ralph Setzer & Guntram Wolff, 2013. "Money demand in the euro area: new insights from disaggregated data," International Economics and Economic Policy, Springer, vol. 10(2), pages 297-315, June.
    5. Dreger, Christian & Wolters, Jürgen, 2014. "Money demand and the role of monetary indicators in forecasting euro area inflation," International Journal of Forecasting, Elsevier, vol. 30(2), pages 303-312.
    6. Dreger, Christian & Wolters, Jürgen, 2015. "Unconventional monetary policy and money demand," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 40-54.
    7. Jawadi, Fredj & Sousa, Ricardo M., 2013. "Money demand in the euro area, the US and the UK: Assessing the role of nonlinearity," Economic Modelling, Elsevier, vol. 32(C), pages 507-515.
    8. Beyer, Andreas, 2009. "A Stable Model for Euro Area Money Demand: Revisiting the Role of Wealth," Working Paper Series 1111, European Central Bank.
    9. Defne Mutluer & Yasemin Barlas, 2002. "Modeling the Turkish Broad Money Demand," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 2(2), pages 55-75.
    10. Mohsen Bahmani-Oskooee & Ali M. Kutan & Dan Xi, 2013. "The impact of economic and monetary uncertainty on the demand for money in emerging economies," Applied Economics, Taylor & Francis Journals, vol. 45(23), pages 3278-3287, August.
    11. William T. Gavin, 2005. "M2 and 'reigniting inflation'," Monetary Trends, Federal Reserve Bank of St. Louis, issue Jun.
    Full references (including those not matched with items on IDEAS)

    More about this item


    money demand; VAR model; spread; forecasts;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods


    Access and download statistics


    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:vls:rojfme:v:1:y:2014:i:1:p:117-124. 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: (Daniel Mateescu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.