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A New Technique based on Simulations for Improving the Inflation Rate Forecasts in Romania


  • Mihaela Simionescu

    () (Institute for Economic Forecasting, Romanian Academy, Bucharest)


The necessity of improving the forecasts accuracy grew in the context of actual economic crisis, but few researchers were interested till now in finding out some empirical strategies to improve their predictions. In this article, for the inflation rate forecasts on the horizon 2010-2012, we proved that the one-step-ahead forecasts based on updated AR(2) models could be substantially improved by generating new predictions using Monte Carlo method and bootstrap technique to simulate the models’ coefficients. In this article we introduced a new methodology of constructing the forecasts, by using the limits of the bias-corrected-accelerated bootstrap intervals for the initial data series of the variable to predict. After evaluating the accuracy of the new forecasts, we found out that all the proposed strategies improved the initial AR(2) forecasts and even the predictions of two experts in forecasting. Our own method based on the lower limits of BCA intervals generated the best forecasts. In the forecasting process based on AR models the uncertainty analysis was introduced, by calculating, under the hypothesis of normal distribution, the probability that the predicted value exceeds a critical value.

Suggested Citation

  • Mihaela Simionescu, 2015. "A New Technique based on Simulations for Improving the Inflation Rate Forecasts in Romania," Working Papers of Institute for Economic Forecasting 150206, Institute for Economic Forecasting.
  • Handle: RePEc:rjr:wpiecf:150206

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    References listed on IDEAS

    1. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.
    2. Gospodinov, Nikolay, 2002. "Median unbiased forecasts for highly persistent autoregressive processes," Journal of Econometrics, Elsevier, vol. 111(1), pages 85-101, November.
    3. Clements, Michael P., 2003. "Some possible directions for future research," International Journal of Forecasting, Elsevier, vol. 19(1), pages 1-3.
    4. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    5. Mihaela BRATU (SIMIONESCU), 2012. "A Strategy To Improve The Gdp Index Forcasts In Romania Using Moving Average Models Of Historical Errors Of The Dobrescu Macromodel," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 128-138, December.
    6. Mihaela Bratu (Simionescu), 2013. "Filters or Holt Winters Technique to Improve the Forecasts for USA Inflation Rate?," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(1), pages 126-136, February.
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    More about this item


    accuracy; forecasts; Monte Carlo method; bootstrap technique; biased-corrected-accelerated bootstrap intervals;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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