New strategies to improve the accuracy of predictions based on Monte Carlo and bootstrap simulations: An application to Bulgarian and Romanian inflation

The necessity of improving the forecasts accuracy grew in the context of ac- tual 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 for Romania and ARMA(1,1) models for Bulgaria could be substantially improved by gener- ating new predictions using Monte Carlo method and bootstrap technique to simulate the models' coeficients. 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) and ARMA(1,1) forecasts. These techniques also improved the predictions of experts in forecasting made for Romania and the forecasts of the European Commission made for Bulgaria. Our own method based on the lower limits of BCA intervals generated the best forecasts. In the forecasting process based on ARMA models the uncertainty analysis was introduced, by calculating, under the hypothesis of normal distribution, the probability that the predicted value exceeds a critical value. For 2013 in both countries we anticipate a decrease in the degree of uncertainty for annual inflation rate.