New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation //
DOI:
https://doi.org/10.46661/revmetodoscuanteconempresa.2207Keywords:
Accuracy, forecasts, Monte Carlo method, bootstrap technique, biased-corrected-accelerated bootstrap intervals, precisión, pronósticos, método Monte Carlo, técnica bootstrap, intervalos de rutina de carga con corrección de sesgo aceleradoAbstract
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 for Romania and ARMA(1,1) models for Bulgaria 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) 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.
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