In this paper I built forecasts intervals for the inflation
rate in Romania, using the quarterly predicted values provided by the
National Bank of Romania for 2007-2010. First, I used the historical
errors method, which is the most used method, especially by the central
banks. Forecast intervals were built considering that the forecast error
series is normally distributed of zero mean and standard deviation equal
to the RMSE (root mean squared error) corresponding to historical
forecast errors. I introduced as a measure of economic state the indicator
– relative variance of the phenomenon at a specific time in relation with
the variance on the entire time horizon. Then, I calculated the relative
volatility in order to know the change that must be brought to the root
mean squared error in order to take into account the state of economy.
Finally, I proposed a new way of building forecasts intervals, when the
date series follows an autoregressive process of order 1. In this case the
length of forecasts interval is smaller and I got a slightly higher relative
variance. I consider really necessary the building of forecasts intervals,
in order to have a measure of predictions uncertainty, which is quantified
by the National Bank of Romania using the prediction intervals based on
a simple methodology. I calculated the forecasts intervals using MAE
(mean absolute error), the indicator chose by National Bank of Romania
and the MSE (mean squared error) indicator
