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Forecast Intervals for Inflation in Romania


  • Mihaela BRATU

    (Academy of Economic Studies, Bucharest, Romania)


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 the building of forecasts intervals truly necessary, 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 chosen by the National Bank of Romania and the MSE (mean squared error) indicator.

Suggested Citation

  • Mihaela BRATU, 2012. "Forecast Intervals for Inflation in Romania," Timisoara Journal of Economics, West University of Timisoara, Romania, Faculty of Economics and Business Administration, vol. 5(17), pages 145-152.
  • Handle: RePEc:wun:journl:tje:v05:y2012:i17:a10

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    References listed on IDEAS

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    Cited by:

    1. Mihaela Simionescu, 2014. "Forecast Intervals for Inflation Rate and Unemployment Rate in Romania," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 10(5), pages 39-51, October.
    2. Simionescu, Mihaela, 2017. "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series 82, Global Labor Organization (GLO).

    More about this item


    forecast intervals; historical forecasts errors; root mean squared error (RMSE); relative variance; uncertainty;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models


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