A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast Gdp of Iran

In general gross domestic product (gdp) is a substantial element in macroeconomicanalysis. policy makers of a country use variations ofgdp for longrun planning. considering different economic conditions of a country,forecasting is a useful tool to identify the variations of gdp for planning. inthis paper, quarterly gdp value during (1998-2003) is used as a base ofanalysis. the quarterly gdp values of the year (2004 -2005) are forecastedusing time series, exponential smoothing and neural network approaches.the results are compared with actual quarterly gdp value and errormeasurement are computed in each methods. consequently statistical analysesare accomplished to show the best method of forecasting. we have shown that .neural network approach method is the best alternative to forecast the gdp ofiran.