Forecasting macroeconomic variables using artificial neural network and traditional smoothing techniques

In this study eight macroeconomic indicators including gross domestic product (volume, NGDPD), gross national savings (NGSD_NGDP), inflation (average consumer prices, PCPI), population (LP), total investment (NID_NGDP), unemployment rate (LUR), volume of exports of goods and services (TX_RPCH), volume of imports of goods and services (TM_RPCH) were used for forecasting. As analysis tools, classical time series forecasting methods such as moving averages, exponential smoothing, Brown's single parameter linear exponential smoothing, Brown’s second-order exponential smoothing, Holt's two parameter linear exponential smoothing and decomposition methods applied to macroeconomic data.