Journal of Applied Finance & Banking, vol.3, pp.73-104, 2013 (Peer-Reviewed Journal)
For many years, economists have been using statistical tools to estimate parameters of
macroeconomic models. Forecasting plays a major role in macroeconomic planning and it
is an essential analytical tool in countries’ economic strategies. In recent years,
researchers are developing new techniques for estimation. Most of these alternative
approaches have their origins in the computational intelligence. They have the ability to
approximate nonlinear functions, parameters are updated adaptively. In particular, this
research focuses on the application of neural networks in modeling and estimation of
macroeconomic parameters. Neural networks have received an increasing amount of
attention among macroeconomic forecasters because of the ability to approximate any
linear and nonlinear relationship with a reasonable degree of accuracy. Turkey is one of
the European Union candidate countries such as Iceland, Montenegro, Serbia and The
Former Yugoslav Republic of Macedonia. 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. The
study focuses mainly on the applicability of artificial neural network model for
forecasting macroeconomic parameters in long term and comparing the artificial neural
network’s results with the Traditional Time Series Analysis (Smoothing &
Decomposition Techniques). To facilitate the presentation, an empirical example is
developed to forecast Turkey’s eight important macroeconomic parameters. Time Series
statistical theory and methods are used to select an adequate technique, based on residual analysis. Turkey will celebrate the 100th anniversary of its foundation in 2023. Policies
and implementations targeted for raising economic position.