Abstract
Investigating the factors effective on economic growth is of great importance for most economists. Although lots of studies have been done on economic growth in the world, it has less been regarded in Iran. In this article, by estimating growth regression, we attempt to investigate the supply side of economic growth in Iran. Then we compare the predictive results of Fuzzy-logic, Neural-Fuzzy and Solow models. The results show that there was negative significant relationship (i.e.–0.035) between unstable policy and economic growth rate in Iran during investigation period (1959–2001). In this model, the effect of expenses used by government is positive (i.e. 0.01). Furthermore, the estimated results of long term relationship show that the variable coefficients of capital, labor power, exportation, and inflation are 0.319, 0.016, 0.001, and–0.001, respectively. And also by comparing the predictive results of models for the average percent of annual growth, it is predicted that the average percent of Solow, Neural-Fuzzy, and Fuzzy-logic models are 7.17%, 5.92%, and 6.46% for 2002–2006, respectively. Evaluation of results from the models on the basis of criteria shows that model Neural-Fuzzy predicts better than Fuzzy-logic and Solow models. In other words, forecasting by the model Neural-Fuzzy is recommended.
Highlights
Economic growth is the most important index among the macroeconomic variables
Studying different aspects of economic growth of Iran can be important for two reasons
It is important for politicians to make appropriate governmental decisions, secondly, for economists to get appropriate economic planning for the country as well as the economical institutions
Summary
Economic growth is the most important index among the macroeconomic variables. This variable has been considered as an economical index of government, and its increasing rateM. Economic growth is the most important index among the macroeconomic variables. This variable has been considered as an economical index of government, and its increasing rate. Analyzing economic structure and comparing the results. Shows the welfare condition of the society. Applying suitable economical policies, and recognizing effective factors in economic growth, have always been more important for politicians and economists. Since forecasting economic growth seems to be one of the main parameters of decision makings for governmental and private-sector programmers, identifying effective factors on economic growth, linear and non-linear models (Solow) and (Fuzzy-logic and Neural-Fuzzy) have been designed to achieve more accurate predictions
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