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Understanding the different aspects of the relationship between energy consumption and economic growth can outstandingly help to adopt appropriate policies in energy sector. Structural breaks and regime shifts may affect the above relationship. Therefore, it is important to consider structural breaks and regime shifts in empirical analysis. In this paper, the relationship between energy consumption and economic growth is analyzed in the presence of structural breaks. The empirical models are specified and estimated using Iran's time series data during 1967- 2005 period. To this end, unit root tests proposed by Zivot and Andrews (1992) are first used to identify structural breaks found endogenously and then the Gregory-Hansen cointegration test, which allows strctural breaks in time series, is employed to estimate the long-run relationship between energy consumption and economic growth. The results show that in the long run, there is a positive and significant relationship between energy consumption and economic growth in Iran.

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Hyper inflation rates impose direct and indirect costs upon society. It has undesirable consequences that are caused by inflation uncertainty. In this regard, the following questions are raised: How do inflation rate and its uncertainty affect economic growth? Does the structural breakpoint affect relationship between inflation and growth rate? In this study the above questions are examined for the Iran's economy in period 1974-2007. For this purpose the regressive model is applied. In this model, growth rate of GDP depends on inflation rate, growth rate of the money supply, growth rate of the real gross fixed capital formation and inflation uncertainty. For the measuring inflation uncertainty Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used. Based on data analysis, structural break point occurs at inflation rate equal to 20 percent. Results show that the impact of inflation rate on economic growth is significantly negative but it minimizes at the rate of less than 20 percent and increases at the rate of more than 20 percent. Moreover, inflation uncertainty has significant and negative effect on growth.

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The convergence process and the advantages involved for less developed and developing countries, especially those located in the MENA region is of a great importance in economic studies. Through expanding regional co-operations and playing a wider role in the economies of the member states, it can prepare a suitable ground for growing regional markets and positive international economic reactions and finally can result into total development of the region. This article, using time series model is aiming at testing the convergence hypothesis in MENA region (15 countries) during 1980-2008. For analyzing time series model, we used Augmented Dicky Fuller test, Zivot & Andrews (with the endogenous time break) unit root test, Im, Pesaran & Shin and also Levin, Lin & Chu unit root panel data tests. The results of time series model with ADF and ZA tests show that there are two groups of convergence among the selected MENA countries. The first one is those countries which are converging from the low per capita income up to the average per capita income of the selected countries. The second one is the countries which are converging from the high per capita income down to the average of the region. The rest have diverged from the average per capita income during the period. According to Im, Pesaran & Shin and also Levin, Lin & Chu unit root tests, the convergence hypothesis of per capita income to average, is accepted for the whole sample. Altogether, the selected countries are minimizing the gap between their per capita income and the average per capita income of the region.

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This paper examines the existence of β-Convergence between per-capita incomes of selected Islamic countries. For this purpose, data over the period 1965-2006 and a time series approach proposed by Vogelsang (1998) are applied. Robustness of the estimated parameters to the presence of unit roots and/or serial correlations in the residuals is the main advantage of this method. The results show that per-capita income of most countries is converging to the average per-capita income of the selected Islamic countries, which provide evidence of β-Convergence. Cameroon, Indonesia, Malaysia, Niger, Chad, and Togo are the countries that have shown some forms of divergence either before the break date or after that. The estimated break dates are clustered and mostly related to the energy shocks in 1974, 1979, and 1986.

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There have been few studies working on effects of financial repression policies on Iran’s economic growth. Considering the huge share of agricultural sector, we have been trying to fill this gap by the help of time series data from 1962 to 2007 on agricultural GDP, unproductive government expenditure, human capital, industrial price index, political instability, and financial repression measures. Results show that controlling the bank reserve requirement ratio as a proxy for financial repression has negative effect on economic growth of agricultural sector. This indicates that reducing controls on this parameter will help government to achieve higher rate of growth.

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The main purpose of this paper is to introduce a method for more accurately measurement of structural breaks’ impacts of money demand function using fuzzy set approach. Hence, we present a robust method in order to modeling endogenous structural breaks. To do this, first, we review the recent studies on modeling structural breaks in money demand using nonlinear transition functions and fuzzy set theory, then we examine theoretical basics of fuzzy sets, membership and transition functions. In this paper, we model the structural breaks in money demand function via fuzzy set theory by using transition function instead of membership functions. In this regard, after introducing a new transition function, we model the 1993 structural break of money demand in Iran using a binary dummy variable and various transition functions. The findings show that the AS transition function due to more flexibility provides more accurate results rather than binary dummy variable, exponential and logistic transition functions. In general, if the dependent variable of the model is stationary, use of the binary dummy variable for modeling structural breaks causes misspecification. Also, if the dependent variable is non-stationary, due to increasing shock effect, the use of binary dummy variable is wrong.

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Due to the importance of limited energy resources in the world, researchers and policy makers pay more attention to energy intensity. The purpose of the paper is to study the effect of structural break on factors influencing energy intensity in Iran during the period of 1979-2013. The Fully Modified Ordinary Least Squares (FMOLS) method was used to estimate co-integrating relationships among variables under study. The results showed that energy price and foreign direct investment had negative effects, and share of industrial value added had a significant positive effect on energy intensity. Then structural break was included in the model as a dummy variable. Findings indicate that 1987’s structural break has reduced the impact of energy price and industrial value added, which points to a decrease in the price elasticity of energy intensity and an increase in productivity of the industrial sector after structural break. However, such break had no significant effect on the relationship between direct foreign investment and energy intensity.