This article examines the effect of oil price fluctuations on Iran's economic growth. The research data are quarterly and cover the period from 1991:1 to 2021:4. For this purpose, first the oil price instability index is estimated using the GARCH model, then the mutual relationships between the model variables are examined using the vector autoregressive (VAR) method, and finally the long-term relationship between the variables is extracted using the Johansen Cointegration method. Based on the impulse response functions, the oil price shock has had a negative impact on production. Also, according to the estimated long-term relationship during the study period, the variables of private consumption expenditure, investment, and net exports have had a positive and significant impact on GDP, which is consistent with the theoretical basis of the research. In the long run, the oil price variable has had a positive effect and the oil price instability has had a negative effect on GDP. Given the country's strong dependence on oil and oil revenues, the above results are acceptable. Another finding of the study is that the effect of an increase in oil prices has been significant in all cases and greater than the effect of a decrease in oil prices. The results also show that monetary shocks, along with oil price shocks, have a significant effect on GDP.

In this paper relation of stock market and money demand investigated. According to Friedman (1988) stock market has two main effects on money demand. One is positive wealth effect and other is negative substitution effect. Therefore we can investigate net effect of stock market on money demand. the econometric employad approach is Johansen-Juselius and also data are quarterly (1991Q1-2006Q4) and results show that money demand elasticity respect to stock market index is 0.046051. This means that stock market index in Iran has wealth positive effect on money demand. Therefore central bank should increase the money supply when stock market index increase.

This article aims to investigate the relationship between fuel demand and economic growth in the period of 1966-2005 using the Vector Auto Regressive (VAR) methods and Granger causality Test and Vector Error Correction estimation (VEC) and Johansen Cointegration Test. The results suggest a long term relation between gasoline annual consumption and gross domestic product (GDP). The results of variance decomposition show that GDP has the highest impact on itself and the gasoline consumption variation is mainly defined by the GDP. Incorporating gas oil annual consumption, the results of variance decomposition show that GDP has the highest impact on itself and the gas oil annual consumption variation is mainly defined by GDP. The results of estimation incorporating gas oil annual consumption to the model show that that GDP has the highest impact on itself and the gas oil annual consumption variation is mainly defined by itself. The Granger causality Test runs one-way from GDP to gasoline annual consumption and not the other way but it does not show any relationship between GDP and gas oil annual consumption. The results of VEC estimation confirm the results of granger causality Test. The Johansen Cointegration Test shows a relation between GDP and gasoline and gas oil annual consumption in long term. JEL Classification: O40, L91.

In this research, the impacts of nominal shocks (money supply) on real wage in the industrial sector of Iran has been investigated for period 1981-2008. The model that we have used in this study is Vector Autoregressive Model. According to the results of Johansen Test, a long run (cointegrated) relationship between variables in the industrial sector of Iran is confirmed. After estimation of the model and calculation of Impulse Response Function and analyzing dynamics in the model, we will be able to evaluate the response of real wage of industrial sector and the GDP to the shock of monetary policy variables. On the basis of the results, response of real wages is negative and GDP is positive, real and the wages of industrial sector are sticky.

The stock exchange is one of the most powerful sectors, which contribute significantly to the economy's wealth. It plays a crucial role in economic growth and economic development, to which industry, trade and trade as a whole would be benefiting. Therefore, a significant number of research projects have been devoted not surprisingly to understanding the nature of stock market movements and their general performance. A number of studies have shown that macroeconomic variables have a significant impact on stock market performance, while other studies have at best found an inconclusive relationship. It is also worth noting that most of these studies were conducted on developed markets and rarely touched on the combination of emerging and developed markets. Hence this study aims at understanding the impact of selected macroeconomic variables such as Export growth, Import growth, Trade balance, Inflation rate, Broad money growth and exchange rate on the stock market chosen Indices of five Asian countries such as India, Japan, China, Hong Kong and Singapore. The Augmented Dickey-Fuller Test (ADF), Granger causality Test, Johansen Cointegration Test the short-run and long-run Cointegration between the variables. Variance decomposition analysis is also used to determine how much of the variability in stock returns is lagged by its own variance. The study's findings reveal a substantial long-run Cointegration among the macroeconomic variables and stock indices in the case of Japan, China, Hong Kong, and Singapore. All the macroeconomic variables are integrated into I (1) except for the trade balance in the case of Japan, which is integrated into I (2).