Iranian economy as a state–petroleum economy with inflation and budget deficit challenges, has experienced both large and small business cycles in the last three decades. Obviously, studying the significant causes of these cycles can help the policy makers to design more accurate and efficient plans and policies. In this paper, we use a structural vector autoregressive (SVAR) model to identify the effective causes of business cycles in Iran. The results show that between 1990 and 2012, budget deficit growth and real exchange rate growth are the most important causes of business cycles in Iran.

Most of the economic plans of industrialized countries due to their dependence on oil imports, as well as oil exporting countries due to the importance of oil revenues in their economy, are formed based on oil price changes and developments. Oil price developments, which are interpreted as shocks, are mostly random in nature, and for this reason, the future shocks or the probability of their occurrence or both are uncertain and unknown for the actors of the oil markets. raw will be uncertain. In this research, the effects of international crude oil price shocks on economic fluctuations in Iran have been investigated using the structural vector autoregression (SVAR) model. In the short term, oil supply and specific demand shocks in the oil market led to an increase in oil prices and, as a result, curb economic production. An increase in oil prices caused by aggregate demand shocks will increase economic output. Aggregate economic demand shock acts as the main source of oil price shocks, and the specific demand of the oil market creates more restraining effects on economic production than aggregate supply and demand. Also, energy industries are less affected by supply and demand shocks than other industries due to the effect of government subsidies and the share system of state companies. The effect of specific demand shocks on oil price on industrial production is greater than supply shocks and demand shocks.

Iranian economy as a state – petroleum economy with inflation and budget deficit challenges pass big and small Business Cycles in the last three decades. Obviously recognition of significant causes of these Business Cycles can to help to programmers and policy makers for the more accurate and efficient offers. This research by using of Structural Vector Autoregressive (SVAR) model recognizes The Effective Causes on Business Cycles of Iran. The conclusion shows between 1990 & 2012 budget deficit growth and real exchange rate growth were the most important causes of Business Cycles of Iran. According to this conclusion macroeconomic policy makers should attention to these causes for gaining more stability.

Because the critical role of agriculture in providing food, produce raw materials and inputs required, prices control of these products have been considered by policy makers and with the various tools try to control the price of agricultural. Agricultural sector as one of the sections of the macroeconomic sector affected by macroeconomic variables. The purpose of this study is to investigate the effect of macroeconomic variables such as liquidity, interest rate, real exchange rate of market and industrial price on price of agricultural products. Therefore, Structural Vector Autoregressive Model (SVAR) was used. In order to identify the structural shocks Directed Acyclic Graphs (DAG) was used. The results show that liquidity effects on agricultural price in the short-term, although this effect is less in the long run. In addition, real exchange rate of market in the long run and industrial price in short-term and in long-run are the most important factor that affecting agricultural price. Therefore, in order to avoid the change of agricultural price uses tightening monetary, control the change of markett real exchange rate and prevent the formation of black market of exchange rate and control industrial price by controlling change in the market exchange rate as the most important factors affecting industrial price.

If there is a consensus about the existence of a bubble in the Tehran Stock Exchange, there is not much consensus about the time of its formation and evacuation. In addition, there is much disagreement about the reasons for the formation and effects of the collapse of the bubbles and its impact on the nominal and real sectors of the economy and its channels of influence. Therefore, identifying the time of formation, collapse and factors affecting the formation and collapse of bubbles and their impact on different sectors of the economy is questionable and research. For this purpose, in this study, the timing of the formation of stock price bubbles in the Tehran Stock Exchange and the impact of the production gap on its formation during the period 2004 to 2020 has been investigated. During the period under review, the stock market in three different periods in 2004, 2011 and 2018 has witnessed a price bubble. Also, the results of the study of how the output gap affects the stock market bubble, which was done using the TVP-SVAR method, indicate that the output gap is effective on the fundamental part of the stock price and its ineffectiveness on the bubble sector. Meanwhile, the effect of stock prices on the output gap from the wealth channel is positive, and as the market grows, this channel will be strengthened.

In countries like Iran, where the government relies heavily on oil revenue, the response of fiscal policy to oil revenue fluctuations is a key transmission mechanism of oil revenue volatility. Several studies have documented various transmission channels through which oil price shocks affect economic activities in developed oil importing countries. But, regarding oil exporting countries, there are few such studies. According to them, government expenditure has the effects of diminishing returns; and, over-expanding by crowding out of private investment will decrease economic growth. Moreover, inefficiency, distortion in allocation of resources and corruption are other channels that have negative effects on output. The aim of this study is to assess the mechanism in which oil shocks affect economic variables of an oil exporting country. For this purpose, we provide evidence on Iran, an oil exporter where a positive oil revenue shock generates an expansion in consumption and investment by both the private and public sectors. we document the effects of an unexpected increase in the oil revenue, on several variables which are GDP, government consumption of goods and services, government investment, private consumption, and private investment. The effects of structural shocks on that variables have been assessed using a Structural Vector Auto Regressive (SVAR) Model in two different situations with dependence and independence of government budget to oil revenue. Due to data availability, however, we study a more recent period, from 19959 to 2015. We assumed the oil revenue is exogenous, so that it is only affected by its lagged values and a shock and the logarithms of the variables are detrended by Hodrick–Prescott Filter. As a first step of the empirical analysis, we carried out unit root tests for all of the variables and the lag length criteria were employed to select optimal lag order of a VAR model. To analyze the relationships between variables with the SVAR model, we estimated matrix B, the coefficients of structural shocks were recovered and their impacts on the system were investigated through impulse responses. To derive the set of identifications, use can be made of the economic theory which imposes a set of over-identifying restrictions on the coefficients of matrix B. Considering the existence of five endogenous variables, x= {GDP, GC, GI, C, I} and one exogenous variable, OR, we have six equations. By restrictions on matrix B, we may have an over-identified structural VAR. In this paper we have two different matrix B with different restrictions to show the dependence and independence of government budget to oil revenue. The resulting structural parameter estimates of matrixes B are given and comparing them indicate that a positive oil revenue shock generates an expansion in consumption and investment by both the private and public sectors. Government investment expands about 2 percent above trend a few quarters after a 4.5 percent oil revenue shock hits the economy. Finally, we find that when fiscal policy is assumed to be unrelated with oil revenue the response of economic variables to oil shocks is smoothed. We find that fiscal policy is the main propagation mechanism that transmits the oil shocks to the economy. The results of the paper carry important implications for the formulation of fiscal policy in oil-exporting countries like Iran. These countries could prevent large swings in economic activity by saving oil windfalls and investing them gradually. Therefore, controlling government expenditure as fiscal policy instrument effectively insulating the economy from the volatility of oil revenue.

With regard to the role of fiscal policy in reducing the financial crises, determining the magnitude of the fiscal policy multiplier after the 2007-2008 global crisis became one of the most challenging issues in the field of fiscal policy. In general, the magnitude of the fiscal policy multiplier is estimated larger than one according to the Keynesian viewpoint and smaller than one based on neoclassical viewpoint. The difference in the magnitude of the multiplier comes from the fact that economists believe that the fiscal policy multiplier is influenced by the degree of economic openness, the exchange rate regime, the way monetary policy is applied and the business cycle. Differences about the magnitude of the fiscal policy multiplier among schools of economic thought are evident in both theoretical and empirical dimensions. In this regard, this paper tries to estimate fiscal policy multiplier using structural vector autoregressive model (Blanchard and Peroti, 2002 method and Markov switching approach (Hall, 2009) using the seasonal data for Iran during the period (1990: 1-2017: 3). The results of the structural vector autoregressive model showed that the instantaneous multiplier, 10-quarter cumulative multiplier, and the 20-quarter cumulative multiplier of the government expenditure were equal to 0. 281, 0. 304, and 0. 445, respectively. In addition, the corresponding multipliers for taxes were-0. 079,-0. 107 and-0. 171, respectively. Since the fiscal policy multiplier varies based on the economic conditions, the results of the nonlinear Markov switching model showed that the government expenditure multiplier during the recession is 0. 828 and it is larger than the same coefficient during the boom period (0. 108), on one hand. On the other hand, the tax multiplier during the boom period (-0. 194) is larger than its value during the period of recession (-0. 092 ).

The present study was aimed to investigate the effects of oil price shocks on discretionary fiscal policies in selected OPEC countries during 1980-2015. In this regard, the heterogeneous dynamic reaction to structural shock was examined using Panel Structural Vector Autoregressive (PSVAR) technique. Based on the findings, the effect of oil price shocks on discretionary fiscal policy was positive in short-run but ineffective in long-run. In addition, the oil price shocks caused an increase in inflation and government expenditure and a decrease in the economic growth in selected OPEC countries according to the Resource Curse phenomenon. Moreover, as variance decomposition showed, the government expenditure and economic growth have the most effect on discretionary policy changes. The effect of discretionary fiscal policy on economic growth in selected OPEC countries was negative, contrary to the Keynesian theory and the results of some other studies. Because discretionary fiscal policies play a major role in decisions of the countries mentioned above, the results also showed that a limitation in the government authority in OPEC countries would come into conflict with the decrease in economic growth and production fluctuation.

Investigating the effects of socioeconomic macroscale factors on road traffic fatalities is a useful step for adopting accurate economic decisions and reducing damages of these accidents in countries. But due to the distinct economic level and position of countries, these effects are different. This paper has paid to investigate the simultaneous relationship between gasoline price and GDP with traffic fatalities. The data used in this paper are the panel data of 91 countries spanning 2000-2014. In analyzing these data that applied separately for OECD and non-OECD countries, have used one of the proper models in econometrics titled "vector autoregressive model (VAR)". The results revealed in both groups of countries and with quite different trends, increase in gasoline price and GDP per capita significantly lead to decrease in traffic fatalities rate. This decrease is more especially about gasoline price in OECD countries. The reason for these results can be the removal unnecessary trips and increase in public transportation utility in effect of gasoline price increase and improve traffic safety conditions in effect of an increase in GDP.