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Economic convergence can be considered as one of the practical reactions of the countries to globalization process. Thus, selecting a :union: or regional trade group is one of the important goals in economic planning. Studying international business cycles and their transfer from one country to another can have a great impact on regional cooperation. Investigating the relationship between trade and business cycles can also offer a proper analysis of regional integration. In this paper, such convergence is studied after Iran’s presence in Shanghai Group as an observer member and efforts which are made to join it. Econometric method and generalized gravity model for the years 1996-2009 are used to find out if there is any business convergence between Iran and member states of Shanghai Group and if synchronization of business cycles is effective to business convergence. It has been revealed that there is no business convergence between Iran and member states of Shanghai and the business relations are divergent as well. It is also found out that there is a negative and significant relationship between synchronization of business cycles and convergence (divergence) of these countries.

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Boom and recession cycles in different countries relate to the U.S. business cycles. The study of severe recession in the U.S. can predict a contemporaneous global recession and provide policies to reduce the negative effects. This paper analyzes the business cycles of the U.S. using three stylized facts and reasons. The consequences of U.S. business cycles, as a developed country, have been compared to those of Iranian business cycle in the final section of each part. The period covers quarterly data for U.S during 1960-2010. This paper analyzes the data using VAR model. Our findings show the severe economic recessions have been started in the U.S. during 1980 and 2008.in addition, The U.S. economy has experienced the longest period of economic boom during 1980s and 1990s. Comparing business cycle features of the U.S. and Iran suggests that the severity and extent of boom and recession cycles is much higher in Iran than America. According to the stylized facts on business cycles, some common features of the variables have been confirmed in both countries. On the other variables, the Iranian model is the same of developing countries and the American model is consistent with the developed countries. In terms of the causes of business cycles, the private residential investment has been major cause of business cycles in American economy in the recent years, while exogenous oil price shocks on the Iranian economy has been the most important factor.

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This research examines business-cycle fluctuations by using Knowledge-based Economy Index (KEI). Data have been collected using consolidated method in 116 countries over the period 1990 -2012. Impact of business cycles' fluctuations has been studied according to the level of the countries' economic knowledge. In this classification, countries were divided to three categories: high, medium and low knowledge-based economies. The generalized method of moments (GMM) and system of simultaneous equations were used to estimate the models, and differential equations were applied for interpreting the results. The findings are described in three parts: top countries with high KEI scores experience decreasing and damped business cycle fluctuations. Those oscillations are convergent, and knowledge-based supply and demand in these countries are proportional. The countries with medium KEI scores have stable and iterative business cycle fluctuations, their movements are nearly convergent, and supply and demand are almost knowledge-based. The countries with low KEI scores are capable of instable and very high business cycle oscillations, and there is knowledge-based demand in these countries, but there is no appropriate supply with it, which results in divergent movements in business cycles.

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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 ).
 

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The change in the price of real and financial assets is one of the factors that cause business cycle through different channels such as consumption, investment, firm’s balance sheet, and net export. With attention to aware of factor causing on business cycle in Adopting Economic policies, in this paper, we investigated the effect of stock market, house price, exchange rate, and liquidity on business cycle using linear and nonlinear LSTR models and season’s data in the period of 1991-2018. In nonlinear model, which is more suitable for explaining the relationship between variables in comparison with linear model, the cyclical component of the exchange rate selected as the transition variable and the value of the transition parameter was estimated to be 83.89 rials. Considering the estimated value of the transmission parameter, in the period, there were two regimes in the Iranian economy, low-exchange rate regime and a high-exchange rate regime. The results indicate that in both regimes, an increase in stock prices and liquidity cause economic expansion. Also, an increase in house prices and a decline in the exchange rate in the first regime put the economy at an expansion phase and put the economy at a recession phase in the second regime. Therefore, in order to expanding the economy, it is suggested that, on the one hand, the exchange rate be kept low and, on the other hand, increase housing price, stock price and liquidity.
 
 

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Macroeconomic policy makers and planners always use different tools to achieve economic goals. Credit control is one of these tools. The boom and recession of the financial sector of the economy are called the credit cycle, and of the real sector is called the business cycle. Credit as a complementary input for capital, intermediate goods, and primitive materials can be effective in improving business cycles. This study, by employing Structural Vector Auto Regressive (SVAR) model and using the annual data of Iran during 1973 to 2016, investigates the relationship between credit cycles and business cycles in Iranian economy. The results show that credit cycle has positive effect on business cycle, but business cycle has negative effect on credit cycle. Credit cycle fluctuations have the largest share in explaining the business cycle fluctuations, but business cycle ranks the fourth in explaining the credit cycle fluctuations following own variable, inflation rate and consumption shocks. The investigation of the co-movement between the credit cycle and the business cycle also show that the effect of the credit cycle on the business cycle is revealed from the second period and there is 24 years of co-movement between these cycles. Also, the persistence of the co-movement between these cycles in expansion - improvement phases has causes severe financial crises in the Iranian economy in the long run.