Banks as financial institutions of the economy have a significant role in financial intermediation. Savings, investment, production, employment and growth in the national economy are affected by the decisions and operations of banks. Lending credits have been always considered as the main function of banks. Change of the economic circumstances can affect the banking risk. Since repayment of borrowers may decrease over time, the main issues that all banks usually face with are credit risk or loan default. On the other hand, business cycles and financial development are considered as two main factors which affect the credit risk and the failure to repay the loan.
Therefore, the purpose of the current study was to investigate the effects of financial development and business cycles on credit risk of banks for a selection of Iranian banks during the period from 2005-2014 using panel data approach.
The results of the study indicated that financial development and business cycles have negative effects on the credit risk of banks.

 Monetary and fiscal policies are the most important demand-side policies and have an undeniable role in the management of politics. The relative impact of macroeconomic policies rooted in Keynesian and monetarist arguments. Until the Great Depression of the 1930s, the macroeconomic was not formed and the classic thinking was governing the economy. Great Recession of 1929-1933 had undermined the foundations of classical doctrine. Thoughts and theories of classical and neoclassical economics that prevailed for 150 years, could no longer be useful in identifying problems and solutions out of the depression. Keynes success in this period led to the general acceptance of his views about the relative importance of fiscal policy. Then reaction of the theorist of quantity theory especially Milton Friedman developed to the quantity theory of money. Monetary rules of Friedman and the increase of central bank independence in the 1980s (with the intensification of the stagflation phenomenon) led the importance of coordination of monetary and fiscal policy be approved in this period. But it was the right solution for countries that have an independent central bank, or a central bank with a rising degree of independence. Hence, the Keynesian view that fiscal policy priority in countries that do not have independent central bank still retains its importance. According to the central bank's dependence on government policies, investigation of the fiscal policy effects on economic growth in Iran is of great importance. Hence, the present study by indicating a Keynesian model has investigated the effects of various tools of fiscal policy on economic growth in Iran during the 1981-2013 period using the Auto Regressive Distributed Lag Model (ARDL). The study hypotheses include: “The effect of government expenditure on economic growth is positive and significant” and “Algebraic value of the government expenditure coefficient in the Keynesian approach is greater than the government expenditure in the St. Louis model. The results showed that the effect of government expenditure (purchase of goods and services) on economic growth is positive and significant. In order to compare the effect of government expenditure in the Keynesian approach and monetarist approach, comparable models were specified. The first model is the adjusted Keynesian model and the second model is the model of St. Louis (monetarist approach). Both models were estimated using the Johansen- Joselius approach. The results indicated that the algebraic ratio of government expenditure coefficient in the Keynesian model is much larger than the value of the same coefficient in the model of St. Louis, which approves the second hypothesis.

Demand for money is one of the most influencing factors in making monetary policies and it is affected by different variables such as interest rates, income, exchange rates, etc. But all these variables are attributed to the formal economy. One of the most important factors that can affect the demand for money is the underground economy. The underground economy can create monetary and financial issues, obscure statistics and cause the wrong performance of economic policies. More the volume of the underground economy leads to more demand for money in informal and underground markets. The purpose of this study was to estimate the long-run demand for money in Iran with respect to the underground economy as one of the most important variables for the period of 1997-2012 using the ARDL Approach. Three models were estimated for demand for money in Iran. The first model only included the income of the formal sector. In the second model, the underground economy was included to the demand function for money as an independent variable.In the third model, the sum of incomes in formal and underground sectors were were used to estimate the model. Theresults of the study indicated that the underground economy has a positive significant effect on the long-run demand for money in Iran. On the other hand, taking into account the effects of the underground economy, the long-run elasticity of demand for money to income decreases. The results stability tests confirmed the stability of demand for money taking into account the underground economy.
 

 Industrial development is considered as a necessary condition for economic development. among other industries authors paid special attention to cement industry in the process of industrial development, since it absorbs capital, job creation opportunities, consumption of fuel and electricity and the creation of value added in the industrial sector. It is also considered as one of the most important institutions in the construction sector due to national demand in both terms of reconstruction and completion of infrastructure projects. Due to high share of added value and great contribution of cement industry in national production and construction projects, it is important to analyze the relationship between input and economies of scale in the production. So the main question of this study is to estimate the cost function of Fars Cement Company by using combination function, and then analyzing its cost structure. Investigating the structure of an enterprise by using the cost function is based on the of microeconomic theories that is considered as duality. In order to extract the cost function, the Iterated Nonlinear Seemingly Unrelated Regression (NLSUR) method and quarterly data from 2002 to 2012 with Limdep8 Software were used. In this paper, by using the composite cost function and dual cost approach, we could extract economies of scale, returns to scale and substitution elasticity of Fars Cement Company. Allen cross partial elasticity results for each pair of inputs showed that labor is a substitution for capital and other services. Also, capital input and other services are complementary. In addition, demand price elasticity indicate inelasticity of production factors against changes in price of those factors. According to results, production of cement in Fars Cement Company showed increasing economies of scale and returns to scale.

The informal economy includes all activities that are not recorded in GDP of countries. Unlike the formal economy, the informal economy doesn’t follow passed rules and it’s the activities are based on a behavioral criteria. Due to the nature of the informal economy, the money that circulates in this sector of the economy is dirty money. Dirty Money is the money obtained illegally or illegally transported or consumed in the economy. Dirty money in addition to the negative effects of their source activities (the informal economy) has destructive impacts on the economy. Tax evasion and money laundering are among the socio-economic impacts of dirty money that have destructive effects on the economy. In general the dirty money can be considered the cause of currency and financial markets disorders which do not have a clear economic justification. Therefore, this study estimated the volume of dirty money in the economy over the period 1976-2012. To this end, the size of the informal economy was estimated using logic and fuzzy sets, and therefore the results of the study, the informal economy during the related period an average of 17.22% of the GDP in Iran. Due to the results, the size of the informal economy has increased during this period and had an increasing trend 1996 onward. After estimating the size of the informal economy, based on quirk (1996) model, this variable was added as a dependent variable in the equation of money demand function and the volume of dirty money was calculated in the economy, respectively. As the time series used in the model were not co-integrated the ARDL method was used to estimate the model. The results indicated that the dirty money has constituted 10.13 percent of the country's liquidity. There is a significant positive relationship between liquidity and the informal economy. According to the results, the volume of dirty money has increased during the period under discussion. From 2004 onwards, the volume of dirty money has increased with greater intensity.
 

 The main question of this research is studying the data generator system of Tehran Stock Exchange index return. Recent studies show that once data generator system of a variable (linear or nonlinear) is gained, it will be easier to predict that variable with less error. Data used in this research is in the form of daily time series from March 28, 2009 to May 22, 2013. For this purpose, variance ratio test, lyapunov exponent, correlation dimension, and BDS were used as chaos detection tests, and GPH, MRS, R/S and AFRIMA model tests were used to identify long-term memory in stock index return time series. GARCH family asymmetry models were used in order to study data symmetry or asymmetry. The results of MRS, R/S, and GPH tests indicated a long-term memory in the stock index return time series. Moreover, the results of these tests indicate that the Iranian stock market become more efficient during the said time interval. The variance ratio test (VR) shows the biased nature of the data series generator process. But one cannot discover the linearity or nonlinearity of data generator system through the results of this test. It is only possible to ensure that data is not martingale and are capable of prediction. To review any chaotic process in data, lyapunov exponent and correlation dimension tests were used. The results of these tests indicate chaos in the time series of stock index return. The results of BDS test prove a nonlinear process in the ARMA fit model residue. This test confirms chaotic process in GARCH nonlinear model residues. The results of asymmetrical models of GARCH family show the asymmetric behavior of data toward positive and negative shocks. According to the obtained results, it is tried to choose an optimum model to predict the stock index return series. For this purpose, 6 different time series models including linear and nonlinear models and those models that consider long-term memory are used for modeling and prediction. The results indicate the priority of ANFIS fuzzy neural network method by entering the virtual variable in its structure.

 The government needs revenue sources to perform its plans. Tax is one of the most important sources of government revenue which, in addition to its income characteristic, is the most important tool of fiscal policy and plays a significant role in achieving economic goals such as social justice, the improvement of revenue distribution, resources allocation and economic stability.The aim of this research is thus to investigate factors influencing tax effort in Iran and some selected, developing countries.