This Paper investigates impacts of macroeconomic variables on the demand for money in Iranian economy using an AUTO REGRESSIVE DISTRIBUTED LAG model ((ARDL)) and the data for the period 1340-1382. The results indicate that there is a unique cointegrated and stable long-run equilibrium relationship between the real demand for money and its determinants such as: real GDP, interest rate, and inflation rate. These results reveal that the demand for money in Iranian economy is more sensitive to the real GDP than to the other macroeconomic variables (long term interest rate and inflation rate). Moreover, the long-term income and inflation elasticity of money demand is 2.620 and 0.038, respectively. This shows that money demand function is more elastic with respect to long-term income and inelastic with respect to price level. Also, adjustment coefficient for money demand is estimated to be 0.19. This means that the adjustment process for money demand would take 5 years.

In this article we conducted the production elasticity in separation of human capital and the other production elements to identify the importance of human capital versus physical capital in official and private sections.For this purpose, first we studied theoretical principles of the growth models and the related previous studies. Then a Human capital model presented by Mankiw-Romer and Weil was used to estimate Iran's economy during 1978-2006, by using AUTO REGRESSIVE DISTRIBUTED LAG ((ARDL)). We used the mean of the years as the human capital index. The results indicated that the rate of human capital is more than physical capital in official and private sectors in a shorttime and longtime of the production elasticity. The error turn coefficient (ETC) showed that in every period, %34 of inequality was modified in gross domestic production (GDP) and it is going towards the longtime current.

The phenomenon of population decline and its aging not only affects economic variables, but also leads to increased spending and financial instability in retirement funds. Hence, the present study investigates the impact of demographic changes on the financial sustainability index of Iran's Social Security Organization. To achieve the research goals, the statistical information related to the research variables during the period 1980-2017 collected from the United Nations and the Social Security Organization of Iran websites. Then, the research model was estimated using AUTO REGRESSIVE DISTRIBUTED LAG ((ARDL)) econometric method. The research findings show that population size and organizational support ratio index have a positive effect on the financial sustainability of the organization in the short and long term. Also, the effects of life expectancy and population dependency on the financial sustainability index of the organization in the short and long term are negative. This study, on the one hand, pursues the policies of population growth in the country by the relevant institutions and, on the other hand, proposes parametric and systematic reforms in the Social Security Pension Fund as a strategy for financial sustainability in the terms of aging population phenomenon.

Nowadays, earning maximum foreign exchange through export goods and services are main economic policies of countries, because, if a country faces with shortage of foreign exchange reserves, it must ask other countries for loan to fulfill it' s import needs. then, it can be saied that the policy of determining exchange rate regulates entry and exit of exchange in national econom.Therefore, through applying proper policies, the government should take the control of supply and demand conditions in the exchange market. given the importance of exchange and the policies affecting it, in this study it is aimed at reviewing the impact of monetary policy on exchange from 1972 to 2010. To this end using AUTO REGRESSIVE DISTRIBUTED LAG model the hypothesized model was estimated. the findings of this study show that there are a positive and significant effect of the domestic money and domestic price and negative and significant effect of national income on the exchange rate both in long term and short term.As another variable shows in this study, unstable component of real exchange rate indicated that this variable has a negative and significant impact on real exchange rate, but the impact of this variable is meaningless in long term.

Rural inhabitants’ perception of better life changes when observing the success of other people, and hope to emulate their success. They know that University degree can lead to a higher expected income. In fact urbanism has some benefits but the costs (pollution, congestion, and crime) are also pervasive in developing countries. In order to better understand the problem, and examine policy measures for controlling its negative externalities, it is of importance to study and analyze the factors which may affect migration. Therefore, in this study we investigated this important issue with emphasis on the effect of rural literacy level on rural-urban migration by using an AUTO-REGRESSIVE DISTRIBUTED LAG ((ARDL)) model utilizing time-series data related to the years 1959-2005 in Iran. Results indicate that in long term, rural literacy level has the most effect on this function. It was also found that, 1% increase in rural wage, urban wage, rural value added and rural literacy level can cause 0.25% decrease, 0.32% increase, 0.16% decrease and 0.32% increase in migrant’s number, respectively.

The main propose of this research is the survey of affecting globalization on tax revenue in Iran by AUTOREGRESSIVE DISTRIBUTED LAG ((ARDL)) approach. So other variables such as real per capita income (as an indicator of economic development), degree of urbanization, the share of agriculture in gross domestic product, dependency ratio (as an index of social and economic structure) and exchange rate, effects on tax revenue have been investigated. Stationary test of variables in the model is shown based on adjusted Dickey – Fuller. For the results of this test, the time series used in this model are characteristics I(0) and I(1). In this study, the pattern AUTOREGRESSIVE DISTRIBUTED LAG ((ARDL)) and the method of least squares for first or more order differencing is used. Dynamic model estimation results indicate a tendency towards long run equilibrium model. Additionally, globalization has positive effect on the proportion of total tax and the tax on trade in GDP.

This article attempts to univestigate the phenomon of currency substitution in Iranian economy, using the (ARDL) model. For this purpose both long-run and short-run demand functions were estimated using the statistical data for 1974-2009 period. According to our findings, currency substitution both in long-run and short-run were confirmed with long-run substitution having a more powerful effect than long-run substitution. Also, it is indicated that the direct effect of income and the indirect effects of real interest rate and inflation on demand for money in the long-run were greater than in those in the short-run. The ECM estimated from the real demand function for money was-0.24 which expresses a rather slow process of currency adjustment in Iran.

Several studies have estimated production function in agriculture. Most of them have used econometric methods. Recently, the heuristic algorithms have been widely used in optimization problems. In this paper, genetic algorithm model compared with AUTO REGRESSIVE DISTRIBUTED LAG approach to estimate production function in agriculture. Time series data related to agricultural value added, labor, energy and capital was used for 1978-2008. Comparing the results of two methods based on two criteria of Root Mean Square Error and Coefficient of Determination indicated that genetic algorithm was more suitable than (ARDL) approach for estimating production function.

Increasing the price of energy carriers, due to their contribution to production costs, directly affects the production price index of different sectors of the economy and reduces the welfare of the society. The rising trend of global prices for energy and food suppliers in recent years has made economists interested in examining the relationship between these two variables. In this study the effects of energy prices on the food price index was investigated by using of Atou-REGRESSIVE DISTRIBUTED LAG model at the years of 1980-2016. Also, the error correction term, ECM (-1) was estimated in the estimated model of 0. 76, which indicates that in e The results showed that in the long run, with the rise in the price of energy carriers and because of the manufacturer's alignment with the rise in the price of energy carriers and the effect of other sub-sectors that have been affected by this rise in prices, and they affect the amount of production, the price of food increases dramatically.

The relationship between financial development and income inequality is one of the topics that has been the focus of researchers and economic policymakers since the 1990s,hence extensive empirical studies attempt to determine the type of effect of financial development on income inequality in the world. In Iran, in recent decades, studies have been conducted to investigate the effects of financial development on income inequality within the framework of the inverted U hypothesis and linear relationships between these indicators. In the present study, the asymmetric and non-linear effects of financial development on income inequality for the period 2013-2016 have been investigated. The current research method is organized in the category of applied research, and for this purpose, the N(ARDL) model has been used,the use of this approach is the distinguishing feature of the present study compared to other studies conducted in Iran. The results show that financial development has a negative relationship with income inequality in Iran, and this relationship is consistent with the inequality reduction hypothesis. Also, the existence of long-term asymmetric effects has been confirmed in the model, so increasing and decreasing the financial development of income inequality in the long term bears different statistical effects.