فهرست مطالب zahramila elmi

One of the most important developments in international immigration is the increase in the number and share of women in the migration process. Due to the phenomenon of feminization of migration and the lack of studies on the migration of Iranian women to the destination countries of migration, we decided to study the most important factors affecting this phenomenon in Iran. Therefore, in this research, using the data on Iranian women's migration to developed countries and the two-stage panel generalized moments method (PGMM), the factors affecting the international migration of Iranian women were investigated from 2011 to 2021. Based on the estimation results, the misery index has a positive effect, and control of corruption has a negative and significant effect on women's migration. In addition, the increase in women's participation rates can be a deterrent for women’s international migration. Considering the low rate of women’s participation, which is one of the lowest rates in the Middle East region, and which is a sign of structural problems in the labor market, it is a warning for macroeconomic policymakers that due to the increasing literacy level of women and their self-confidence, and in order to preserve this human capital, examining the situation of the women's labor market and solving its challenges should be prioritized. The ratio of the economic growth of the destination countries of women's migration to the economic growth of Iran, as well as the ratio of the per capita income of the destination countries to Iran, has a positive and significant effect on the migration of Iranian women. These ratios show the welfare difference between the destination countries and Iran, which acts as an attractor not only for women's migration but also for men's migration. Therefore, it is expected that with the appropriate policies in the economy and society and the improvement of economic and welfare conditions, we will not witness the departure of human resources and the wastage of human capital.

In recent decades, the increase in income inequality, economic inefficiency, and lack of economic justice have played a significant role, especially in developing countries, in emphasizing the crucial role of governments in determining appropriate income distribution. Since the mid-1990s, along with the expansion of new institutionalism literature, good governance has been proposed as one of the essential components influencing the fair distribution of opportunities and incomes and the development of countries. In this study, we focus on the Middle East and North Africa (MENA) countries and examine the effects of good governance components on income inequality from 2008 to 2021, using the System Generalized Method of Moments (SGMM) approach. The estimated model results indicate that political instability, one of the most important components of governance, increases income inequality in MENA countries. On the other hand, the expansion of civil liberties and increased economic transparency can reduce income inequality in these countries. Examination of macro variables also shows that an increase in per capita income provides opportunities for reducing inequality, while an increase in the size of the government may be accompanied by an increase in income inequality.

The objective of this research is to examine the growth of green productivity in the industry and transportation sectors of Iran during 2001-2019 and compare it with the conventional productivity index, which has been the criterion considered in policy-making decisions for several decades. Although in traditional productivity theories, green productivity indices generally have higher growth rates than conventional ones, some studies have shown that green productivity can grow at a lower rate than traditional productivity. The results of extended growth accounting along with using SUR methods for calculating the green productivity of two sectors show that the growth of this index is 2.11% for the industrial sector and -5.8% for the transportation sector, and compared to the conventional method, it was found that the growth of traditional productivity measure for the industry sector is underestimated for 0.7% and for the transportation sector, it is overestimated for 6.76%. Based on the results, the policy recommendation is to transform the adoption of an economic growth strategy focused on green productivity from a choice to a necessity, To prevent the creation of misleading ideas about growth prospects and, consequently, prevent the selection of inappropriate policy options by officials, especially in the transportation sector.

The wide scope of influence and effectiveness has turned inflation into one of the most important subjects of empirical studies as well as one of the main axes of policy making. In addition to the causes and effects of inflation, some economists have paid attention to the inflation index. Based on this, current inflation is not considered a suitable indicator for policy making and modeling due to high fluctuations. On the other hand, core inflation as a stable component of current inflation is a more suitable indicator for economic policies due to its stability. In this paper, we investigate the dynamics of macroeconomic variables and inflation core gap using SVAR method, n Iran's economy in the period of1998-2021. The momentum of oil price fluctuations and liquidity do not have a significant impact on the core inflation gap. The core inflation gap is most influenced by currency impulses and its own fluctuations, which shows the impact of inflation expectations on the formation of core inflation; According to the findings of the research, it is suggested to control exchange rate fluctuations and target core inflation in order to control inflationary expectations.The results show that the core inflation index has been more stable compared to the inflation rate and exchange rate fluctuations have the greatest impact on the core inflation gap.

According to financial and monetary theories, the main role of banks in the economy is to create liquidity through cash deposits and provide them in the form of loans. The main purpose of this study is to investigate the effect of shadow banking system on the volume of liquidity in Iran. For this purpose, Iranian quarterly data during the years 1397-1388 have been analyzed using structural vector autoregression and ordinary least squares. The results of  the SVAR model in the form of shadow banking shock and analysis of variance show that the shadow banking system affects the liquidity of the country in the period under review, so that the effect of shadow banking shock on supply Money and quasi-money reached their highest levels in the second year, about 29.70 and 28.40 percent, respectively, and then began to decline. Also, the results of the ordinary least squares method show that there is a positive relationship between shadow banking and money supply and quasi-money and the correlation coefficient of shadow banking with money supply and quasi-money is 0.502677 and 1.043699, respectively. Therefore, the activities of the shadow banking system increase the volume of liquidity by promoting the volume of money and quasi-money, which are the components of the volume of liquidity.

Nowadays, knowledge and technology are tangled with human life, and it is expected that the advancement of technology and its role in daily human life will reduce pollution. Foreign direct investment (FDI) as one of the driving factors of economic growth has caused the destruction of the environment in most of the host countries (pollution haven hypothesis). Considering the importance of environmental quality and the intertwining of human life with information and communication technology (ICT), this study aims to investigate the impact of ICT and FDI on the emission of carbon dioxide (CO2) as an indicator of the quality of the environment in the OPEC member countries during the period of 2008-2019. The estimation results with the Generalized Moments Method show a U relationship between information and communication technology and carbon dioxide emissions. It is also a confirmation of the hypothesis of environmental pollution of foreign investment for the host countries. With regard to the formation of the global village, it is expected that governments, as supporters of society's health, will direct foreign investment towards the use of clean and environmentally friendly energy by applying laws protecting clean production and closely monitoring it.

This study examines how socioeconomic and demographic factors influence labor force participation (LFP) in Iran. Data from the Iranian Household Income and Expenditure Survey applied the pseudo-panel data method used. The logit model estimations show that there is an inverted U-shaped relationship between age and the probability of LFP, with higher chances of entering the labor market at younger than at middle or old ages. Marital status also affects LFP, with respectively never-married and divorced people more likely to participate in the labor market than married people. Being a student reduces the likelihood of LFP while having a larger household size and a higher level of education increases it. Being the head of the household increases the probability of LFP by 39%. Demographic trends in Iran, such as the high proportion of young adults (25-44 years old) who want to join the labor force, the large number of young people in higher education, and the rising rates of divorce and singlehood, suggest that the economic participation rate will increase shortly. Therefore, this important issue should be considered in the macro-policy.

Tourism is a social, cultural and economic phenomenon that plays a vital role in the economic and social development of many countries. The tourism phenomenon has a special direct and indirect relationship with different aspects of human life. Inbound tourism has a positive effect on the economy of destinations by affecting the income of the residents, creating jobs, attracting investment, and increasing the demand for local goods. However, the development of tourism in a destination can lead to some negative aspects, which can cause serious problems after it becomes an established activity. Increasing health expenditures, as an indicator of the health status of communities, is one of the negative effects of tourism. In recent years, tourism and health expenditures have considerably grown in most countries. The GDP per capita is one of the important factors to determine the amount of health expenses. In the tourism literature, few studies have investigated the effect of inbound tourism on the health status of residents. Since there is no consensus on the effects of inbound tourism on the health of the host community, this study aims to investigate the effects of the tourist congestion, carbon dioxide emissions per capita and GDP per capita on health expenditures per capita. To this end, the non-linear relationship between the GDP per capita and the dependent variable is taken into account.

In this study, the Generalized Method of Moments (GMM) was used to investigate the effects of tourist congestion, GDP per capita and carbon dioxide emissions on the health expenditures per capita in 30 OIC and oil-exporting countries. These countries were selected based on the maximum available data during the period of 2004-2018. To estimate the model, the index of the ratio of inbound tourism to the population of the host community was used for the tourist congestion variable. The GMM econometric method was used owing to its ability to solve the problems of possible endogeneity, autocorrelation and heteroskedasticity in the variables. In this study, the cross-sectional dependence was examined by Pesaran’s cross-sectional dependence test (2004), and the stationarity of the variables was checked by Pesaran’s unit root test (2007). The cointegration between the variables was also checked by the Pedroni cointegration test and the Kao cointegration test. The validity of the instruments was assessed by the Sargan test, and the lack of correlation of the second order and the general validity of the estimation was investigated by the Arellano-Bond test and the Wald test, respectively. The data of this study were obtained from the World Bank Database and analyzed with the Eviews 12 software.

Based on the results of Pesaran’s unit root test, the variables of GDP per capita and health expenditure per capita were non-stationary at level. Moreover, the results of the the Pedroni cointegration test, the Kao cointegration test and the unit root test on the model residual term showed that the estimate was not spurious. The results of estimating the research model with the GMM method showed that the variables were statistically significant at the significance level of 1%. The variables of carbon dioxide emission per capita and logarithm of tourist congestion had a negative and significant effect on health and caused an increase in health expenditures. The GDP per capita variable had a nonlinear inverted U-shaped relationship with health expenditure. According to this finding, the increase in the GDP per capita after reaching the maximum point was 43405 international dollars, reducing the health expenditures. After the maximum point, the increase of GDP per capita is expected to make investing in the infrastructure of the health sector possible and provide easier access to health services. Therefore, it can be expected that the increase in GDP per capita will eventually lead to the improvement of the health status of the society. The results of the Sargan test and the Arellano-Band test confirmed the efficiency of the used tool and the lack of correlation of the second order residual. The Wald test also confirmed the validity of the results of the estimated model.

Based on the results of this study, an increase in GDP per capita before reaching the maximum point causes an increase in health expenditures. After reaching the turning point, however, it reduces the health expenditures per capita. Since the per capita GDP of some countries, including Iran, has a significant distance from the maximum point, there is a good opportunity to achieve the downward range of the inverted U in smaller amounts of per capita GDP by investing in health infrastructure. Therefore, before reaching this point, it is recommended to allocate a part of the tax revenue from the top income deciles to investment in the health sector in order to improve the health of the society. Furthermore, in order to reduce the pollution caused by the GDP of polluting industries, the government should adopt policies to prevent environmental damages from directly endangering the health of people. Also, for the reduction of the adverse effect of tourism on health, a tax is suggested to be collected from incoming tourists. Moreover, it is recommended to include environmental and occupational health methods in the design, construction and utilization of tourism industry facilities. It is also suggested that a part of foreign exchange income from the tax on inbound tourists be allocated to the monitoring, control and prevention of epidemic diseases as well as research on diseases and occupational hazards related to the tourism industry. Finally, it is suggested to create a system for registering disease outbreaks in the tourist population and evaluate the disease burden attributed to tourism.

we study the effects of socio-economic and demographic factors on women's economic participation in rural areas of Iran's provinces with emphasis of age-participation curve. Therefore, this study was performed by using the results of the rural households’ income and expenditure survey -has been taken in 2016- in the framework of Pseudo-Panel Data. We used the logit model and the maximum likelihood method to study the rural women's participation, with 28,265 observations. Results show the inverted U-shaped relationship between age and the probability of female participation; In other words, young women are more likely to participate in labor markets more than the other groups. Divorced and single woman has more likely to participate in comparison with who was being married. Therefore, with increasing the divorce rate and singleness in Iran, economic policymakers must provide appropriate solutions for this challenge in the coming years. We found that women studying and the presence of an infant under the age of 6 in the household has a negative effect on the possibility of women's participation in the labor market. The female education has positive effect on their participation rate. In the overlook, considering the demographic mirror and due to the frequency of the women population in the age group of 25 to 35 years, and more willingness of women in the age 35 to 44 years to participate in the labor market, and education of a significant portion of the rural women, the increase of rural female participation is expected in the years ahead.

Nowadays, the world has seen tremendous progress in the penetration of information and communication technology in individual and social life in countries worldwide, regardless of income level. While the increasing penetration of information and communication technology in economic, social, and energy dimensions creates exciting challenges and opportunities, examining its role in reducing or increasing CO2 emissions is essential. Therefore, the main goal of this research is to investigate the role of information and communication technology on the environmental quality of selected oil-exporting countries. The difference between this research and previous studies is that to investigate the impact of ICT on CO2 emissions, it uses a composite index of information and communication technology based on the principal component method (PCA), unlike previous studies that used only one dimension (for example, the Internet penetration rate). In addition to investigating the relationship between ICT and the environment, the study examines the existence of the Kuznets environmental curve and the relationship between foreign trade and the carbon dioxide index. The model estimation of the effect of information and communication technology on the environmental quality of selected oil-exporting countries, including Iran, from 2009 to 2019 has been carried out using the generalized method of moments. The estimation results indicate an inverse U relationship between information and communication technology and carbon dioxide emissions. Also, the results confirm the Kuznets curve hypothesis in the studied countries. According to the study, foreign trade has a positive and significant impact on CO2 emissions.

Since increasing stress in financial markets is important for analysis and forecasting of economic activities and can be reflected in many variables of the financial market, recognizing the main sources of financial stress and its effects on various economic activities and sectors is one of the most important areas in the financial discussions. Considering the importance of this issue, in the present research, the financial stress index in Iran will be calculated, and then the short-term and long-term relationship between financial stress and stock returns of top industries in the Tehran Stock Exchange by using the panel method in the form of a multivariate model will be evaluated during the period of 1384-1398 using daily data. The analysis of this relationship in the long and short term will be investigated using Co integration and Panel Error Correction Model (PECM) and dynamic ordinary least squares (DOLS) methods will be used to investigate the long-term dynamic relationship between model variables. It should be noted that in order to more accurately analyze, in addition to investigation the effects of total financial stress index FSI (which is a combined index of financial stress in the capital, currency and money markets) on the stock returns of the studied industries, the financial stress index of each markets (money, capital and exchange market) has been entered into the model separately and we have investigated the effect of financial stress index in each of  studied financial markets on the stock returns.

In this research, in order to investigate the effect of financial stress, oil price and other independent variables on the stock returns of the studied industries, in the form of a multivariate panel model and the analysis of long-term and short-term coefficients, using Pedroni panel data method (Pedroni 1999&2004) and The panel error correction model (PECM) is used, and for this purpose the following is considered:                                                                                    
    (1)
 
SR: stock returns of the top industries in the Tehran Stock Exchange. This variable is calculated using the following: (Maditinos., & Theriou, 2011)                                                                         (2)                                                                           
 Ti,t  is the stock price index of industry i in period t.
FSI: Financial Stress Index
INF: inflation rate
INT: Interest rate
RER: real exchange rate
                                                                           (3)
       ER: Nominal exchange rate
       CPI*: Foreign CPI
       CPI: Domestic CPI
OIL: oil price 

The results show that in all four estimated models, the effect of the financial stress index on the stock returns of industries is negative and statistically significant. The estimated coefficients for the oil price variable are positive in all four models, which are statistically significant in all models.The estimated coefficients for the inflation rate variable in all models have a negative sign and are statistically significant.The estimation results indicate the positive effect of the interest rate on the stock returns of the studied industries.Based on the obtained results, the exchange rate in all models will have a positive effect on the stock returns.

The results indicate that in all four estimated models, the effect of financial stress index on industry stock returns is negative and statistically significant. In other words, financial stress in the studied markets, including the capital market, money market and foreign exchange market has a negative impact on the stock returns of industries and decrease stock returns of these industries. Also, the research findings show that in all estimated models, oil prices, exchange rates and interest rates have a positive effect on stock returns of the studied industries in Iran. In addition, the findings show that the estimated coefficients for the inflation rate variable are negative in all models and are statistically significant.

Inflation forecasting is one of the most important issues for the economies of countries, As the existing literature suggests, hybrid models will bring better prediction accuracy due to attention to both linear and non-linear dimensions. Furthermore, the use of ARDL model can include lags of other variables in tandem with having linear features. It should also be noted that LSTM models have a forgetting gate due to their non-linear estimation characteristics, and they can incorporate data with very distant lags in the model. Therefore, the combination of these two models can significantly improve the prediction accuracy. Accordingly, attempts have been made in the current study to compare ARDL, NARX, LSTM and ARDL-D-LSTM models with one another and to introduce a suitable model for predicting Iran's monthly inflation rate in the short-term and long-term time horizon. After estimating the monthly inflation rate of Iran in the period of 4/21/2005 to 8/22/2018 and testing the model on the data for the period of 9/22/2018 to 12/21/ 2020 it was found that the NARX model and the ARDL-D-LSTM hybrid model performed well respectively for short-term time horizon and the long-term horizon according to the RMSE criteria.

The formation of the spatial employment pattern in a region is influenced by various geographical, economic, social, and climatic characteristics. In this regard, this paper analyses the effective factors on employment rates in 31 Provinces of Iran over five years (2011-2016). For this purpose, the spatial autocorrelation with direct and indirect effects (spatial spillover) of Factors on employment rate in provinces of iran has been estimated using the panel data and spatial econometrics method (Spatial Durbin model). The results of spatial estimation showed that there is spatial autocorrelation in the provincial employment rate. Other results indicate that the GDP of the provinces has a significant positive direct and spatial spillover effect on the employment rate. On the other hand, energy intensity has a significant negative direct and spatial spillover on the employment rate. The amount of rainfall does not directly affect the employment rate. The study finds an inverse U-shaped relationship between direct and indirect effects of net migration, population density variables, and the employment rate. Therefore, by increasing in immigration and population density, the employment rate increases in the studied provinces and neighboring provinces, and it decreases after crossing the threshold.

The most important instrument of the government to finance public expenditures and to improve the distribution of tax revenues is tax. High reliance of government on seignorage can reduce the role of taxes in correcting the inequalities. Improving the political variable of the voice and accountability by less reliance on seignorage and more reliance on taxes can improve income distribution.The main purpose of this study is to investigate and test this hypothesis with the help of data from selected OECD and D8countriesperiod 2018-2008 using the fully modified least squares method (FMOLS). The results of model estimation showed that the political variables of accountability can improve the distribution of income in the studied countries by reducing the government's reliance on seignorage.

In recent years, the increasing growth in health expenditures has led to the recognition determinants of health expenditures be considered by researchers. According to studies, GDP and the emission of pollution are the important determinants of health expenditures. In this study, the effect of CO2 emission as an environmental indicator, GDP per capita as an economic indicator, urbanization rate and age dependency ratio as social indicators on health expenditures per capita has been estimated through use of the Panel Generalized Moments Method (PGMM) and the nonlinear relationship approach between income per capita and health expenditures per capita in 19 Oil Exporting countries including Iran in the period 2004 - 2018. The findings reveal that the variables of carbon dioxide emission per capita, urbanization rate and age dependency ratio have positive and significant effect and GDP per capita has a nonlinear inverted U-shaped relationship with health expenditure. This nonlinear relationship suggests that increment in GDP per capita leads to an increase in health expenditures per capita until the threshold level, and after that, this increment can lead to a reduction in health expenditures.

Banks have a considerable ability to use financial leverage compared to non-bank firms to earn high profits and returns with support of the central bank as a last resort lender. The ability of banks to use leverage depends on internal characteristics such as size, profitability and risk, as well as environmental variables such as inflation, which affect the Business cycle. This study aims to find the effects of these variables on the dependency of banks on financial leverage in recession and booms periods. To this end, Hodrick-Prescott filter was used to extract business cycles. The Generalized Method of Moments (GMM) based on the data from 18 Iranian banks during 2005-2018 was used in order to test the research hypotheses. The results show that larger banks are more inclined to leverage and economic conditions have no significant effect on this desire. Banks with better financial stability and less risk rely on lower financial leverage in times of economic prosperity. The effect of profitability criteria on the leverage of banks depends on economic conditions. In times of economic prosperity, banks with better profitability have a higher incentive to leverage. Also, how the inflation affects the financial leverage of banks depends on the economic conditions. During an economic boom, inflation encourages more reliance on leverage in banks.

This paper, at first, examines the determinants of the labor income share (LIS) and second calculates the own, cross, and output elasticities of the labor force demand for three sizes of firms in Iran’s industry: 10-49 employees, 50-99 employees, and more than 100 employees. Since the dependent variable was limited to the interval 0 and 1, a Fractional Panel Probit technique has been used for the period 2004-2014 and provincial level. The findings from the first section of all groups showed that the relation between labor share income and wages, capital prices, and the ratio of skilled to non-skilled employees is positive. Labor income share is reduced by increasing real output, tax, the premium paid, and the value of raw materials. The share of labor income is reduced by increasing production can make sense that the rising in production is more capital-intensive than labor-intensive, and leads to a reduction of the labor income share. In the second part, the own wage elasticity was negative for all groups. The relationship between labor and capital price was positive that implies substitution elasticity between them. There is a positive sign for output-employment elasticity. The nonlinear relationship among the elasticities is consistent with our finding that within all groups, small and large firms have more own and output elasticities. There is a U-shape relationship between firm size and elasticities. In reverse, cross elasticity is high for medium-firm size. Based on research results and since the labor market of Iran is suffering from labor demand shortage, some suggestion to the economic policymaker may be helpful such as applying appropriate facility to increase industrial growth, eliminating production barriers, reducing the risk of investment, and improving human resources skills following the requirements of industrial sectors.

There are numerous and conflicting views on the impact of corruption on economic growth. A number of humanities scholars have described corruption as a good phenomenon and called it the grease wheel of the economy, and they believe that financial corruption improves the weak economic institutions, and by that means , The growth rate of the economy will increase. On the other hand, some scholars have emphasized the undesirable nature of corruption and considered financial corruption as the economy's sand and argued that corruption is costly and costly, and the ineffectiveness of the administrative process and the transfer of resources to non-productive activities is eroding economic growth.This paper studies the impact of corruption on the growth of the Iranian economy from 1983 to 2014 by using the talent allocation approach and by applying the econometric method of equation system. The divergence in talent allocation has slowed the growth of the Iranian economy in of these years.

In this paper, with the purpose of better understanding of the relationship between education and the employment of women with their divorce, the socio-economic factors which affect on divorce are investigated in the provinces of Iran by using the micro data of Household Expenditure and Income Survey in 2014 which covers 18885 households and the application of pseudo-panel data method. At first step, a subset of the data was collected include male and female who were divorced or married (16503 breadwinner) and categorized them on the base of the provinces. Data was analyzed based on the initial classification. Then On the base of Deaton(1985), and Goaed and Ghazouani (2001) the logit model of this research with pseudo-panel data and including explanatory variables; household size, the occupation of the head and his/her literacy and household income, age and age square of head, with emphasis of female education and occupation; was regressed by using the Maximum Likelihood method. On the base of results, household size, the occupation of the head and his/her literacy and household income reduces the probability of divorce, while the effect of women's higher education on the probability of divorce is positive. Also, the relationship between age and divorce is U inverted. It means in the early years of their household common life, and in the latter years, the probability of divorce is less than the average age of the head of household.

Poverty, as a socio-economic problem, prevents societies to attain sustainable development and growth. Therefore, poverty reduction is one of the objectives of developing countries. Knowing the status of poverty and its determinants is essential for the successful implementation of poverty reduction policies. Therefore, in this study, after the calculation of the relative poverty line in the urban and rural areas of each province by using the micro data on the income-expenditure of 38303 households gathered by the statistical center of Iran in 2013, the poor families were identified. On the basis of the initial processing of the data, it is recommended that poverty alleviation programmers pay attention to spatial planning. In the next step, to examine the effective factors in the probability of going out of poverty, the model was estimated with the maximum likelihood method. The results of the regression logit model based on pseudo-panel data with random effects showed that female-headed households are supposed to be in poverty more than males. Also, variables such as the education level of the head, statement of his or her income, and the number of the educated and the number of employees in the household have a significant effect on the probability of going out of poverty. Being in poverty is strongly associated with household size and living in urban areas. The effect of the head’s age on poverty is U shaped. It means, when the head is young, the probability of being poor is low. On the other hand, when the head is in pension years or old ages, the probability of being poor is high. Therefore, in poverty eradication programs, the government should pay attention to the elderly, especially females who head households with no income.

This paper examines the own and cross price elasticities of the labor force demand for two size firms: 10-49 employees and more than 50 employees. Estimation of elasticities is done in two steps: firstly, the effect of some variable will be regressed on labor income share. In second step, by using of previous estimation, own price and substitution elasticities of the labor will be calculated. In this study, for estimation, the Fractional Panel Probit technique has been employed for the period of time from 2004 to 2014 and at the provincial level. The results of estimation for both groups shows a negative relationship between tax, value of raw material and premium paid with labor income share. There is a positive sign for output-employment elasticity. The results show own price elasticity is negative and cross elasticity of capital price and labor demand reveals a substitution effect in small firms. As Iran’s labor market is suffering from labor demand shortage and high unemployment, it is suggested that the economic policymaker should eliminate production barriers, care about increasing production capacity and facilitate the supply of raw materials.

The asset price bubble is the deviation of the asset price from its fundamental value. The price bubbles usually have common features. On one hand, providing excessive loans and facilities along with continuous raises in demand and asset price cause an inflation in price bubbles. On the other hand, the bubbles burst and the asset prices collapse because of abundant sales. Since many of the financial crisis arise from bursting bubbles of financial assets, exploring the bubbles behavior in these markets and the early detection for the prevention of adverse economic consequences is important.
Generally, the correct detection of assets price bubbles is complex and difficult due to uncertainty in accurate identification of the fundamental factors and their randomness. Especially, if the bubbles were inherent and dependent on fundamentals, the correct specification of the bubble equation will be more difficult. Many of the methods used for testing the price bubbles, have been criticized for various reasons. In this line, the present study has used Sigma-Point Kalman Filter (SPKF) to measure the price bubbles in the non-official foreign exchange market of Iran during the period of 2002:04-2015:09, forming a nonlinear state space model. In this paper, to derive the state-space model, the presented value model with variable discount rates was used as a start point. After solving this equation, the asset price includes two components, the fundamental value and the non-fundamental value or the speculative bubble. By applying the transversality condition, we obtain no bubble solution. The fundamental value is affected by market fundamentals and is expressed as the sum of the asset’s expected future dividends discounted to the present time. But, if the transversality condition be violated, this equation is the only solution for main equation.
The price bubble can be a function of fundamental factors. In addition, the relationship between the expected bubble and the current bubble values follow a nonlinear process.
If prices and fundamentals have unit root, we can write the general solution in differences. Since the bubble is an unobservable component, we regard it as a state vector and estimate it in a state space model. In addition, because fundamentals and price are observable, we consider them as observation vectors in signal equation. We assume the fundamentals follow an ARIMA (h, 1, 0) process, where h is determined empirically.
In the present study, we apply the Sigma Point Kalman filter (SPKF) for foreign exchange market in Iran. In this regard, we have taken consumer price index and real interest rate as fundamentals in nonofficial exchange rate of Iran. After specifying the state space model, this model is estimated using the maximum likelihood method. Then, we extract the bubble component using SPKF algorithm and by the MATLAB software. In order to identify the series of foreign exchange market bubbles, we have followed the SPKF methodology to detach the bubble component from the fundamental component in exchange rate. Since price variables are nonstationary in level, but stationary in first difference, we are capable of separating the bubble component of a change in the exchange rate from its fundamental components.
Regarding SPKF model estimation for the period of 2002:04 to 2015:09, most of the bubbles in exchange rate changes have been compressed at the 2012m09 so that about 61 percent of the exchange rate change can be attributed to the bubble component. Moreover, it can be seen that the non-official exchange rate of Iran in the 2000s had a very mild rising trend and slight volatilities. However, in the 2010s, at the same time with the intensification of economic sanctions, the decline in foreign exchange earnings and the rise in inflation, the exchange rate has experienced a significant growth. In this paper, we applied a Sigma-Point Kalman filter (SPKF) to extract the bubble term from exchange rate changes in non-official market of Iran during 2002:04-2015:09.The results showed that the significant part of the exchange rate changes, especially during 2010s, have been due to the formation of price bubbles. In this framework, the highest share of bubbles in exchange rate changes has been related to 2012:10 so that about 61 percent of the increase in exchange rate in this month compared to the previous month have been attributed to price bubbles. Moreover, in 2015, the exchange rate bubbles have been very insignificant and the market value of the exchange rate has been close to its fundamental value

This paper proposes a new unit root test against the alternative of symmetric or asymmetric exponential smooth transition autoregressive (AESTAR) nonlinearity that accounts for multiple smooth breaks. We provide small sample properties which indicate the test statistics have good empirical size and power. Also, we compared small sample properties of the test statistics with Christopoulos and Leon-Ledesma (2010) test. The results indicate that our unit root test approach is superior to the test method of Christopoulos and Leon-Ledesma (2010) for both transition parameters (i.e. slow and fast speed), and the test power increases along with the frequency. We apply our test statistics for examining the real interest rate parity hypothesis among OECD countries.

The purpose of this article is to analyze the macroeconomic impacts of fiscal policy in Iran using a new-Keynesian Dynamic Stochastic General Equilibrium (DSGE) model. The model takes into account distortionary taxations on wage, dividend, and consumption, while government expenditures are broken down into consumption of goods and services, and investment. The model is calibrated for Iran based on the estimated parameters by Bayesian method. To do so, a data set from 1981 to 2016 is used. The impulse response functions illustrate that an increase in consumption tax rate has a larger impact on the contraction of the economy than wage tax rate whereas the expansionary effects of government investment is much larger than government consumption expenditures.

This paper has examined the effect of corruption on the allocation of talent in Iran's economy during the period of 1984-2014 and for discovering the effect of unobservable factors as well as political, social and economic structural changes, the structural time series model approach has been used. The results of the research indicate that increasing in corruption, financial development, growth of consumption government size and the share of value added of services sector in the GDP have distorted the allocation of talent in Iran during the period of 1984-2014