دکتر کامبیز هژبر کیانی

In order to evaluate the productivity of banks, it is necessary to measure the efficiency of banks. Therefore, in this research, productivity and factors affecting it were investigated in the Tose’e Ta’avon Bank and its selected branches.Methodology. The marginal cost function approach was used to measure productivity. Also, to investigate the factors affecting productivity in the bank, the autodistribution method with extended intervals (ARDL) and the generalized moments method (GMM) were used in selected branches during the monthly period of 2011-2018.Findings and Conclusion. Productivity in Tose’e Ta’avon Bank fluctuates a lot. The long-term coefficient estimated for the variable of personnel cost and doubtful receivables is negative and significant, and current facilities, internet bank, mobile bank and POS transaction are also positive and significant. Productivity in branches is different in different years. The effect of the two variables of current facilities and doubtful receivables is meaningless, and the effect of the variables of negative personnel costs and ATM and POS transactions is positive and significant.Originality. Previous studies have focused on examining productivity in banking; However, few studies have investigated the productivity of the Tose’e Ta’avon Bank and its selected branches.Limitations: The results of this research are limited to the Tose’e Ta’avon Bank and can be interpreted with caution in the context of other private and public banks.Practical impilications: The results can help bank managers to find solutions to improve productivity, reduce costs and increase bank profits, and analyze various processes and apply the necessary improvements.

Investment is one of the main component of aggregate demand in economy which plays a crucial role in the economic fluctuations and economic growth of each country So economist and policymakers focused on interpret of Investment behavior.  One of the most important factors in the decision to invest in both domestic and foreign investment is the existence of a secure environment. in other words, the most important factors is the proper investment environment and what has been interpreted as the ease of doing business. In such a way that improving the ranking of countries in business environment indicators is one of the prerequisites for attracting domestic and foreign capital and as a result investment. The main goal of this study is to investigate the effect of indicators of ease of doing business and domestic investment on foreign direct investment in selected countries. For this purpose, based on the division of the World Bank, four groups of countries are considered by their income level, including low-income countries, lower middle-income countries, upper middle-income countries and high-income countries, and the effect of domestic investment and indicators of ease of doing business have been evaluated using a Panel data model. The result shows that the level of development of countries and their income influences the magnitude and effect of domestic private investment and indicators ease of doing business on FDI. In a low-income, lower middle income and high-income countries, the effect of investment on foreign direct investment is positive, and in the upper middle countries, this has a negative effect. Meanwhile, the effect of each indicator of ease of doing business on foreign investment varies depending on the income level of countries.

One of the most important risks faced by financial institutions is credit risk, which is formed by the possibility of the receiver's default in repaying the loan or repaying the loan on time. One of the pivotal financial institutions in Iran's economy is the Export Guarantee Fund of Iran. Being the exclusive official export credit insurance entity in Iran, it operates under complete government ownership, shouldering all obligations associated with the fund's coverage. Over the past decade, the Export Guarantee Fund of Iran, the sole provider of export guarantees in the Iranian economy, has undertaken the risk amounting to approximately $15.8 billion through the issuance of diverse guarantees and insurance policies. The most significant volume of claims pertains to credit guarantees. Based on available statistics and official records within the Iranian entity, it can be observed that between the Iranian calendar years of 1387 and 1397, this fund issued guarantees totaling $6.7 billion, with the largest claim, exceeding $317 million, originating from the credit guarantees provided for the benefit of creditors. Recognizing the significance of this matter, the development of an optimal model for evaluating the credit guarantees provided by customers of the Export Guarantee Fund of Iran holds the potential to mitigate credit risk and subsequently decrease the fund's incurred losses. Even a one percent reduction in the fund's losses could result in substantial savings, amounting to at least 1,330 billion Rials. This figure is poised to grow even further as the fund increases the issuance of credit guarantees. Consequently, the primary objective of this research is to identify the most effective method for distinguishing between creditworthy and high-risk customers, ultimately diminishing the default rate of loans extended by the Export Guarantee Fund of Iran.

In this study, an artificial neural network model was employed to create a risk assessment framework for applicants seeking financial facilities and guarantees from this fund. This model exhibits exceptional predictive capabilities, especially in estimating the likelihood of default for the granted facilities. To achieve this objective, a dataset comprising 2,170 credit files granted by this fund was utilized. A total of 69 intra-organizational and extra-organizational variables were initially considered, and their respective information was gathered. Subsequently, six key variables were employed in the ultimate neural network model, encompassing the credit recipient's province, the guarantee beneficiary (creditor bank), personnel count, current ratio, real interest rate, and economic growth rate.

Based on the neural network model, the best models were extracted with three methods Bayesian, Levenberg, and Conjugate Gradient, and with one to 30 neurons in the hidden layer. The best model with all independent variables (i.e., 69 independent variables) was predicted with 96.2% accuracy, which is more than the Probit econometric model.

The findings of this research offer the capability to distinguish between customers with favorable and unfavorable credit profiles. Furthermore, the credit rating of customers can be used as a basis for adjusting the collateral requirements for each customer group, thereby aligning the collateral amount with the creditworthiness of the respective groups. This means that if the customer is one of the customers with good credit and a good credit rating, less collateral can be obtained from them, and if the customer has higher credit risk, more collateral can be used as a guarantee of the repayment obligation. In this case, while measuring the credit risk and separating customers, it is possible to manage the risk and the credit portfolio of the Export Guarantee Fund of Iran optimally.

Housing, as an asset and shelter after food and clothing, is the most basic human need, which is very important for the life and survival of the individual as well as for the society. Changes in housing prices, on the one hand, as the main asset in households' portfolios, will lead to changes in individual wealth over time, and on the other hand, fluctuations in housing prices, especially their rapid increases, are among the threats that governments aim to provide access to. People face challenges in housing. This issue has become more important especially in recent decades with population growth, urbanization and the formation of new families. Air pollution as one of the most important environmental concerns of this century and the result of increasing population and urbanization and housing construction threatens the lives of millions of people in developing countries as well as in developed and industrialized countries. Therefore, considering the importance of air pollution and its impact on housing and housing prices, this research tries to use the panel data technique of the effect of air pollution on housing prices in developed countries (including: Norway, Switzerland, Australia, Iceland, Denmark, America , Japan and the Czech Republic) and developing countries (including: Turkey, Mexico, Brazil, China, Colombia, South Africa, Indonesia, India) during the period of time (2010-2017) and then this review for Iran using self-explanatory vector technique with extended non-linear intervals (NARDL) and during the years (1375-1996).

As mentioned in the introduction, the purpose of this research is to analyze the impact of air pollution and some economic variables on housing prices in developing countries, developed countries and Iran. For this purpose, the following model has been used:Which in this model: Logarithm of housing price in year t.Logarithm of air pollution index in year t.Logarithm of per capita income in year t.Logarithm of liquidity in year t.Logarithm of the price index of consumer goods and services in year t.Logarithm of exchange rate in year t.Interest rate in year t.It is important to mention two points here: First, the index considered for air pollution is the amount of suspended particles PM2.5. Second; The base year is 2010 for developed and developing countries and 2010 for Iran. The desired statistical information, which is in the form of a time series, was collected through the information portal of the World Bank, the International Monetary Fund, the Organization for Economic Cooperation and Development, the Central Bank of Iran, the Statistical Center of Iran, and the energy balance sheet.

The impact of air pollution on housing prices in developed and developing countries:Due to the short period of time (due to the limited access to information) and the invalidity of the results of the unit root test in these conditions, in the first step, the problem of heterogeneity of units was investigated using the F-test statistic of Limer. Considering that the probability value of the F test for both groups of developed and developing countries is less than 0.01, therefore, Panel Data technique is used to estimate the model in both groups of countries. As the next step to examine the correlation between disturbance components and explanatory variables (i.e. choosing between the fixed effects method and the random effects method), the Hausman test was performed, and the results of this test indicated a probability value smaller than 0.01 for both groups of countries. Investigating and applying the fixed effects method.The results of model estimation are as follows:In developed countries, air pollution leads to a decrease in housing prices by 30%. But in developing countries, there is no significant relationship between air pollution and housing prices. The effect of per capita income on housing prices is positive and significant in both groups of countries under investigation. The effect of liquidity on housing prices is positive and significant in developed countries, but the effect of liquidity on housing prices is not significant in developing countries. Considering the relative stability of the consumer goods and services price index in developed countries, this index has no effect on housing prices in the aforementioned countries. In developing countries, the effect of the price index of consumer goods and services on the price of housing is positive and significant at the rate of 48%.The stability of the exchange rate in developed countries has caused this variable to have no significant effect on housing prices. But in developing countries, an increase in the exchange rate causes a 4% decrease in housing prices. The increase in interest rate causes the housing price to increase by 0.5% in developed countries and decrease by 0.2% in developing countries.The impact of air pollution on housing prices in Iran:As the first step, the variables used in the model were tested for reliability. The results of the ADF unit root test showed that all the variables investigated in this research were I(1) and this means that the vector self-explanatory model with wide ARDL intervals is a suitable method for analyzing the short-term and long-term behavior of the variables in this research. Then, in order to check the classical assumptions, relevant diagnostic tests were used, and the obtained results indicated that the model does not have any problems in terms of the classical assumptions, that is, there is no autocorrelation and heterogeneity of variance, and the distribution of disturbance components is normal.The results of model estimation are as follows:The effect of negative and positive air pollution shocks on housing prices is significant, which means that the decrease in air pollution leads to an increase in housing rent and an increase in the level of air pollution leads to a decrease in the housing rent index in Iran. An increase in per capita income leads to an increase in housing rent index. The variable coefficient of liquidity logarithm is negative and meaningless. An increase in the price index of consumer goods and services and the exchange rate will lead to an increase in housing rent. The results of the model estimation indicate the insignificant effect of the interest rate of this variable on the housing rental index in the long term, but in the short term, with the increase in the interest rate, the demand for housing rent and consequently the rent will increase.

Based on the results obtained in this study, the effect of air pollution on housing prices was negative and significant in developed countries, while this effect was insignificant in developing countries. The results of the model estimation in Iran show that air pollution has a significant effect on housing rent.According to the obtained results, the following suggestions are presented in order to control housing prices:Stability of prices and prevention of excessive growth of the price index of consumer goods and services through control of liquidity and exchange rate.Exchange rate management: Since the fluctuations and instability of the exchange rate can leave destructive effects in the economy of the countries, therefore, the forecasting and use of tools that enable the economy of the countries to face the fluctuations of the exchange rate should be considered.

The present study, in the form of a state-dependent model and during the period 2001:6-2019:12, investigates which of the components of monetary aggregates has the greatest impact on real exchange rate volatility of Iran. In order to achieve this goal, the variables of money, quasi-money, liquidity and monetary base are considered as monetary aggregates and in order to avoid multicollinearity between monetary aggregates, four Markov Switching Exponential GARCH models with fixed transition probability are estimated. The findings of the study also indicate that in both low and high regimes of real exchange rate volatility, monetary aggregates have a positive and significant effect on real exchange rate volatility and the effect of monetary aggregates in low regime of real exchange rate volatility is different from the high regime, so monetary variables have an asymmetric effect on real exchange rate volatility. In addition, in both the low and high regimes of real exchange rate volatility, the monetary base had a greater effect on real exchange rate volatility than other components of monetary aggregates. Therefore, controlling the components of monetary aggregates, given the importance of each in the up and down state of real exchange rate regime, can be considered as a strategic point by economic policymakers.

This article examines the non-linear effect of inflation on the economic growth of Iran, Algeria, Saudi Arabia and Nigeria. So far, there have been many studies in the field of economic growth, in which different estimation methods have been used. The dependent variable of this research is GDP per capita as an indicator of economic growth, and the variables of inflation rate, investment, labor force, income from oil export and government expenditure have been used as explanatory variables. In the current study, using the non-linear distributional autoregressive model (NARDL) with the bound approach, the effect of inflation rate on the economic growth of the countries under investigation has been investigated asymmetrically. In this project, the positive changes in the inflation rate are shown with the POS variable and the negative changes in the inflation rate are shown with the NEG variable. The research period is 1990 to 2019 and the data are annualized. The results of Curran's test indicate the existence of a long-term relationship between research variables. The results in the case of Iran show that the variable coefficient of NEG is negative and significant, and the variable coefficient of POS is meaningless. In the case of Algeria, both coefficients of NEG and POS variables are negative and significant. For Nigeria, POS variable coefficient is negative and significant, but NEG variable coefficient is meaningless. Therefore, for all three countries of Iran, Algeria and Nigeria, the effect of inflation rate on growth is negative and due to the different coefficients of NEG and POS variables, this effect is non-linear. In the case of Saudi Arabia, both coefficients of POS and NEG variables are meaningless.

The economy of many countries around the world is now dependent on commercial activities in ports. Although ports are considered among the most important transportation infrastructures that can greatly affect economic growth, less attention is paid to ports and their relevant commercial activities in Iran. This study used the mixed-data method to address this issue by reviewing the data related to Khuzestan, Bushehr, Hormozgan, Sistan and Baluchestan, Guilan, and Mazandaran provinces of Iran in the period 2005-2017. The results showed that the operating capacity of ports exhibited a significant and positive effect on the economic production of the studied provinces. In addition, the uploading and offloading volume showed a significant but nonlinear effect on the economic production of hosts. In other words, the economic production increased with the increase in the operating capacity of ports but further increase in the operating capacity beyond the critical point negatively affected economic production. The study findings also indicated that human development, economic growth rate at the beginning of the studied period, employment, government investment in ports, government’s working budget, technology, manufacturing structures, and urbanization rate had positive and significant effects on the economic production of the studied provinces.

The main goal of this research is to examine and test the asymmetric effects of monetary policy on the production of Services. For this purpose, hidden cointegration analysis and Autoregressive distributed lag (ARDL) approach in Iran's economy have been used in the period from 1353 to1399.Hodrick Prescott filter was used to extract the positive and negative impulses of the liquidity variable. Then, the effects of positive and negative impulses of the variables were investigated separately on the positive and negative impulses of the production of this sector with latent cointegration analysis. In the last step, the long-term relationship between the variables is checked and the long-term coefficients are calculated using the auto-regression model approach with non-linear distribution intervals and the bounds test. The results showed that there is a hidden co-accumulation between the time series of M2 and production in the industrial sector.The results showed that there is a hidden cointegration between the time series of M2 and production in the Services sector. So that the positive components of the M2 and production in this sector have a long-term relationship with each other, as well as their negative components. Also, the effect of the positive shocks of M2 is greater than the negative shocks of this variable. Therefore, the existence of asymmetry in monetary policy was confirmed.

With having 80 percent of world trade, ports nowadays are the most important national and international window towards trade. Despite their Increasing importance in development of transportation, ports and the relevant activities are completely neglected in Iran. Significant relationship between ports development and their capacity and throughput drive an important question: what is the net effect of port throughput on the host areas growth? The present study analyses the question using data of six provinces including Khoozestan, Booshehr, Hormozgan, Gilan, Mazandaran, and Sistan and Baluchestan during 2005-2017 (1384-1396). Results show that ports capacity, human development, economic growth at the initial period, employment, government investment in ports, government's current budget, wage, technology, production structure and urbanization have significant positive impact on economic output of the provinces while the transportation cost has a negative one.

The industry sector is one of the most important and influential sectors in the economy of any country. Information and communication technology can be effective on all types of productivity in industries through infrastructure channels. Iran, as a developing country, seeks to improve productivity due to its special conditions. In industries, in order to use limited resources more and more efficiently, so that by increasing its competitive power, it can be successful in competing with global markets and international arenas. Therefore, the purpose of this research is to investigate the impact of information and communication technology on the productivity of all production factors.capital productivity and labor productivity in factory industries of Zanjan and Qazvin provinces This research in terms of its practical purpose and its time period includes the years 2006-2016. The statistical population also includes factory industries with 10 workers and above in the two provinces of Zanjan and Qazvin. The relevant data is based on the latest published information of the four-digit isic codes of the industries. Factories with 10 or more workers in two provinces have been collected from the Iranian Statistics Center. The research hypotheses were tested through panel data using the Cobb-Douglas production function and estimated by Ols method by Eviews econometrics software. The results of this study show that Fawa does not have a significant effect on capital productivity and labor productivity in two provinces, but it shows a negative and significant effect on the total productivity of production factors in two provinces. Therefore, in order to increase the level of production and improve productivity, different industries should include in their long-term plan by preparing the necessary infrastructure for the introduction of technology suitable for the conditions and structure of the industry and providing new courses to prepare the specialized workforce with new technologies.

One of the important and effective success factors in development planning is the knowledge of the structure and potential of different sectors in the economy. Transportation, warehousing and communication sub-sectors are among the sectors of the country's economy, which have a significant share in the gross national product, and therefore, the factors affecting its added value should be considered by economic policy makers. On the other hand, in the direction of formulation and macro-economic decisions, the amount and direction of influence (symmetry or asymmetry) of monetary policies, including changes in the volume of liquidity, on macro-variables has always been the concern of economic policymakers. Therefore, in the upcoming study, we will dynamically examine the direction and degree of influence of the added value of the transportation, warehousing and communication sub-sector from asymmetric changes in the volume of liquidity using time series data annually during the period 1363 to 1398 and for For this purpose, the autoregression model with non-linear distribution breaks and the edge test approach have been used. The results show that there is a long-term relationship (collinearity) between the variables of the model, and the shocks of changes in the volume of liquidity in the studied model have an asymmetric effect and have larger coefficients in the long run. Based on other research results, the interest rate of bank loans on the added value of this sub-sector is positive and significant, and the elasticity of the added value of the mentioned sub-sector in the investigated model is higher than the interest rate of bank loans in relation to the changes in the volume of liquidity in the short and long term.

The main goal of this research is to examine and test the asymmetric effects of monetary policy on the production of industries and mines. For this purpose, hidden cointegration analysis and Autoregressive distributed lag (ARDL) approach in Iran's economy have been used in the period from 1353 to1399.Hodrick Prescott filter was used to extract the positive and negative impulses of the liquidity variable. Then, the effects of positive and negative impulses of the variables were investigated separately on the positive and negative impulses of the production of this sector with latent cointegration analysis. In the last step, the long-term relationship between the variables is checked and the long-term coefficients are calculated using the auto-regression model approach with non-linear distribution intervals and the bounds test. The results showed that there is a hidden co-accumulation between the time series of M_2 and production in the industrial sector.The results showed that there is a hidden cointegration between the time series of M_2 and production in the industrial sector. So that the positive components of the M_2 and production in this sector have a long-term relationship with each other, as well as their negative components. Also, the effect of the positive shocks of M2 is greater than the negative shocks of this variable. Therefore, the existence of asymmetry in monetary policy was confirmed.

The aim of this study is to investigate the short-term and long-term asymmetric effects of exchange rate on Iran’s gross domestic product (GDP). Considering the importance of the issue in policy making and the possibility of influencing production through exchange rate, in this study, the effects of positive and negative exchange rate shocks on Iran's GDP in the short and long term with nonlinear distributed autoregressive lags (NARDL) have been investigated in the period of 1991 to the fourth quarter of 2018 and the "Shine et al" model is the main basis of the research. For this purpose, using explanatory variables of liquidity volume, exchange rate, degree of openness of economy, gross domestic capital stock, labor and oil prices, through band test confirms the existence of a long-term asymmetric equilibrium relationship and also confirms the results of asymmetric relationship between real exchange rate and GDP. In the short term, the decrease in real exchange rate leads to an increase in GDP and an increase in the exchange rate has negative and significant effects on GDP, and in the long run, the severity of negative shocks has been more than positive shocks, this effect has been positive and asymmetric.

Fertility rate as an effective factor in population change is of great importance in all societies. In this article, using the information of household income and expenditure plan in 2017 of Iran Statistics Center and using the Poisson method in Stata software, the effect of women's employment on fertility has been investigated. The estimation results show that women's employment has a negative and significant effect on fertility; in such a way that their employment reduces the size of the household by an average of 7%. Age and education variables also have a negative effect on the household dimension. Although the coefficient related to the income variable is positive and significant, its smallness indicates a very insignificant effect on the household dimension. The variables of educational expenses and religious expenses also have a positive and very strong effect on the household dimension. The virtual variable of urban and rurality of the household did not have a significant effect on the size of the household; therefore, it seems that the larger size of rural households is explained only through other variables of the model, especially the employment of the woman and her education.

This paper attempts to explain the importance of small and medium-sized enterprises in the economy and to highlight their main facing challenges, in particular the “financial challenge". The present paper seeks to analyze the impact of small and medium-sized industries on the growth of industrial value added in Iran’s economy for 22 ISIC codes during the period of 2005-2014.The main findings of this study indicate that the growth of value added of small and medium-sized industries has a significant positive effect on the growth of value added of industries with ten employees and more; the growth of innovation level in small and medium-sized industries may have a significant positive effect on the growth of value added of this group of industries, and the growth of openness of Iranian economy can affect the growth of value added of industries with ten employees and more, positively; but it has a negative effect on the growth of value added of small and medium-sized industries. Furthermore, it is suggested that in order to boost and facilitate the economic activities of small and medium sized enterprises, several issues should be considered including“promoting the non-bank financing methods”, “providing effective support for innovative projects”, “implementing industrial export development programs”, and “providing industrial advisory services, in particular financial advisory services”.

The main purpose of this article is to investigate the return of scale indicators,technological changes and productivity growth rate on the cost in Shazand CityWater and Wastewater Company. For this purpose, based on repetitive seeminglyunrelated Regression, translog cost function form was used to estimate water supplycost function. Cost function parameters were estimated from seasonal time seriesdata over time period 2008 to 2018. The company used four factors of production,labor, capital, raw materials and other services in the production process. The resultsshowed that there is a diminishing return to scale and a lack of economies of scale,which means that there is no natural monopoly in the company. Technologyprogress and productivity growth indicator indicates that cost reduction as a result oftechnology progress and productivity growth over the study period.

The successful experiences of developed countries in applying fiscal policies to overcome the financial crisis of 2008 led to the fact that in developing countries considered impact of fiscal policy, also. Fiscal policy instruments (especially government expenditure) should attract the attention of policymakers and economic theorists in order to increase economic growth and exit the recession. The purpose of this study is to estimate of government expenditure Multiplier and to examine the effect of government expenditure shocks on GDP in Iran's economy and comparative comparisons with selected countries. In this regard, used for selected countries, the Panel Vector Auto Regression (PVAR) and Iran's economic Vector Auto Regression (VAR) model and computed the government expenditure Multiplier for each of them (in Iran (1985-2015) and selected countries (2000-2015)). The results show that a government expenditure shock in Iran and selected countries together initially increase of GDP and then a declining trend and moves in long run and the results of expenditure Multiplier confirming this. On the other hand, according to the results of the analysis of variance the high speed of the impact of government expenditure shocks on GDP is clearly visible

Production, including industrial and agricultural production, is not possible without the existence of economic infrastructure. Electricity plays an important role in the industrial development of countries due to changes in the industries and the conversion of mechanical to electrical power, the emergence of electric motors and the development of machine tools. Purpose of this article, comparative comparison of the effects of electricity consumption shocks on Environmental pollution and economic growth in IRAN and selected MENA countries.

The article is descriptive, analytical and inferential, to achieve this goal, the method has been used the PVAR approach during the period 2016-1992 as well as the country of Iran during the period 2016-1985 using the VAR method has been studied.

Electricity consumption, direct foreign investment, labor force and capital inventory have a direct and significant relationship with economic growth, but environmental pollution has a negative and significant relationship with Iran's economic growth.

the results indicate that the shock of increasing electricity consumption in selected MENA countries after an insignificant decrease in GDP per capita will increase proportionally in subsequent periods but in Iran, it grows very smoothly. The effect of this shock on carbon dioxide emissions in the countries concerned has been relatively mildly reduced, but in Iran, carbon dioxide emissions have been at a higher level than before.

Awareness of the structure and potential of different sectors in the Iranian economy is one of the important and effective factors for success in development planning. Service section is one of the most important section in a country’s economy that it operates as a development (growth) motor of other sections and its share is constantly increasing in the gross domestic product and development. Hence the effective factors on its added value has always been of interest to economists and politicians. On the other hand, investigating the direction and extent of the impact of liquidity changes on macroeconomic variables is always important to formulate and adopt appropriate macroeconomic policies. In this study, considering the share of service section in the gross domestic product (GDP) and employment in the Iran’s economy as well as liquidity volume mutations in the recent decade, we examine and analyze the direction and extent of the impact of value added of the service section from changes in the volume of liquidity by using time-series data on an annual basis during the period 1360 to 1395 dynamically. In this regard, the self-return model with Non-Linear Auto Regressive Distributed Lag (NARDL) and the threshold test approach has been used. The research outcomes confirm the existence of a long-term Cointegration between the variables of the model. Furthermore, the results show that liquidity volume changes’ shocks have a greater impact on the value added of the service sector in the long term. According to other research results, the effect of bank credit interest rate on value added of services sector is positive and significant and the attraction of value added of service sector is more than short-term and long-term interest rate of bank credits compared to changes in liquidity volume

Air transport is one of fundamental sub-sectors of transport services, which has a high value added and novel technologies. On the other hand, due to the importance of employment, this article examines the effects of factors of production on employment in the Iranian air transport industry. For this purpose, the CES function has been used to examine employment. Workforce is introduced as dependent variable and value added, wage and capital price are considered as independent variables in the model. Research period - years 1382 to 1397 (2003 to 2018) is considered as time series for the extracted data of the air transport industry of Iran and the mentioned Econometrics model is estimated by Autoregressive distributed lag model (ARDL( and with a boundary test approach. Boundary test result, confirms correlation among the variables, which shows long-term relationship between the research variables and this is interpretable. Result of the long term model estimation shows that the estimation index for the variables (value added, wage and capital price) are statistically meaningful and their values are 0.16, 0.62 and -0.23, respectively. Result of the long term model estimation shows that the estimation index for the variables (value added, wage and capital price) are statistically meaningful and their values are 0.16, 0.62 and -0.23, respectively.

Considering the importance and effectiveness of transportation in regional and local development in countries, this article examines the challenges and strategies for the development of the air transport industry as one of the sub-sectors of the transportation industry. According to the results of research, it can be concluded that the value added of the air transport industry and the level of wages and the price of capital as the price of factors of production in this sector are the most important factors in increasing production, employment and labor force in These sections are in Iran. This seems to be due to the fact that in the past few years, for various reasons, including international sanctions, the provision of foreign exchange resources, and the depletion of fleets and equipment in the air transport industry, the negative impact of the corona epidemic on the transportation economy Transportation, high investment has not been made in Iran's air transport sector, and due to the lack of sufficient capacity in this sector, in many cases, shortages can be observed. Therefore, the increase in value added in this industry leads to an increase in demand for labor and increases employment. On the other hand, because most of the people working in this sector are professionals and educated people, the added value that these people create is much higher than other sub-sectors of transportation. Therefore, aviation, while being one of the most important sub-sectors of services for regional and local economic development, has the capacity to invest in this sector, a significant increase in macroeconomic variables in the country, including employment create...

Air transport is one of the key sub-sector  of transport industry, which has a high value added and novel technologies. Taking into consideration the importance of the employment in Iranian economy, this research investigates the contribution of air transport industry to employment in Iran. In this research ,CES function is used to determine employment potential in this industry. This model considers workforce as dependent variable and value added, wage and capital price as independent variables  . Data time span covers the period 1382 to 1397 (2003 to 2018). The Econometric model is estimated by Autoregressive distributed lag model (ARDL( subject to a boundary test approach. Boundary test result confirms correlation among the variables,which indicates interpretable long-term relationship between the variables . Result of the long term model estimation shows that the estimated coefficients for the variables (value added, wage and capital price) are statistically meaningful and their values are 0.16, 0.62 and -0.23, respectively.