زهرا (میلا) علمی

Economic stability via Information and Communication Technology (ICT) has sparked interesting discussions among scholars. ICT plays a crucial role in realizing sustainable development objectives. Globally, the prospective advantages of ICT are widely acknowledged. Some research has solely emphasized ICT's role in mitigating air pollution, but the ecological implications of ICT have largely been overlooked. This article is pioneering in domestic studies of ICT's influence on ecological footprint. In addition, the present research uniquely computes the ICT index through the principal component method, distinguishing it from other ICT studies conducted within Iran. In recent times, the ecological footprint has been embraced as a broader gauge for assessing environmental damage. One reason for this choice is that other environmental harm indicators, such as air and water pollution, deforestation, and others, only represent a part of the total environmental degradation. However, the ecological footprint index incorporates diverse elements like agricultural lands, pastures, fishing areas, forests, carbon footprint, and constructed lands, hence offering a more holistic measure. Concerning the topic in question, it is evident from national studies that there has been little research on identifying the factors contributing to the ecological footprint.

In this research, we investigate the impact of the information and communication technology (ICT) index on selected oil-exporting countries' ecological footprint from 2006 to 2020. To do this, we use the generalized moments method. We extracted the model of this research from the studies of Higon et al. (2017) and Caglar et al. (2021) for carbon dioxide emissions. The variables of our study include the ecological footprint (as the dependent variable), the information and communication technology index (an explanatory variable calculated using the principal component analysis (PCA) method), and control variables such as GDP per capita, exports of goods and services, financial development, and economic Complexity Index which is chosen on the review of other studies. The data used for this study are taken from databases such as the World Bank and the Global Resource Footprint Network and the Atlas of Economic Complexity.
Discussion and

Given the challenges posed by global warming to current and future generations, this study aims to explore the impact of Information and Communication Technology (ICT) on the ecological footprint in chosen oil-exporting nations. This study studied the inverse U relationship of the information and communication technology index with the emission of ecological footprints from 2006 to 2020. The ecological footprint is an index of the amount of environmental pollution and a more comprehensive index than CO2. A data description was undertaken before estimating the model. The research model, built on theoretical underpinnings and past studies, was structured, and estimated by the Generalized Moments Method.The findings showed a non-linear connection between ICT and the ecological footprint in oil-exporting countries. ICT augments the ecological footprint per capita before a certain threshold, but it begins to diminish after that.The positive and significant coefficient of GDP per capita indicates the increase in ecological footprint per capita for the increase of GDP per capita. This result indicates that economic activities such as industrialization and development cause the exploitation of natural resources, which causes more pollution.Financial development has had a positive and significant effect on the ecological footprint. To prevent the destructive effect of financial development on the environment, governments in selected oil-exporting countries should develop financial markets in such a way that financial resources are available for investing in projects that help introduce clean energy technologies. The economic complexity index has had a negative and significant effect on the per capita ecological footprint. In fact, the expansion of economic complexity in the studied countries will lead to the reduction of the ecological footprint. According to the obtained result, the economic complexity index can be considered as one of the ecological footprint control factors; Therefore, the production of more complex goods that contain higher technology can lead to a reduction in energy consumption and ecological footprint; Therefore, governments can provide tax exemptions and subsidies for those companies that use new technology and clean energy, and also support knowledge-based products.The influence of goods and services exports on the ecological footprint has been negative and substantial. The significance of the quality and diversity of exported goods regarding environmental destruction has not yet been thoroughly considered. Therefore, the focus should be on enhancing the quality of export goods via cleaner production methods. Overall energy consumption should also be reduced in all countries, with policymakers prioritizing the use of renewable energy resources and promoting the reduction of fossil-fuel energy export products.The influence of urban population growth on the ecological footprint has been positive and substantial. Essentially, uncontrolled population growth, especially in developing countries, creates grave issues including scarcity of food, poor air and water quality, environmental contamination, degradation of the ecological structure, waste disposal problems, and high energy usage.

Education, especially in academic fields of basic sciences, technology, engineering, and mathematics (STEM), is one of the significant indicators of human capital. STEM represents the economy's capacity for innovation and creativity, which forms the core of economic growth. The current research used the model of Knowles et al. (2002), who have added gender inequality in education to the economic growth model of Mankiw, Romer, and Weil (1992), to investigate the effect of gender inequality in STEM and deal with the economic growth of Iran in the period of 1988 to 2020. In this study, due to the random nature of unobservable factors affecting economic growth such as technological progress, the structural time series econometric model (STSM) approach was used. The results of the estimation showed that the positive effect of women's enrollment in STEM on economic growth is greater than the effect of men's enrollment, and the increase in gender inequality in STEM has a negative and significant effect on economic growth in Iran. Therefore, adopting appropriate policies in the labor market to eliminate gender discrimination will lead to gender equality in the education of these academic fields; because the sustainable growth of the economy depends on the intertwining of labor market policies and other institutions, including educational institutions.

In this paper, the effect of social capital on the efficiency of government expenditures has been studied in the two sectors of education and health during the period 1364-1396. social capital has been estimated by The Multiple Causes-Impact (MIMIC) approach, and efficiency of government expenditures in both education and health is estimated by the Data Envelopment Analysis (DEA) and Bootstrap data envelopment analysis approaches. The effect of social capital on the efficiency of government expenditures are measured by the regression model of the deficit probe in both education and health.
 The results of estimating social capital show that the trend of social capital is declining by the method of  Multiple Indicators and Multiple Causes during the study period. Also, the efficiency scores of government expenditures has been measured by Data Envelopment Analysis and Bootstrap Data Envelopment Analysis in Iran. The results show that on average, public spending is inefficient in education and health.
Findings of the fractional probit model show, the effect of social capital is positive and significant on the efficiency of government spending in both education and health. The effect of per capita income, economic growth, government size, inflation and trade openness is different on efficiency of government expenditures in education and health sectors.
 For example, the impact of economic growth is positive on the efficiency of government education and health spending. While the effect of government size is negative on the efficiency of government education and health spending.

Today brain drain is considered a significant phenomenon in developing countries. Brain drain is particularly important for countries in the Middle East and North Africa that are less developed and face disadvantages such as low economic growth and high unemployment rates. Typically, elites and specialists from less developed countries migrate to more developed countries to use the facilities of destination countries. Given the importance of human capital in theories of endogenous growth, brain drain can have deleterious effects for countries of origin. Therefore, this study examines the effect of brain drain on the economic growth of selected countries in the Middle East and North Africa. For this purpose, panel data was used to examine the relationship between the variables during the period 2015-2000. The results of the research indicate that there is a negative and significant relationship between brain drain and economic growth in such a way that a one percent increase in brain drain, with the assumption of the stability of other conditions, averaged 2.5% of production growth. The results of the research indicate that there is a negative and significant relationship between brain drain and economic growth in such a way that a one percent increase in brain drain, with the assumption of the stability of other conditions, averaged 2.5% of production growth.

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.

This paper firstly investigated the affecting factors on labor income share, and in the second phase, by using the previous estimation, own-wage, cross, and output elasticity of the labor will be calculated. With regards to the fact that the dependent variable was limited to the interval 0 and 1, a Fractional Panel Probit technique has been used for the period of time from 2004 to 2014 and the provincial level for firms with having more than 100 employees. The results of the first phase represent, labor income share is increased by increasing wages and ratio of skilled to unskilled employees. If the value of the raw, premium paid and capital price increase, the dependent variable will rise. In the second part, according to the theoretical, the relationship between labor and wage was obtained negative. There is a positive sign for output-employment elasticity that was obtained 0.52. The results show cross elasticity of capital price and labor demand is negative and reveals a complementary effect. Based on research results and since Iran’s labor market is suffering from labor demand shortage and high unemployment, it is suggested that the economic policymaker should apply appropriate facility to increase industrial growth, eliminate production barriers, reduce the risk of investment and improve human resources skills in accordance with the requirement of industrial sectors.

One of the most effective ways of realizing social equity is to provide equal opportunities for individuals to access education and to achieve educational equity. An important aspect of educational equity appears in the labor market and by the end of the education.  The processes of finding a job in the labor market and wage determination guide the efforts of individuals for gaining effective education. If the labor market does not send appropriate signals to the education system, the allocation of resources in the education system would not be correct. In this paper, the relationship between educational inequality and employment rates in Iranian provinces is examined by using Generalized Momentum Method (GMM) for a panel data of 28 provinces during 1380 - 1392. The employment rates and Gini coefficients of education are calculated from the income-expenditure data, published by the Statistical Centre of Iran. The results of this study show that average educational Gini coefficient, educational inequality, in deprived provinces is higher than rich provinces; and there is a negative and significant relationship between employment rate and educational inequality. In all provinces the employment rates has increased while the Gini coefficients has decreased.

This paper investigates the effective factors on migration network formation among Ardabilian who migrate to Sari. Instead of using proxy variables for relationship, direct relational data are recognized by conducting survey. By employing the valuable data and based on econometric model of network formation and applying logit method for dyadic data, effective factors on network formation are studied. According to strategic view on network formation, it is expected that form a star shape network among migrants. Moreover, it is expected that migrants not only make connection based on strategic behavior, but also based on economic and social similarities. Therefore, variables such as time of arrival, distance at birthplace are used as explanatory variables as well as variables such as age, education and income as proxy for homophily are employed as control variables. Results show that time of arrival, distance at birthplace, age, education and income has significant effect on probability of making link.  Based on results, migrants don’t tend to linking with earlier migrants. The probability of linking increases among migrants who migrants between 6 to 28 years, specifically between 11 to 16 years. This means that earlier migrants are important in migrants’ network, but earliest migrants are not attractive for making connection.

We are embedded by our social networks. Social networks or connections has had important role in shaping of agents behavior. “While the importance of embeddedness of economic activity in social settings has been fundamental to sociologists for some time, it was largely ignored by economists until the last decade”.(Zenou, 2016). The role of social networks in shaping behavior and formation of networks has received increasing attention recent years. Some central questions in the area of economics of social networks are as follows. How agents are affected by their social networks’ member? How our connections can improve our output? Why there are different shape of networks? Which factors are important in formation of network? Which networks are efficient and stable? Migration, by nature, is a phenomena that is involved in relationship and contacts. In this regards, migration is an attractive area in economics of social network. While there are several economic theory about migration, from theories of initiation and perpetuationofmigration to theories of migration’s welfare effect, some economists has done research about economic, social and cultural assimilation of migrants. In this line of research, formation of migrants’ network is a new open issue. Which factors are important in formation of network of migrants? Which shape of network would emerge in short run and long run? And so on.
The paper aims to find essential factors which are important factor in shaping network. Moreover, optimal level of effort migrants to link with central migrant is investigated and developed to heterogeneity condition. To do so, a survey among Ardablian who migrated to Rasht is conducted and run dyadic regression based on theoretical background.
Theoretical Background, Method and data : Social network, as an unofficial institution, can improve our understanding from social and economic phenomena. Generally speaking, there are three scopes of research in the field of social networks. Network effect (also known as games on network), network formation, topology and structure if network are the ongoing area of research. The paper is categorized in the network formation scope. Network formation models are modeled by two different approaches: strategic network formation and stochastic network formation. Obviously, economists are more interested in strategic approach. There are different methods of model of strategic network formation. Table 1 shows a comprehensive classification of strategic network formation models.
Table 1- Strategic network formation models
Cooperative and Noncooperative models
Farsighted and Myopic models
Dynamic and Static models
Complete and Imperfect Information model
We followed Brueckner (2006) and Epstein and Heizler-Cohen (2016), which is a complete information, myopic and noncooperative model to as a basis for our econometric model. We applied logit method for dyadic data to detect effective factors on network formation. Based on our theoretical model, several variables such as time of arrival, distance at birthplace are used as explanatory variables as well as variables such as age, education and income as proxy for homophily are employed as control variables.
Finally, equation (1) estimated, following Fafchamps and Gubert (2007) method to correct standard errors to overcome inference problem.
Lij = a ¦zi-zj¦ (zi) ¦dij¦ 먨 (1)
Where zj and zi , dij and dij are nodes’ (migrants) specification (such as time of arrival), specification of link (such as distance at birthplace) and error term, respectively. Lij stands for relationship matrix, including 0 and 1.
Moreover, in order to focus on importance of time of arrival, two another form is specified. Equation (2) is a second degree model and equation (3) is a model with dummy variable for different time of arrival.
Lij = a ¦zi-zj¦ (zi) ¦dij¦ 獟鶊㶾먨 (2)
Lij = a ¦zi-zj¦ (zi) ¦dij¦ δD먨 (3)
It is noteworthy that, the models are reestimated after adding control variables such as differences in education, age, income as proxy for homophily. In order to gathering data, a purposeful questioner designed and a survey conducted among Ardablian who migrated to Rasht. Finally, 411 members and 400 links are detected.
As mentioned before, optimal effort of migrants to making link is investigated.
Bi=(P(esi,1))u P (esi,1)(∑h=2 P(esh,1)v)-esi,1 (4)
Where is cost or effort in a star network. P(esi,1 ) stands for the intensity (or strength) of the relationship between i and j depends on the investment e. Bj , u and v stand for benefit or payoff from the friendship, utility of making direct connection and utility of indirect links, respectively.
The optimal effort of individual i who is invested in the linking with the central agent can be obtained as follows:δBi⁄δesi,1 = 0 →δP(esi,1 )⁄δesi,1 = 1⁄u ∑h=N P(esi,1 )v (5)
In the formation of a star network, the intensity of the agents’ relationships with the central agent increases in every period not with homogenous utility but also with heterogeneity in direct and indirect utility.
Finding: According to our estimations, distance at birthplace (suggesting that migrants who are born in close by locality are more prone to making link), sum of arrival time and differences between time of arrive have explanatory power (Table 5, Panel a).
Moreover, according our second model estimation, squared arrival time has significant effect in linking. It means that there is significant U-shaped relationship between the probability of linking and time of arrival to destination such that new migrants prone to link with old migrants and also tend to making connection between themselves (Table 5, Panel b). Our final estimation shows that migrants are more likely to connects with their cohort (who migrants less than 5 years) and link with older migrants (who migrated more than 23 years) (Table 5. Panel c).Adding control variable does not have a significant effect on the mentioned results. In other words, although some our control variables are significant, the main finding does not change (Table 6, Panel a, b and c).
Results show that time of arrival, distance at birthplace, age, education and income has significant effect on probability of making link. Furthermore, there is a U shape relationship between probability of making link and time of arrival, which indicates tendency of migrants for linking to cohort migrant also earlier migrants. Another finding which stems from our contribution is that optimal level of effort increases in each period and this finding hold at special level heterogeneity.

This paper examines the own price and substitution elasticity of the labor force demand for small and medium scale firms in Iran's provinces. 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 result of estimation for both groups shows a negative relationship between wage and labor demand that is consistent with labor demand theory. There is a positive effect for output-employment elasticity. The other result shows Cross elasticity of capital price and labor demand reveals a substitution effect in small firms. The demand for labor is reduced by increasing in taxes and value of raw materials. 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.

 This paper tries to measure the index of corruption by the Multiple Indicators and Multiple Causes (MIMIC) approach in Iranian economy during the period of 1979-2014. For this purpose, the variables of growth of government size, type of governance system, political stability, the degree of openness and the oil rent as the causes of corruption and the variables of GDP growth and the ratio of savings to GDP as the effects of the corruption have been considered. The results indicate that the trend of corruption has been increasing in Iranian economy during the period of study.

Network of connections is an informal institution, which affects agents’ decisions as well as their outcomes. Dominant neoclassical paradigm has neglected the role of connections and links, due to its atomistic view, while social networks can play a crucial role with regards to economic and social phenomena, such as migration, job finding, crime network, learning, financial crisis contagion, microfinance, risk sharing and so on. In recent years, economic-social networks have attracted economists’ attention, nonetheless, for some reasons, it is not well considered in Iran yet. Accordingly, this paper aims to not only introduce some fundamental and mathematical concepts on economics of networks, but also review several central questions correspondingly. Indeed, all issues and topics can be categorized under the four following questions. How can analyzing structure and topology of networks help economic analysis? How does social network affect agents’ outcomes? How does social network form from economic point of view? How can one estimate such effects?

This study investigates the effect of volatility structural changes on the shock transmission and volatility Spillover between gold and stock markets in Iran during 2007-2013. For this purpose, firstly, we will detect the time periods of structural breaks in volatility of gold and stock returns endogenously using the standard and modified iterated cumulated sums of squares (ICSS) algorithm. Then, this information incorporates to model the volatility process. The application of bi-variate GARCH model in off-diagonal BEKK parameterization suggest that shock transmission and volatility spillover between gold and stock markets is bidirectional in Iran. Also, based on the present research findings, ignoring or incorrect detection of structural breaks mislead the researcher about the direction of volatility transmission between gold and stock markets.

The main purpose of this study was to evaluate the effect of financial development on income distribution in Iran using panel data of 28 provinces in the years of 1379 to 1385. For this study, data on the Gini coefficient, the growth rate of GDP per capita (GDP), government spending, inflation and financial depth variable and financial performance indicators were collected and organized. The model using static and dynamic panel models, generalized moments estimator (GMM), was estimated. The results show the depth of financial performance indicators, have a significant effect on reducing inequality in Iran. Government spending, unlike inflation rate, reduces inequality. Also in this study, the Kuznets inverted U relationship was confirmed in the provinces of Iran based on the results we can claim the role of financial development in reducing inequality.

In this paper, we analysis the dynamics of per capita income by using Carrion –i- Silvestre et al. (2005) stationary test over the period 1950-2008. We use the Madison historical data. The Results show that Iran economy experienced a golden period over 1955- 1976, and if this trend had been continued, Iran could be in high per capita income club countries. Because of economic policies after first oil shock, political – social changes in the1970s, the 1980-88 war with Iraq, economic sanctions and the oil price collapse in the year 1986, the GDP per Capita in Iran has fallen so much that if the Iranian economy were growing at an average rate of 4 % a year (economic growth in the 2000s), there would be a gap of 19 years between GDP per capita in 2008 and its forecast for this year.

In this paper, the effect of trade openness on growth is examined across the members of Organization of the Islamic Conference (OIC) by using convergence-growth equation and GMM-System dynamic panel data estimator over the period 1980-2009. The results show that the overall trade, the trade with non-OIC countries, and the investment in physical and human capital stimulate economic growth. In contrast, intra-OIC trade, population growth, government consumption expenditure, instability, inflation, and export of primary goods are the obstacles to the OIC economic growth. According to the results, multilateral trade under preferential trade agreement between Iran and the other OIC countries will not provide considerable achievements for economic growth of Iran. In summary, the OIC members are experiencing the natural resource curse.

In the last decades, the industrial structure of countries changed and the SME has become important in development strategy. Because of new industrial countries successful experiment, economic experts and policymakers believe that the cause of economic development of developing and developed countries is private sector and especially the SME. Surveys indicate that SME has an impact on economic growth via entrepreneurship, innovation and new job opportunity creation. Therefore, in Iran the more concern and attention is paid for the improvement of job creation via SME. Also, in Iran, the number of SME is high and more than half of employees work in the SME. Therefore, SME will play an important role in industrial and economic growth programs in the future. This paper studies the relationship between the number of SME and province economic growth by Panel data method by using the augmented Solow growth model. Findings based on provincial data during the (1383-1385) showed that there is the positive and meaningful relationship between SME and country economic growth. This relationship is a reason for the importance of this industry.

In this paper, income per capita convergence hypothesis is tested in selected OIC countries. For this purpose, we use the time series model and univariate KPSS stationary test with multiple structural breaks (Carrion-i-Silvestre et al. (2005)) over the period 1950-2008. The results show that most OIC countries could not catch up toward USA. Although because of some positive term of trade shocks, they experienced catching up process in some sub- periods, they did not have appropriate infrastructure as, they could not use these opportunities and escape lag deadlock.

This paper estimates the long term trend in Iran real GDP using a new econometric technique، Adaptive Least Squares (ALS). ALS is a special case of the Kalman Filter that allows for a time varying parameter model to be estimated relatively easily. The estimated trend is then used to estimate the output gap. According to results، coefficients of gaps in models with gap، are not significantly different from zero، thereupon model with intercept and trend and without any gaps have been tested. The output gap estimation that has been provided in this paper can be used in monetary policies. The comparison of results of ALS، OLS and HP filter shows that the ALS method provides a better estimate.

In this paper, we analyze the dynamics of income gap between 138 countries with USA by using time series model of convergence hypothesis and various panel unit root tests over period 1950-2008. All panel unit root tests don’t reject the null hypothesis of unit root. Univariate unit root tests results show that GDP per capita of South Korea, Switzerland, Austria, Lesoto and Hungry catch up with USA and GDP per capita of Syria, New zealand, and Jordan diverged from USA GDP per capita. The estimation shows that the breaks were clustered around specific dates, such as oil shocks or financial crises. Also,the results show that almost poor countries stay poor and almost rich countries stay rich yet. Only some countries same as South Korea, Hong Kong, Singapore, Taiwan, India, and China could escape lag deadlock and the countries e.g. Syria, Madagascar, Kenya, and Comoro moved into poverty trap. The distributions of GDP per capita in various years confirmed our results.

Economic growth and promoting the nation’s welfare is one of the main concerns of governments and policy makers. Also, the process of per capita income convergence indicates changes to countries welfare. In this paper, in order to realize the convergence process of Income per capita of Iran with income per capita of 129 countries we use the time series model and ADF unit root test with multiple structural breaks. The results of this study show that, first; in Iran the most important shocks occurred in the years 1966, 1973, 1977-1978, 1985 and 1997. Secondly, due to various shocks, Iran could not reach to specific steady state in per capita income. Thirdly, Iran could not escape vicious circles and converge to high level per capita income during 1950-2006. Although, due to the first oil shock, the level of per capita income increased, but the negative shocks in the later decades leads to not only a decrease in per capita income but also a divergence between Iran per capita incomes with high per capita income countries.

Oil price fluctuations are one of the most important causes of economic crisis among both oil exporting and importing countries. Hence, study of oil price shocks on economy of oil exporting countries which oil revenues is the intensive generator is so vital. In this study, the effect of oil shocks on economic growth in selected OPEC member countries is studied; at first oil price shocks are extracted by Hodrick-Prescott filtering and then the effect of oil shocks on regarded variables are estimated by Vector Auto-regressive Model (VAR). The result of regression analysis show that Emirate and Iran are the most dependent to oil shocks; Indonesia and Ecuador is the least dependent. The experience of Indonesia shows that decreasing in oil dependence is not possible without taking correct policies.