saeid eisazadeh

This study aims at investigating the impact of bilateral investment treaties on foreign investment inflows into Iran from developed source countries. To achieve this purpose, the two common approach in foreign investment literature, that is, the gravity and knowledge-capital model has been used as the analytical framework of the study, as well as the pseudo-Poisson maximum likelihood method for the years 2002-2020. The results show that both gravity and knowledge-capital models provide an acceptable explanation of foreign investment inflows into Iran from developed countries. Except of Iran's real GDP, the main variables of the gravity model, that is, the geographical distance and real GDP of developed source countries are statistically significant and have the expected signs. All the main variables of the knowledge-capital model, including the difference between gross enrollment ratio in tertiary education of developed source countries and Iran (with a negative coefficient), sum of real GDP of developed source countries and Iran (with a positive coefficient) as well as Interaction of the difference between gross enrollment ratio in tertiary education of developed source countries and Iran and difference between real GDP of developed source countries and Iran (with a positive coefficient) are statistically significant and indicate that the foreign investment of developed countries in Iran is more horizontal than vertical. There is a positive and statistically significant relationship between bilateral investment treaties and foreign investment inflows into Iran from developed source countries in both gravity and knowledge-capital models. Finally, the sanctions imposed against Iran have reduced foreign investment inflows into the country.

Nowadays, unemployment and particularly the unemployment of educated youth is one of the difficult problems of developing countries including Iran. Since unemployment is costly for households and society from an individual and social perspective and has long-term psychological destructive consequences; hence, understanding of unemployment duration and the factors affecting, can help policymakers in planning to reduce these costs. In this article, in order to evaluate the impact of education, including education levels and fields on unemployment duration of new entrants to the labor market, the common survival analysis models; That is, Kaplan-Meier estimator, Cox proportional hazards model and parametric models were used. The results showed that new entrants to the labor market in the major educational group of engineering, manufacturing and construction compared to the social sciences, journalism, and information; experimental sciences, mathematics and statistics as well as humanities and arts have lower probability of surviving unemployment. The unemployment duration of illiterate and new entrants to the labor market with upper secondary, lower secondary and primary education has been lower than new entrants with other educational levels. Also, we find that the unemployment duration of new entrants to the labor market increases with age.

AbstractThe emergence of the Covid crisis around the world and its impact on the economic activity caused many countries to experience a recession during this period that affected all sectors of the economy. During the period of facing this crisis, many countries witnessed a decrease in economic growth because this disease caused the closure of production companies and the adjustment of the workforce, which resulted in a decrease in economic growth. This study aims to assess the effect of covid 19 on businesses through the survival analysis approach. By using the information of starting and ending of businesses during December-2011 and September 2021, we have resulted that the businesses had a 10% lower risk of closure before the start of Covid19. Also businesses in the other cities of the province 35% less likely to close down compared to Hamadan city.

Foreign investment has many positive effects on the host countries. Attracting foreign investment through technology transfer and increasing competitiveness in the business environment probably lead to increasing economic growth and reducing poverty. Developing countries have always been trying to attract more foreign investment by providing the necessary conditions and increasing their competitiveness. In this regard, the governments of these countries have used various initiatives such as signing bilateral investment treaties as a reliable tool to encourage and promote foreign investment. This study has been compiled with the aim of investigating the impact of bilateral investment treaties on foreign investment in Iran. To achieve this purpose, the gravity model approach and the panel data model in the period of 2002 to 2020 have been used. The results show that there is a positive and significant relationship between signing bilateral investment treaties and the attraction of foreign investment in Iran. Because the sanctions imposed against Iran foreign investment inflows to Iran have significantly reduced. In addition, there is a positive and statistically significant relationship between the variables of the existence of common language, as well as the real GDP of the home countries and the attraction of foreign investment in Iran

The present study aims to investigate the impact of unilateral economic sanctions of the United States of America on Iran's employment during 1991-2020. Nowadays, the issue of employment and providing decent jobs is one of the major development goals and a main concern of policy makers and economists. Moreover, job creation is a major strategy to reduce poverty and improve well-being and thus to generate income and increase demand for goods and services. Nevertheless, with the advancement of science and technology and the specialization of jobs, the prospect of employment in most developing countries, including Iran, has become a major and fundamental problem. Several factors affect employment, one of which is definitely economic sanctions that cause social and economic inequalities as well as the reduction of economic growth through the restriction of the export and import of goods.

This research examines the effects of the economic sanctions imposed by the United States on Iran's employment during 1991 to 2020. To this end, the synthetic control method (SCM) is applied. At the first step, the total employment is measured as the outcome variable. Then, a synthetic control unit is built for Iran, by which the expected employment occurs under a scenario with no sanctions after 2005. Then, the effects of sanctions on employment are estimated. The synthetic control method is a statistical method used to evaluate the effect of an intervention in comparative studies. It involves the construction of a weighted composite of groups that are used as a control group to compare the treated unit .Using the weighted mean of units as a comparison avoids the model-dependent extrapolation on which regression results are often based. This research shows the potential gains achieved by using synthetic controls in comparative studies. The effects of the intervention may have been randomly generated, in which case it will not be statistically significant. Therefore, in the next step, the inferential techniques proposed by Abadi et al. (2015 and 2010) are used to support the estimates of the synthetic control method and evaluate the significance of the results.

Considering the importance of employment in the social and economic life of any country, especially developing countries, international economic policies have been given almost as much attention as national policies to expand employment opportunities in less developed countries and have always been one of the concerns of planners. Therefore, it seems necessary to make a serious effort to identify the factors affecting employment, which can achieve the prior goals of employment and eliminate unemployment. One of the factors affecting Iran's employment in recent years is economic sanctions. The present study utilizes the synthetic control method (SCM) to investigate the effects of sanctions on Iran's employment. Through SCM, the difference in employment between the treated country (actual Iran) and the synthetic one (synthetic Iran) is estimated. Synthetic Iran is constructed as a convex composite of the countries in the control group in such a way that it is most similar to the actual Iran in terms of the predictor values of the pre-sanction outcome variable.

The study shows the intensification of the economic sanctions imposed on Iran since 2006 and the exposure of new sectors in the Iranian economy. There were thousands of declines in the employment of Iran until 2015, which is about -7% in employment of “actual Iran” and “synthetic Iran”. However, with the JCPOA agreement in 2015 and as a result of the resumption of trade, the employment rate decreased to 749 thousand, which was 41.3% in 2018. Yet, by Trump's victory in the elections and America's withdrawal from the JCPOA, and the increased pressure of sanctions, the gap between synthetic Iran and actual Iran reached its peak in 2020, i.e. 1966 thousand people (a 48.9% decrease). This was due to a sharp decrease in employment. The results also indicate that the synthetic Iran was a good reflection of the actual Iran in the pre-intervention period. The increase in economic costs from 2018 to 2020 also shows the large and long-term negative effect of the intervention (sanctions) on Iran's employment during the sanctions period. In addition, the placebo tests show that the results are statistically significant at the 10% level. Iran had the largest treatment effects and the highest ratio of MSPE after the intervention compared to before the intervention. The findings are also robust to the composition of the donor pool and the start of the sanctions, which is because the results are similar when the countries with positive weights are removed from the donor pool one at a time or when the treatment event is moved to 2004. However, the results are not sensitive to the composition of the donor pool or to the start of the sanctions.

In this paper, we use the Synthetic control method to assess the impact of economic sanctions imposed by the United States on Iran's per capita GDP during 1990 to 2020. The US economic sanctions against the Iranian economy during this period has had a huge negative impact on the economy of Iran. Using the Synthetic control method, the economic cost of sanctions has been estimated in terms of per capita GDP. The results show that the effects of sanctions on the economy would be a significant reduction in per capita GDP by 33% in comparision with the lack of sanctions position. After intensifying santions in the Trump administration, negative effect has reached to 44% reduction in per capita GDP in 2020. Definitly, this reduction of per capita GDP will deccrease the walfare of Iranians in the long-run.

In the recent decades, global tendency towards the knowledge-based economy, has become human capital and effective labor to one of the major factors of economic growth and has led to increasing willingness of governments and individuals to invest in higher education. generally, considering education as an investment and development of educational systems on the one hand and increasing the share of education in gdp and the national budget on the other hand, has attracted the attention of economists and planners to evaluate the effectiveness of investment in education. the purpose of this study was to evaluate the private rate of return of educational institutions in iran using the generalized mincer model and by using the mincer income function, the effect of education at different levels on employee income was investigated using household-budget statistics in 2019. ordinary least squares regression model (OLS) has been used to estimate the desired pattern.the results showed that education in diploma, bachelor and postgraduate degrees has a positive effect on income from employment that the rate of this impact for each year of additional education is about 8/1 percent and the effect of work experience on people's income shows 4/1 percent. this, apart from other incentives to enter these sections, shows the economic justification of these sections from an individual point of view. also, with the inclusion of virtual variables of gender, job and marital status of individuals in the model according to the coefficients obtained in the regression model, the effect of these variables on the income of individuals has been a significant effect and these results were obtained: men earn more than women, people working in the public sector earn 32.3% more than other people in the private sector and finally married people earn 41.6% more than single people.

Because of agricultural businesses and lower incomes, people in villages usually are poorer than those living in rural areas. The Poor development of rural area due to poverty compared to urban areas is one of the main issues of economic development nowadays. Therefore, in many countries, the people of rural areas decided to set up industries in the villages to get rid of poverty, so that they could earn high income through non-agricultural employment. Therefore each village has acquired skills to produce a distinctive product that can reduce poverty in rural areas. The aim of study is realizing the influential factors of formation and establishment of such industries in the villages. For this purpose, a set of Hamadan villages with non-agricultural activities was selected. Study follows a qualitative approach, that is, empirical evidence is beside in-depth-study of the literature on the historical origins of non-farm agricultural activities upon more than 50 interviews with experts and owners of establishments. The results shows that among the villages that established the “one village- one product" activities,one of the important factors is "market access" of their products. Low cost of living in the new point of production-villages-in terms of cost of rent and labor was another leading factor for forming the industrial businesses in rural places. Besides, the inheritance of routines from initial firms located in urban areas and knowledge exchange between skilled workers and pool labor are main factors of creating new business in new areas. Dependent activities have been formed to eliminate the needs for materials and devices and repairs, that caused be complete the specified cluster of activities. Along with these developments, some villages have witnessed reverse migration and people have moved from cities to villages. Investigating these activities revealed that better income prospects, flexibility, less stressful work environment and job stability were important reasons for continuing these activities.

Skills Mismatch is an encompassing term which refers to various types of imbalances between skills offered and skills needed in the labor market. In this article, indicators of primary and secondary Skills Mismatch (KILM 15a, KILM 15b) that in 2014 were considered the key indicators of Labor Market are calculated. The research method used in this article was the same approach used by the International Labor Market. For the purpose of calculating existing index information in the Labor Force Survey during 2006:Q1 to 2013:Q1 were used. According to the research results, women and young people are more vulnerable than adults in the first type mismatch. Moreover, for all group's education was decreased by age and gender during the period under review, whereas over education showed an excessive increase, especially for individuals aged 15-29.

During last few decades, Iran has experienced a massive flow of immigrants from two countries of Afghanistan and Iraq as a result these countries social, political and economic instability. For the time being, the majority of immigrants in Iran are Afghans. Difference in level of economic development between Iran and Afghanistan is the main contributing factor to this phenomenon, while the cultural and religious commonalities also should not be ignored. The majority of Afghan immigrants are typically unskilled and illegal workers. They expect lower wages than their Iranian counterparts and are ready to work in difficult conditions. Keeping in mind that a high percentage of Afghan immigrants are working in the construction sector, it is expected that most effects take place in this sector of the economy. In this paper we study the impacts of Afghan immigrants on the employment and average real wages of construction sector in Iran, through time series data analysis and estimating regression equations using Ordinary Least Square (OLS) method. Results indicate that during the period under study (1976-2006), Iranian workers have been replaced by Afghan workers, and their employment rate has declined in the construction sector. Declining average wage rate in construction sector due to existing Afghan workers in Iranian labor market is another important result of this study.

Iran is one of the most concentrated areas of Afghan migrants and refugees. Most Afghans dispersed throughout the country mixed with Iranian households. The majority of Afghan immigrants are typically unskilled and illegal workers. This study aims at investigating the nature of the causal relationship between Afghan immigrants and two main labor market indicators، average wages and unemployment rate، in Iran using autoregressive distributed lag (ARDL) bounds testing procedure and Granger-causality within vector error correction model (VECM) based on annual data spanning the period between 1976 and 2006. Results of the ARDL bounds test are supportive of the theory that the variables are in a long-run equilibrium level relationship. Results of the Granger-causality tests support the existence of a long-run، bidirectional causality between immigration and unemployment. While in the short run there is unidirectional Granger causality running from immigration to unemployment rate.

Banking system is one of the important sections in the economy. In economies those stock exchange and other financial intermediaries are inefficient this rule is vital. In this regard the efficiency of banking system should be mentioned in the economy.This paper examines empirically the effect of macroeconomic stability on efficiency in the Middle East and North Africa (MENA) banking industry for the years 1995 to 2008 by Using panel data method. We use bank level data to study the efficiency of banks in MENA countries and provide possible explanations for the difference in the efficiency levels of banks. We find that banks, on average, could save 20 percent of their total costs if they were operating efficiency. Through the stochastic frontier approach (SFA) method we measure the cost efficiency of different banks in MENA including Iranian banks. Then we investigate the impacts of macroeconomic State on the efficiency level of banking industry. In this study are as inflation rate and GDP per capita. The findings show that, the stability macroeconomic stability has increased efficiency during the period of study.

In this paper, we try to explain cross-country differences in the level of entrepreneurship using self-employment and innovation as proxy variables. For this purpose, we use a comparative approach to explore empirically the ways in which institutions have influenced self-employment and innovation. In this paper, we make the assumption that national patent grants represent innovation and that national self-employment rates represent job replacement. Then, we investigate the relationship between the institutional setting, in terms of economic freedom measures, and entrepreneurship which is measured by proxy variables of self-employment and innovation in a panel data setting covering selected countries for the time-period of 1990-2009. The empirical findings show that indices of corruption perception, business freedom and trade freedom are negatively correlated with self-employment rate. On the other hand, investment freedom and freedom from government intervention have positive effect on self-employment. Interestingly, we found that institutional factors that determine self-employment and innovation may act in opposite directions: what encourages self-employment might discourage innovation and vice-versa.

Urbanization is a major feature of economic development, and involves many structural changes across the economic system which have important implications for energy consumption. This paper provides empirical evidence on urbanization and energy consumption in Iran over the period 1973–2006, using ARDL testing approach and factor decomposition model. The results of the bounds test show that there is a stable long-term relationship among total energy consumption, population, GDP (gross domestic product) and the level of urbanization. meanwhile, the results of the causality test using ECM (error correction model) to test short- and long-term dynamics of the relevant variables, indicate that there exists only a unidirectional Granger causality relationship between urbanization and total energy consumption in the short run. On the other hand, the results support the existence of a long-term, bidirectional causality relationship between urbanization and total energy consumption. Factor decomposition analysis indicates that technical progress, urbanization process, and economic development have respectively the greatest impacts on the energy consumption in Iran. At present, the share of urbanization in increasing energy consumption is smaller than the past, and the energy intensity is gradually on the fall.

This study aims to estimate the employment multipliers of the various sectors related to tourism industry. In this regard, the amount of direct, indirect, and induced jobs associated with tourism sectors were measured. Also, using the input-output table of 1380 of Iran’s economy, the first and second employment multipliers were calculated. Results revealed that "wholesale and retail sales sector" with a normal multiplier of 0.002 and multiplier ratio of 15.15 obtains the first rank in creating jobs in Iran’s economy.

During last decades Iran has experienced a massive flow of illegal Afghan immigrants. These immigrants not only affect the cultural, marriage, employment, education, health, crime & housing but also has influenced directly the economy of Iran. The aim of this paper is surveying the economic effects of illegal immigrants. As there is no statistical information on this group, so we study the impacts theoretically. It is important to consider this phenomenon because majority of immigrants in Iran is illegal ones. During the past few years a huge flood of illegal Afghan immigrants have been employed in the labor market of Iran. So we can use the special effects of illegal immigrants in studying the Afghan workers in Iranian labor market. Besides, we can use best practice of polices in confronting of Afghan immigrants in Iran.

Iran is one of the most concentrated areas of Afghan migrants and refugees. Most Afghans live outside camps dispersed throughout the country mixed with Iranian households. The majority of Afghan immigrants are typically unskilled and illegal workers. They expect lower wages than their Iranian counterparts and are ready to work in troublous conditions. Therefore, they can compete with Iranian unskilled workers. This study makes an attempt to investigate the impacts of Afghan immigrants on the unemployment rate in the economy of Iran, through time series data analysis and estimating regression equations using Ordinary Least Square (OLS) method. The results indicate that during the period under study (1976-2006), Afghan immigrants led to and increase in the unemployment rate in the economy of Iran. In fact, Iranian workers have been replaced by Afghan workers.