In the past few decades, a large number of Iranians have chosen to find new places of residence in foreign countries. This Iranian diaspora includes a significant number of highly-skilled workers, entrepreneurs, and owners of capital. These skills, capabilities, and capital assets have either been transferred directly from Iran as a result of MIGRATION or have been created indirectly in the host countries with the support of domestic Iranian financial and intellectual sources. Furthermore, the demand for MIGRATION has not subsided in Iran. Yet, whereas the MIGRATION of highly-qualified LABOR FORCE continues to be significant, the surplus Iranian LABOR FORCE with medium level of qualifications is not able to secure productive jobs abroad. The purpose of this article is to examine various important aspects of significant MIGRATION propensity observed among Iranians with an emphasis on the highly-skilled as well as semi-skilled LABOR FORCE. Furthermore, in this article, government efforts placed on expatriate reconnection and dispatch of surplus LABOR to foreign countries are described. Some observations on the main MIGRATION causes of the highly-skilled LABOR FORCE and obstacles to the MIGRATION of the semi-skilled LABOR FORCE as well as a set of recommendations for the short-term are also offered in the article.

Women comprise roughly half of active population of societies. Although the education of women is costly, they mainly have low rate of participation in the LABOR market. Using raw data of LABOR FORCE surveys for Iran LABOR market during period1397 to 1398, this paper investigates factors affecting Women LABOR FORCE Participation (WLFP). The results of this research, which uses logit model for analyzing its data, eLABORate that despite similarities (significance and the same direction of effectiveness in the number of children under seven, age, age square, and education variables), there are differences in urban and rural estimation results. While non-Iranian nationality in urban areas has increased WLFP, it is not true for rural equation. Also, the probability of rural women participation in the LABOR market will increase till a higher age in comparison to urban sample. It is noteworthy that education is the most powerful factor in the participation of urban women in the LABOR market. According to Iran statistics, the main reason of increased non-active population is family responsibilities. As results show, increasing the number of children under seven, in urban and rural areas will decrease WLFP and being married will decrease WLFP in urban regions.

The present study examines the MIGRATION of the Iranian workFORCE to the Caucasus in the second half of the nineteenth century to the constitutional revolution and the role played by Azerbaijan in this regard. current paper, based on the authoritative internal and external sources and with using of a descriptive-analytical method in response to issues such as the reason for the MIGRATION of the LABOR FORCE to the Caucasus and the share of Azerbaijan in it shows that Azerbaijan was the main center for the issuance of migrant LABOR to the Caucasus, which, in turn, was the result of the general economic downturn in Iran, the decline of Azerbaijan's position as a result of changing the ways of commerce, The high population and the inability of the province's economy to absorb indigenous LABOR, and on the other hand, the natural consequence of the industrial areas on Beyond the border, and in particular the Caucasus.

It is necessary to study the relationship between foreign trade and MIGRATION between developed and developing countries, as the eMIGRATION rate has been increasing in recent decades. The objective of this paper is to examine such relationship between Iran’s trade and LABOR FORCE MIGRATION to the selected major OECD members over the period 1992-2004. Hence, the empirical results, obtained by estimating a panel gravity-based model, indicate that there is a significant and complementary relationship between Iran’s foreign trade and MIGRATION to these countries. Moreover, the results show that the LABOR wage divergence, increasing gap between real LABOR wages in Iran and the selected OECD countries, increase eMIGRATION flow from Iran to such countries.

AbstractReverse MIGRATION as a demographic phenomenon is influenced by various causes and factors. As this trend continues and large numbers of migrants arrive in rural areas, the government faces the challenge of providing basic rural infrastructure and services to meet the needs of the migrant population. Therefore, managing and formulating supportive and encouraging policies and creating a suitable platform for reverse MIGRATION can be one of the most important solutions to address this challenging issue. In this research, for the first time in the country, we evaluate the trend of urban-rural MIGRATION and identif its causes using LABOR FORCE Survey Database during 2017-2021. The research findings show that urban-to-rural MIGRATIONs and their causes are strongly influenced by the socio-economic characteristics of migrants. Therefore, it is necessary to pay attention to different sections of the society and continuously investigate urban-to-rural MIGRATIONs based on sustainable development indicators in the country's villages. Descriptive analysis and logistic regression model fitting on the data during the five-year period showed that age, sex, activity status and education level are related to urban to rural MIGRATION. IntroductionAccording to the results of the 2011 population and housing census, the amount of urban to rural migrants in Iran is more than the number of rural to urban migrants. It seems that the reverse flow of MIGRATION from urban to rural areas, which is called reverse MIGRATION, has been started. However, investigating the flow of urban to rural MIGRATION and identifying the reasons of this type of MIGRATION in Iran, especially in short time intervals, has been less discussed. The issue is due to the lack of a database or a specific framework for investigating and evaluating this type of MIGRATION.Until now, the main source of information and data for investigating MIGRATION patterns and its reasons has been the latest population and housing census. However, due to the fact that the censuses are carried out with a frequency of five or ten years, it is not possible to continuously monitor internal MIGRATIONs and their causes. Therefore, it is important to find other data sources to monitor the flow of urban to rural MIGRATIONs in shorter time intervals. Investigations showed that the only other source other than the census that provides information is the LABOR FORCE Survey (LFS), which is conducted annually by Statistical Center of Iran. The general purpose of this paper is to estimate the number of urban to rural migrants during the years 2017 to 2021 at national level, to investigate its causes, and to identify the socio-economic characteristics of migrants during these years using LFS data. Methods and DataThe research method is the secondary analysis of the data obtained from the LABOR FORCE survey. Descriptive statistics are presented and the logistic regression model has also been used to investigate the factors affecting urban to rural MIGRATION. According to the definition of the LFS, those household members whose Length of stay (continuously until the survey time) was less than 12 months in that city or village are known as immigrants. The target population in LFS is the members of private settled or collective households. The sampling method is stratified two-stage cluster sampling. The annual sample size in rural areas is about 94 thousand households. Since LFS is not done centrally in a specific time of the year, the duration of people's stay is not measured at a certain point of time and the same for everyone. The causes of MIGRATION listed in the LFS questionnaire are similar to those mentioned in the 2011 census and include seeking work, looking for better work, job transfer, education, graduation, beginning or ending of compulsory military service, follow the household and others. FindingsIn this section a summary of results including, the estimation of the number of urban to rural migrants using the LFS data from 2017 to 2021 by reasons, gender and activity status is presented at national level. Table 1- The number of immigrants from the urban to rural areas by gender and the reason for MIGRATION during the years 2017 to 2021 According to the Table 1, the highest and the lowest amount of urban to rural MIGRATIONs among men during the entire period under review was due to begin or end of compulsory military service, education and graduation, respectively. The highest number of urban to rural migrants among women was due to follow the household. In the total period of five years, it can be stated that the total number of MIGRATIONs was higher for men than for women.According to the results of Table 2, beginning or end of compulsory military service, seeking work, looking for better work, job transfer are main reasons of urban to rural MIGRATION among employees during the five-year period. But the reason for MIGRATION of inactive people is different from that of employed people, that is follow the household. In the total period of five years, it can be stated that the number of employed immigrants has been more than other people.  Table 2- The number of immigrants from the urban to rural areas by activity status and the reason for MIGRATION during the years 2017 to 2021 The effect of various factors on urban to rural MIGRATION is investigated using the logistic regression model and based on the available data. In this model, the person's imMIGRATION status is considered as the response variable and MIGRATION from urban to rural area is considered as a pass event. The independent variables whose information are available from LFS include age, gender, literacy status, activity status, and marital status. Due to the fact that marital status is determined for people aged 10 years and older, model fitting is done for this subgroup of people. The results of fitting the logistic model to the data from 2017 to 2021 are shown in Table 3.As can be seen in Table 3, from 2017 to 2021 urban to rural MIGRATION is decreases with increasing age. Also, the odds for women to migrate is less compared to men. Examining the effect of activity status on the odds of MIGRATION shows that the chance of MIGRATION of unemployed people is higher compared to employed people and the odds of MIGRATION of inactive people is lower compared to employed people. But the interaction effect of age and activity status shows that with increasing age, the odds of MIGRATION of inactive people is higher compared to working people. This issue can indicate the return of the elderly from the urban to rural areas. Among women, inactive women are more likely to migrate than working women, which can be due to the MIGRATION of housewives or female children following the household.Table 3- Fitting Logistic regression Model on Urban to Rural MIGRATION Data from 2017 to 2021. Conclusion and DiscussionThe estimation of the number of urban to rural migrants, its causes, as well as the socio-economic characteristics of migrants at the national level, was presented based on the annual data of LFS. Obviously urban to rural MIGRATIONs are strongly influenced by the socio-economic characteristics of the migrants. Therefore it is essential to consider different  groups of people based on their characteristics in order to formulating support and encouragement policies and creating a suitable platform to meet their needs. AcknowledgementThis paper is based on the research project: “Feasibility Study of Estimating Urban-to-Rural Migrants, 2016 to 2021”, commissioned by the Vice-president for Rural Development and Deprived Areas of the country and conducted at the Statistical Research and Training Centre of Iran, and we thank them for their support.

Female LABOR FORCE participation (FLP) has been shown to be inversely correlated with fertility based on most literature. However, despite a considerable decline in fertility rate in Iran over the past two decades, women's participation in LABOR FORCE has not been increased significantly. To investigate the issue, this study is following two objectives: First, to explain the relationship between the FLP and childbearing, theoretically. Second, to study empirically the matter using the data of Household Income and Expenditure Survey (HIES) conducted by the Statistical Center of Iran (SCI) in years 1991 to 2012. Based on the theoretical model, two mutual relationships can be explained for FLP and childbearing. In one hand, female LABOR FORCE participation can lead to increase of family income and fertility. On the other hand, there is the substitution effect by which a woman who has desire to bear a child, would undermine her economic participation. Existence of both effects system was confirmed, using simultaneous equations in provincial panel data. To encounter this endog eneity problem, we employed an instrument variable as “ same gender of the first two children” for decision of having another child. Based on the results, the relationship between FLP and fertility in Iran is based on the income effect. Accordingly, the substitution effect of childbearing and LABOR FORCE participation which is under influence of cultural factors, has been evolved. Hence, it does not seem that facilitating FLP and support of employed women would be a threat to fertility behaviors in Iran. Even, it might be considered as an encouraging policy for childbearing by enhancing family income

The relationship between international trade and eMIGRATION is being concerned in most developing countries with their relevant MIGRATION and trade policies. Such policies should rely on logical resolutions in order to reduce unemployment pressure on the LABOR market. Hence, this study examines the relationship between Iran’s trade volume and LABOR FORCE eMIGRATION to the five major members of the OECD (the US, Canada, the UK, the Netherlands and Sweden) over the period 1992-2004 (1371-1383). Following Mitchell and Pain (2003) and Mayda (2005), a specified gravity model is estimated by panel data to show the impacts of determinants on the Iran’s eMIGRATION. The empirical results obtained indicate that there is a significant and complementary relationship between trade volume and the LABOR FORCE eMIGRATION to the selected countries of OECD in Iran. Additionally, the results show that convergence in the LABOR FORCE productivity, as a gap between the number of skilled LABORs falls in Iran and the OECD members, can lead to a decrease in eMIGRATION from Iran to abroad.