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Showing 4 results for Karimzadeh
Mirsatar Sadr Mousavi, Hossein Karimzadeh, Aghil Khaleghi,
Volume 5, Issue 16 (summer 2016 2016)
Volume 5, Issue 16 (summer 2016 2016)
Abstract
Introduction
The idea of "ignoring economic labor" of rural women and their role in providing households' financial and non-financial resources is deeply ingrained in cultural fabric of our society that is hardly possible to change the notion of "men being sole breadwinners". The rate of women participation in the employment and labor market is much less than men. This is due to the presence of social, legal, and economic barriers and cultural and traditional restrictions. In Iran, the main activities of rural women can be summarized in three sectors; agriculture, rural industries and rural services. Currently, according to the information contained in the (2011-2012) 1390 Statistical Yearbook, 14987out of 37 958 people, as the population of 10 years and more in the County of Varzeghan, constitute the employed active population. It makes a portion of 13098 for rural areas. The share of female population employed in agriculture, forestry and fishing in the province has reported to be 26116 people within which the overall share of the total population of Varzeghan has been 8280.
Although rural women are not counted in agriculture sector, many women of the County are participating in this sector. While rural women try alongside men in agriculture, because of certain traditional beliefs and public imagination there are always barriers for rural women's participation in the labor market. Considering the importance of this issue, this article aims at answering the questions that "what is the main obstacle facing the employment of rural women in Varzeghan County?" and "What is the impact of other effective barriers on the employment?"
Methodology
We have used mixed method approaches in the article. Since the sequence of qualitative and quantitative research methods is known as one of the features of mixed research, we have used first the qualitative and then the quantitative ones. In the first stage, in order to identify different causal conditions, as factors affecting the low participation of rural women in the workforce, a qualitative method was used in which we have interviewed with literate women. Then, to achieve the desired result in the second stage, qualitative research findings were used in developing the questionnaire, whereas obtained quantitative data were used to provide a structural model. The questionnaires were completed by literate girls and women livelihood in rural district of Sina. Using Cochran formula, sample size was calculated to be 300 people, with the confidence interval of 0.95. A simple random sampling method was used and the questionnaires were formulated by a number of 15 closing questions that their options were assessed based on rating Likert scale. Its validity was estimated based on its formal validity and its reliability was calculated 0.919 by Cronbach's alpha which indicates that the questionnaires are highly reliable. Table 3 shows the output of SPSS software.
Discussion and conclusion
Considering the development of different societies and urban areas along with the development of rural societies, rural girls and women are no longer interested in participating in agricultural sector. Instead, they are getting to the employment of nonagricultural manufacturing jobs as well as government and service ones. Casual barriers affecting the employment of rural women in the area under study can be classified in four groups of individual, family, socio-cultural, and management-structural barriers. These are multiple-effect barriers which are related to each other. Being remote as a variable for villages and individual and family factors are of the highest importance. Given the casual barriers of the phenomenon, lifestyle changes are evident in the rural community.
The main reason of most villagers' migration is to find appropriate non-agricultural jobs. Among them, there are some migrant girls that not only have they achieve their goals of employment in urban communities but also there is not enough attraction in their ancestral home of insufficient facilities to make them return. Variables such as education, marital status and income level are commonly considered as intervening obstacles facing the employment of rural women. It is certain that changes in social customs, values and traditions as well as lifestyle changes can make rural women have less or no tendency to live in rural areas and move to cities. Changes in lifestyle, family system, and social customs and values are all strategies taken by rural community to minimize the effect of barriers affecting the employment of girls and women. Of course, these strategies have their special consequences. They may cause late marriage or the rise of average marriage age which are effective in the creation of social and moral corruption in the society.
Rural to urban migration can lead to economic poverty which is by itself one of the most important factors causing corruption in the society. Changes in social customs and values can also lead to reluctance to agricultural activities which is due to familiarity with urban life. A combination of factors like these cause inappropriate behaviors b rural girls and women.
We have used mixed method approaches in the article. Since the sequence of qualitative and quantitative research methods is known as one of the features of mixed research, we have used first the qualitative and then the quantitative ones. In the first stage, in order to identify different causal conditions, as factors affecting the low participation of rural women in the workforce, a qualitative method was used in which we have interviewed with literate women. Then, to achieve the desired result in the second stage, qualitative research findings were used in developing the questionnaire, whereas obtained quantitative data were used to provide a structural model. The questionnaires were completed by literate girls and women livelihood in rural district of Sina. Using Cochran formula, sample size was calculated to be 300 people, with the confidence interval of 0.95. A simple random sampling method was used and the questionnaires were formulated by a number of 15 closing questions that their options were assessed based on rating Likert scale. Its validity was estimated based on its formal validity and its reliability was calculated 0.919 by Cronbach's alpha which indicates that the questionnaires are highly reliable. Table 3 shows the output of SPSS software.
Discussion and conclusion
Considering the development of different societies and urban areas along with the development of rural societies, rural girls and women are no longer interested in participating in agricultural sector. Instead, they are getting to the employment of nonagricultural manufacturing jobs as well as government and service ones. Casual barriers affecting the employment of rural women in the area under study can be classified in four groups of individual, family, socio-cultural, and management-structural barriers. These are multiple-effect barriers which are related to each other. Being remote as a variable for villages and individual and family factors are of the highest importance. Given the casual barriers of the phenomenon, lifestyle changes are evident in the rural community.
The main reason of most villagers' migration is to find appropriate non-agricultural jobs. Among them, there are some migrant girls that not only have they achieve their goals of employment in urban communities but also there is not enough attraction in their ancestral home of insufficient facilities to make them return. Variables such as education, marital status and income level are commonly considered as intervening obstacles facing the employment of rural women. It is certain that changes in social customs, values and traditions as well as lifestyle changes can make rural women have less or no tendency to live in rural areas and move to cities. Changes in lifestyle, family system, and social customs and values are all strategies taken by rural community to minimize the effect of barriers affecting the employment of girls and women. Of course, these strategies have their special consequences. They may cause late marriage or the rise of average marriage age which are effective in the creation of social and moral corruption in the society.
Rural to urban migration can lead to economic poverty which is by itself one of the most important factors causing corruption in the society. Changes in social customs and values can also lead to reluctance to agricultural activities which is due to familiarity with urban life. A combination of factors like these cause inappropriate behaviors b rural girls and women.
Mohsen Aghayari Hir , Mohammad Zahheri, Hossein Karimzadeh, Ali Majnuni Tutakhaneh,
Volume 10, Issue 36 (summer 2021 2021)
Volume 10, Issue 36 (summer 2021 2021)
Abstract
Introduction
Due to its geographical location and climatic conditions, Iran is facing water shortages. A large part of the country is in arid and semi-arid climates. In addition to the dry weather of the country, mismanagement, short knowledge of farmers, outdated infrastructure, low level of technology have led to low water productivity in rural areas. The Qaleh chai watershed is one of the catchments located around Lake Urmia, which is facing water shortage due to drought conditions. This area with 36 villages is known as one of the hubs of agricultural and livestock production. According to the obtained data, the water efficiency level in the basin is less than 50%. Lack of water resources has led to the need to pay attention to ways to improve water efficiency. It seems that several factors play a role in the quantity and quality of water use, in other words, in the level of its productivity in The Qaleh Chai, and the most important ones include geographical conditions such as slope, location of villages, amount of products produced. Literacy level, number of rural households, water resources, amount of water available. By identifying and analyzing the factors affecting the promotion of water productivity in the basin, the amount of water productivity can be improved. Therefore, the main purpose of this study is to investigate and find a scientific answer to the question of what is the spatial distribution of factors affecting water productivity in villages located in The Qale chai? And to what extent can the studied variables explain the changes related to water productivity?
Methodology
The research method is descriptive-analytical and inferential, which has based on documentary studies, libraries, and field studies. Local Moran correlation tests and geographic weight regression (GWR) tests were used to analyze the data. The variables used in this study included 19 environmental components affecting water productivity: Number and spatial distribution of springs, number and spatial distribution of wells, river water volume, water abstraction from wells, water abstraction from rivers, water abstraction from springs, length of concrete irrigation canals of all canals, the total volume of water in Consumption, number of households, unemployment rate, the employment rate in agriculture, literacy rate, rial value of tree products, rial value of rainfed products, rial value of summer crops, rial value of light livestock products, rial value of heavy livestock products, agricultural and medium irrigated land area Slope of villages to percent.
Water productivity has been used to calculate the rial value of livestock products, agricultural products, and human variables. The study area of this research is the Qaleh chai which has 36 villages located in it. The region of this basin is equal to 249.63 square kilometers, which has located in East Azerbaijan province and the southeast of Lake Urmia.
Discussion and conclusion
Research Findings show that the number of spring water resources is higher in mountainous villages and, the number of wells is higher in plain rural. The results of Moran showed that the variables of the Iranian Rial value of livestock production and the total amount of available water lack spatial autocorrelation. Also, the variable of the Iranian Rial value of all agricultural products has no spatial autocorrelation, but the total number of water resources has a spatial correlation. There is also an intense spatial correlation in the average slope of the villages, but the results of this test on the final water productivity lack spatial correlation. According to the results, the literacy variable of spatial autocorrelation is cluster type. The variables of household size and employment have no spatial correlation. Results The GWR regarding the causal role of the variable related to the final value of agricultural products and livestock products with water productivity showed that the last value of products with a correlation of R2 = 229 can explain water productivity. Based on the results of the geographical weight regression test, the value of R2 for social variables was equal to R2 = 0.129, which is lower than the final value variables of livestock and agricultural products.
Findings of this study show that factors such as the number of agricultural products produced, water resources, the volume of water available from water resources, land slope, number of water pumps and Iranian Rial value of livestock and agricultural products, literacy rate, employment rate, population have a significant relationship with water productivity. According to the research findings, it is clear that to achieve an efficient solution to improve water productivity in the villages located in the Qalah Chai watershed, it must have all the operative factors, including natural elements. Human factors, management factors, and physical characteristics are based on accurate, reliable data and planning occurrence.
Due to its geographical location and climatic conditions, Iran is facing water shortages. A large part of the country is in arid and semi-arid climates. In addition to the dry weather of the country, mismanagement, short knowledge of farmers, outdated infrastructure, low level of technology have led to low water productivity in rural areas. The Qaleh chai watershed is one of the catchments located around Lake Urmia, which is facing water shortage due to drought conditions. This area with 36 villages is known as one of the hubs of agricultural and livestock production. According to the obtained data, the water efficiency level in the basin is less than 50%. Lack of water resources has led to the need to pay attention to ways to improve water efficiency. It seems that several factors play a role in the quantity and quality of water use, in other words, in the level of its productivity in The Qaleh Chai, and the most important ones include geographical conditions such as slope, location of villages, amount of products produced. Literacy level, number of rural households, water resources, amount of water available. By identifying and analyzing the factors affecting the promotion of water productivity in the basin, the amount of water productivity can be improved. Therefore, the main purpose of this study is to investigate and find a scientific answer to the question of what is the spatial distribution of factors affecting water productivity in villages located in The Qale chai? And to what extent can the studied variables explain the changes related to water productivity?
Methodology
The research method is descriptive-analytical and inferential, which has based on documentary studies, libraries, and field studies. Local Moran correlation tests and geographic weight regression (GWR) tests were used to analyze the data. The variables used in this study included 19 environmental components affecting water productivity: Number and spatial distribution of springs, number and spatial distribution of wells, river water volume, water abstraction from wells, water abstraction from rivers, water abstraction from springs, length of concrete irrigation canals of all canals, the total volume of water in Consumption, number of households, unemployment rate, the employment rate in agriculture, literacy rate, rial value of tree products, rial value of rainfed products, rial value of summer crops, rial value of light livestock products, rial value of heavy livestock products, agricultural and medium irrigated land area Slope of villages to percent.
Water productivity has been used to calculate the rial value of livestock products, agricultural products, and human variables. The study area of this research is the Qaleh chai which has 36 villages located in it. The region of this basin is equal to 249.63 square kilometers, which has located in East Azerbaijan province and the southeast of Lake Urmia.
Discussion and conclusion
Research Findings show that the number of spring water resources is higher in mountainous villages and, the number of wells is higher in plain rural. The results of Moran showed that the variables of the Iranian Rial value of livestock production and the total amount of available water lack spatial autocorrelation. Also, the variable of the Iranian Rial value of all agricultural products has no spatial autocorrelation, but the total number of water resources has a spatial correlation. There is also an intense spatial correlation in the average slope of the villages, but the results of this test on the final water productivity lack spatial correlation. According to the results, the literacy variable of spatial autocorrelation is cluster type. The variables of household size and employment have no spatial correlation. Results The GWR regarding the causal role of the variable related to the final value of agricultural products and livestock products with water productivity showed that the last value of products with a correlation of R2 = 229 can explain water productivity. Based on the results of the geographical weight regression test, the value of R2 for social variables was equal to R2 = 0.129, which is lower than the final value variables of livestock and agricultural products.
Findings of this study show that factors such as the number of agricultural products produced, water resources, the volume of water available from water resources, land slope, number of water pumps and Iranian Rial value of livestock and agricultural products, literacy rate, employment rate, population have a significant relationship with water productivity. According to the research findings, it is clear that to achieve an efficient solution to improve water productivity in the villages located in the Qalah Chai watershed, it must have all the operative factors, including natural elements. Human factors, management factors, and physical characteristics are based on accurate, reliable data and planning occurrence.
Hossein Karimzadeh, Sima Saadi,
Volume 11, Issue 39 (Spring 2022 2022)
Volume 11, Issue 39 (Spring 2022 2022)
Abstract
Introduction
Despite the fact that the number of female entrepreneurs is growing, data shows that they grow at a slower rate than male entrepreneurs due to the difficulties and challenges they face. There have always been several obstacles and challenges in founding and growing enterprises, whether in urban or rural settings. On the other hand, the resources and contexts available for entrepreneurship can help to mitigate some of the barriers and challenges; in other words, the right geographical location and easy access to resources can help to foster entrepreneurship development, which is the foundation for regional development. Additionally, urban and rural women entrepreneurs play essential roles in the economic growth, particularly in developing and underprivileged countries. The World Bank claims that investing more in female entrepreneurship will result in a nation's development. The reasons are women's empowerment in society (whether urban or rural) eliminates inequality and poverty, and women are the first hope for family development and country development in underdeveloped countries. Female entrepreneurs' success in these societies benefits not only the economy but also the social and cultural structure. Nonetheless, women entrepreneurs confront numerous challenges, just like other groups of entrepreneurs.
Methodology
The study's statistical population is made up of women aged 15 to 65 who live in Marivan City and its surrounding villages. According to the statistical population of 65081 women between the ages of 15 and 65 in Marivan, 189 samples were chosen using Cochran's formula. In addition, 9 villages were chosen from a total of 93 villages in Marivan County based on their distance from the city: 3 villages within 0-5 km of the city (close), 3 villages within 5-10 km of the city (medium), and 3 villages at a distance of 10-15 km from the city (far). According to the statistical population (827), there are 113 questionnaires distributed in the villages indicated. For statistical analysis of the research, the one-sample t-test and ANOVA have used in SPSS 22 software, and for spatial analysis of the research ArcGIS software was used.
Discussion and conclusion
According to the research findings in the economic and political dimensions, women entrepreneurship growth in the both study area's settlements, namely rural areas and Marivan City, are not at the required level. The reasons are the lack of private investment in the region to build enterprises, the lack of banks and institutions offering loans and financial credits in rural regions, the existence of extreme poverty in the region, particularly in rural areas, lack risk-taking, lack of government assistance, lack of action in villages or municipalities to build and promote women's entrepreneurship, lack of public sector cooperation in investing in new firms, and so on. It should be mentioned that the status are considerably better in urban regions than rural ones. These findings are congruent with Sivanesan's 2014 study comparing rural and urban female entrepreneurship in India, as well as Robinson et al. (2004) and Rasekhi et al (2018). Marivan City has a better social and infrastructural status than rural areas in both social and infrastructural terms. Lack of participation of women in business organizations, unions, and guilds, lack of educational fields related to entrepreneurship in rural areas, lack of social security for women in the marketplace, lack of cooperation of rural managers with women, lack of a class or organization of women entrepreneurs, lack of appropriate technology infrastructure in rural areas are some of the reasons for this. These findings are in line with a 2011 study by Angela Davis comparing the priorities of urban and rural entrepreneurs' service demands, as well as studies by Asitik (2015) and Anthopoulou (2016). (2010). Both towns are in good shape in terms of individual dimensions, but when comparing the averages of the two, Marivan is in a better position than rural areas (cities with an average of 3.96 and villages with an average of 3.04). Individual qualities and backgrounds of entrepreneurship in the inhabitants of the research area, such as readiness to confront challenges and difficulties, not escaping unpleasant situations, people's level of responsibility, self-reliance, and acceptability, could be the cause for this. These findings are in line with those of a 2013 study in Kentucky by Hyunjeong Joo, which compared rural and urban entrepreneurs. There is a substantial difference in the mean of the desired dimensions, according to the analysis of the variance test. In addition, according to the post hoc test, the city of Marivan has the biggest differences from other groups, i.e. rural groups, in all of the analyzed characteristics. The city of Marivan has a better situation in the field of female entrepreneurship development than the rural areas analyzed, according to the findings of a spatial analysis of research in ArcGIS software. Due to the fact that the rural areas studied had an unfavorable situation in this regard, we have measured these areas by distance from the city. According to GIS maps, the villages near the city of Marivan, especially Bileh and Tazehabad, are in a more favorable situation than other rural areas. The reason for this can be considered the proximity of these villages to the city of Marivan.
Despite the fact that the number of female entrepreneurs is growing, data shows that they grow at a slower rate than male entrepreneurs due to the difficulties and challenges they face. There have always been several obstacles and challenges in founding and growing enterprises, whether in urban or rural settings. On the other hand, the resources and contexts available for entrepreneurship can help to mitigate some of the barriers and challenges; in other words, the right geographical location and easy access to resources can help to foster entrepreneurship development, which is the foundation for regional development. Additionally, urban and rural women entrepreneurs play essential roles in the economic growth, particularly in developing and underprivileged countries. The World Bank claims that investing more in female entrepreneurship will result in a nation's development. The reasons are women's empowerment in society (whether urban or rural) eliminates inequality and poverty, and women are the first hope for family development and country development in underdeveloped countries. Female entrepreneurs' success in these societies benefits not only the economy but also the social and cultural structure. Nonetheless, women entrepreneurs confront numerous challenges, just like other groups of entrepreneurs.
Methodology
The study's statistical population is made up of women aged 15 to 65 who live in Marivan City and its surrounding villages. According to the statistical population of 65081 women between the ages of 15 and 65 in Marivan, 189 samples were chosen using Cochran's formula. In addition, 9 villages were chosen from a total of 93 villages in Marivan County based on their distance from the city: 3 villages within 0-5 km of the city (close), 3 villages within 5-10 km of the city (medium), and 3 villages at a distance of 10-15 km from the city (far). According to the statistical population (827), there are 113 questionnaires distributed in the villages indicated. For statistical analysis of the research, the one-sample t-test and ANOVA have used in SPSS 22 software, and for spatial analysis of the research ArcGIS software was used.
Discussion and conclusion
According to the research findings in the economic and political dimensions, women entrepreneurship growth in the both study area's settlements, namely rural areas and Marivan City, are not at the required level. The reasons are the lack of private investment in the region to build enterprises, the lack of banks and institutions offering loans and financial credits in rural regions, the existence of extreme poverty in the region, particularly in rural areas, lack risk-taking, lack of government assistance, lack of action in villages or municipalities to build and promote women's entrepreneurship, lack of public sector cooperation in investing in new firms, and so on. It should be mentioned that the status are considerably better in urban regions than rural ones. These findings are congruent with Sivanesan's 2014 study comparing rural and urban female entrepreneurship in India, as well as Robinson et al. (2004) and Rasekhi et al (2018). Marivan City has a better social and infrastructural status than rural areas in both social and infrastructural terms. Lack of participation of women in business organizations, unions, and guilds, lack of educational fields related to entrepreneurship in rural areas, lack of social security for women in the marketplace, lack of cooperation of rural managers with women, lack of a class or organization of women entrepreneurs, lack of appropriate technology infrastructure in rural areas are some of the reasons for this. These findings are in line with a 2011 study by Angela Davis comparing the priorities of urban and rural entrepreneurs' service demands, as well as studies by Asitik (2015) and Anthopoulou (2016). (2010). Both towns are in good shape in terms of individual dimensions, but when comparing the averages of the two, Marivan is in a better position than rural areas (cities with an average of 3.96 and villages with an average of 3.04). Individual qualities and backgrounds of entrepreneurship in the inhabitants of the research area, such as readiness to confront challenges and difficulties, not escaping unpleasant situations, people's level of responsibility, self-reliance, and acceptability, could be the cause for this. These findings are in line with those of a 2013 study in Kentucky by Hyunjeong Joo, which compared rural and urban entrepreneurs. There is a substantial difference in the mean of the desired dimensions, according to the analysis of the variance test. In addition, according to the post hoc test, the city of Marivan has the biggest differences from other groups, i.e. rural groups, in all of the analyzed characteristics. The city of Marivan has a better situation in the field of female entrepreneurship development than the rural areas analyzed, according to the findings of a spatial analysis of research in ArcGIS software. Due to the fact that the rural areas studied had an unfavorable situation in this regard, we have measured these areas by distance from the city. According to GIS maps, the villages near the city of Marivan, especially Bileh and Tazehabad, are in a more favorable situation than other rural areas. The reason for this can be considered the proximity of these villages to the city of Marivan.
Hossein Karimzadeh , Aghil Khaleghi, Ahad Bashiri ,
Volume 11, Issue 41 (Fall 2022 2022)
Volume 11, Issue 41 (Fall 2022 2022)
Abstract
Introduction
Rural development goals cannot be limited to agricultural and economic growth, and economic and social development needs to be balanced for fair income distribution and rapid creation of benefits from high levels of living. As a result, local planners should know the strength and weaknesses of the local economy. In addition, local economic development planners should know the status of the development of activities in the region and whether their distribution has a competitive advantage.
In this study, we aim to determine the employment status of major sectors and activity groups in Iranian rural areas from 2011 to 2016 and examine the entry and exit of the workforce. So the research questions are:
Which sectors have had the most negative and positive impact on the change in share and place of employment among the different economic sectors?
What was the status of different economic sectors at the level of the country's provinces during 2011-2016?
Has the activity in the agricultural sector faced positive growth from 2011 to 2016?
Methodology
This study used the change-share method to analyze the employment status of the main sectors and groups of economic activity in Iranian rural areas of the provinces from 2011 through 2016. Also, the spatial coefficient index was used for the labour force's entry and exit conditions. Is. The data used in this study is based on the statistics of the Iran Statistics Center.
Discussion and conclusion
According to Keynes, the government should intervene in the economy to achieve full employment. There is a direct relationship between the level of employment and the amount of production, which is related to the effective demand. The distribution of employees shows a growth of 226,590 people between 2011 and 2016. In the share of employment, the agricultural sector has decreased by about 0.1%, the industry sector's share was 2.6% with negative growth, and the service sector share increased by about 2.7%, which shows that the service sector has a high growth compared to other sectors. Regarding the Keynesian economic balance in employment, policymakers should change monetary policies, such as reducing the bank interest rate, and the assets, such as real estate, by imposing taxes on depreciated properties.
The research results show that the rural areas of 13 provinces in the Agriculture, Industry, and Services sectors had basic activities in 2015 in more than ten rural areas. Also, the relative growth of economic sectors in the whole reference economy or the effect of industrial composition (IS) shows that the share of employment in the agricultural sector decreased from 50.4% to 50.3%. In addition, the provinces of Khorasan Razavi, West Azerbaijan and Fars had the highest losses, and the province Alborz, Qom and Semnan had the least losses of employment in the agricultural sector. On the other hand, the least losses in the industry sector were in the provinces of East Azerbaijan, Khorasan Razavi and Fars, and the most employment losses were in Qom, Semnan and Ilam. The increase in service sector employment in Mazandaran, Fars and Tehran provinces was the highest, while Qom, South Khorasan and Semnan Provinces had the lowest increase.
South Khorasan province had the best performance in terms of service sector increase. For the agriculture sector, Hormozgan, Kerman and Khuzestan provinces and Hormozgan and Alborz provinces had good performances in the industry sector. This implies that with the increase in the productivity gap between the production and service sectors, the working population moves from the industry and agriculture sectors to the service sector. The main reason for the expansion of services is the growth of information technology because of its role in solving the unemployment problem and developing the country's economy.
According to the results, the agricultural and industrial sectors in the country's rural areas have no relative advantage in employment. The agricultural sector, considered a non-core activity in the rural areas of Khuzestan province in 2011, became a core activity in 2016. In Fars, it changed from a core activity to a non-core activity. The industry sector in Ilam, Bushehr and Lorestan provinces has changed from non-core to core activity and in Khuzestan province, from core to non-core activity. The service sector changed from a non-core activity in Sistan and Baluchistan, and Qazvin provinces to a core activity. However, in Hamedan province, it changed from a core activity to a non-core activity.
Rural development goals cannot be limited to agricultural and economic growth, and economic and social development needs to be balanced for fair income distribution and rapid creation of benefits from high levels of living. As a result, local planners should know the strength and weaknesses of the local economy. In addition, local economic development planners should know the status of the development of activities in the region and whether their distribution has a competitive advantage.
In this study, we aim to determine the employment status of major sectors and activity groups in Iranian rural areas from 2011 to 2016 and examine the entry and exit of the workforce. So the research questions are:
Which sectors have had the most negative and positive impact on the change in share and place of employment among the different economic sectors?
What was the status of different economic sectors at the level of the country's provinces during 2011-2016?
Has the activity in the agricultural sector faced positive growth from 2011 to 2016?
Methodology
This study used the change-share method to analyze the employment status of the main sectors and groups of economic activity in Iranian rural areas of the provinces from 2011 through 2016. Also, the spatial coefficient index was used for the labour force's entry and exit conditions. Is. The data used in this study is based on the statistics of the Iran Statistics Center.
Discussion and conclusion
According to Keynes, the government should intervene in the economy to achieve full employment. There is a direct relationship between the level of employment and the amount of production, which is related to the effective demand. The distribution of employees shows a growth of 226,590 people between 2011 and 2016. In the share of employment, the agricultural sector has decreased by about 0.1%, the industry sector's share was 2.6% with negative growth, and the service sector share increased by about 2.7%, which shows that the service sector has a high growth compared to other sectors. Regarding the Keynesian economic balance in employment, policymakers should change monetary policies, such as reducing the bank interest rate, and the assets, such as real estate, by imposing taxes on depreciated properties.
The research results show that the rural areas of 13 provinces in the Agriculture, Industry, and Services sectors had basic activities in 2015 in more than ten rural areas. Also, the relative growth of economic sectors in the whole reference economy or the effect of industrial composition (IS) shows that the share of employment in the agricultural sector decreased from 50.4% to 50.3%. In addition, the provinces of Khorasan Razavi, West Azerbaijan and Fars had the highest losses, and the province Alborz, Qom and Semnan had the least losses of employment in the agricultural sector. On the other hand, the least losses in the industry sector were in the provinces of East Azerbaijan, Khorasan Razavi and Fars, and the most employment losses were in Qom, Semnan and Ilam. The increase in service sector employment in Mazandaran, Fars and Tehran provinces was the highest, while Qom, South Khorasan and Semnan Provinces had the lowest increase.
South Khorasan province had the best performance in terms of service sector increase. For the agriculture sector, Hormozgan, Kerman and Khuzestan provinces and Hormozgan and Alborz provinces had good performances in the industry sector. This implies that with the increase in the productivity gap between the production and service sectors, the working population moves from the industry and agriculture sectors to the service sector. The main reason for the expansion of services is the growth of information technology because of its role in solving the unemployment problem and developing the country's economy.
According to the results, the agricultural and industrial sectors in the country's rural areas have no relative advantage in employment. The agricultural sector, considered a non-core activity in the rural areas of Khuzestan province in 2011, became a core activity in 2016. In Fars, it changed from a core activity to a non-core activity. The industry sector in Ilam, Bushehr and Lorestan provinces has changed from non-core to core activity and in Khuzestan province, from core to non-core activity. The service sector changed from a non-core activity in Sistan and Baluchistan, and Qazvin provinces to a core activity. However, in Hamedan province, it changed from a core activity to a non-core activity.
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