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Showing 9 results for Gini Coefficient
Dr Esmaiel Abounoori, Dr Anahita Roozitalab,
Volume 0, Issue 0 (12-2024)
Volume 0, Issue 0 (12-2024)
Abstract
Aim and Introduction
Inequality is a multidimensional phenomenon that affects various aspects of households' lives. The economic well-being of individuals depends not only on their income but also on other factors such as access to healthcare, education, transportation, etc. Therefore, one-dimensional methods (income-focused) are insufficient for measuring inequality. The multidimensional approach to inequality considers different aspects of individual welfare, unlike the one-dimensional approach. The concentration of population and activities in some provinces of Iran, along with macroeconomic indicators (inflation and unemployment), exacerbates inequality. These inequalities affect various dimensions of people's lives and endanger their economic welfare. The primary aim of this study is to examine the effects of inflation and unemployment on multidimensional inequality in the provinces of Iran and their reciprocal effects on each other, using a multidimensional Gini coefficient estimated from the household budget microdata of the Statistical Center of Iran for the years 2000-2021.
Methodology
In this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been estimated for 9 dimensions of welfare. Then, the effects of inflation and unemployment, along with variables such as per capita real government expenditure and per capita real financial facilities as indicators of financial development, will be analyzed using a spatial econometric model. The mathematical form of the multidimensional Gini coefficient (MGI) is as follows:
Here, the mathematical formula would be inserted) In this equation: represents the non-increasing rank of the unit under study in the individual's overall welfare vector, and represents the sample size. The range of this index fluctuates between zero (completely equal distribution) and one (completely unequal distribution). For measuring multidimensional inequality in this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been used which is based on the microdata from the household expenditure (income) survey of the Statistical Center of Iran and involves data mining processes such as aggregating groups of beverages and tobacco, ready meals with food expenditure groups, and communications with transportation, and extracting data related to each household code in each province using R Studio 2020 software. The model is based on the spatial econometric method with spatial panel data, defined using a proximity method in which provinces sharing a border have an element of one and otherwise zero. The adjacency matrix (spatial weight) is normalized, where neighboring provinces carry the most weight, and distant provinces carry the least.
Findings
The results of estimating the multidimensional Gini coefficient for the provinces during 2000-2021 show that most provinces have experienced a high rate of inequality. Provinces such as Bushehr, Khuzestan, Kermanshah, Kurdistan, Markazi, Qazvin, Qom, Semnan, Sistan and Baluchestan, West Azerbaijan, Zanjan, and Yazd are in an unfavorable condition compared to the country, and most of these provinces are border regions. Over these 22 years, Sistan and Baluchestan with 77.66% have the highest rate of multidimensional inequality, while Isfahan with 60.85% has the lowest among the provinces. Additionally, the findings indicate that inflation, unemployment, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on multidimensional inequality in the provinces of Iran. The proximity of provinces has also worsened the inequality conditions in the neighboring provinces.
Discussion and Conclusion
Four variables including unemployment, inflation, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on the multidimensional Gini coefficient, worsening income distribution. The most significant impact is seen with per capita real government expenditure, which is not allocated effectively to enhance welfare and improve economic conditions, thus not improving income distribution and reducing inequality. The effects of the other variables are in the following order: per capita real disbursed financial facilities, unemployment, and inflation. It is recommended to consider all welfare dimensions in the household consumption basket, create equal conditions for access to bank facilities, allocate a specific quota of facilities to lessdeveloped provinces, allocate government expenditures to expand public services and infrastructure in deprived provinces, consider the interactive effects between provinces in policymaking, and implement effective policies to improve welfare conditions and balanced income distribution across all provinces
Inequality is a multidimensional phenomenon that affects various aspects of households' lives. The economic well-being of individuals depends not only on their income but also on other factors such as access to healthcare, education, transportation, etc. Therefore, one-dimensional methods (income-focused) are insufficient for measuring inequality. The multidimensional approach to inequality considers different aspects of individual welfare, unlike the one-dimensional approach. The concentration of population and activities in some provinces of Iran, along with macroeconomic indicators (inflation and unemployment), exacerbates inequality. These inequalities affect various dimensions of people's lives and endanger their economic welfare. The primary aim of this study is to examine the effects of inflation and unemployment on multidimensional inequality in the provinces of Iran and their reciprocal effects on each other, using a multidimensional Gini coefficient estimated from the household budget microdata of the Statistical Center of Iran for the years 2000-2021.
Methodology
In this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been estimated for 9 dimensions of welfare. Then, the effects of inflation and unemployment, along with variables such as per capita real government expenditure and per capita real financial facilities as indicators of financial development, will be analyzed using a spatial econometric model. The mathematical form of the multidimensional Gini coefficient (MGI) is as follows:
Here, the mathematical formula would be inserted) In this equation: represents the non-increasing rank of the unit under study in the individual's overall welfare vector, and represents the sample size. The range of this index fluctuates between zero (completely equal distribution) and one (completely unequal distribution). For measuring multidimensional inequality in this study, the multidimensional Gini coefficient by Kumar Banerjee (2010) has been used which is based on the microdata from the household expenditure (income) survey of the Statistical Center of Iran and involves data mining processes such as aggregating groups of beverages and tobacco, ready meals with food expenditure groups, and communications with transportation, and extracting data related to each household code in each province using R Studio 2020 software. The model is based on the spatial econometric method with spatial panel data, defined using a proximity method in which provinces sharing a border have an element of one and otherwise zero. The adjacency matrix (spatial weight) is normalized, where neighboring provinces carry the most weight, and distant provinces carry the least.
Findings
The results of estimating the multidimensional Gini coefficient for the provinces during 2000-2021 show that most provinces have experienced a high rate of inequality. Provinces such as Bushehr, Khuzestan, Kermanshah, Kurdistan, Markazi, Qazvin, Qom, Semnan, Sistan and Baluchestan, West Azerbaijan, Zanjan, and Yazd are in an unfavorable condition compared to the country, and most of these provinces are border regions. Over these 22 years, Sistan and Baluchestan with 77.66% have the highest rate of multidimensional inequality, while Isfahan with 60.85% has the lowest among the provinces. Additionally, the findings indicate that inflation, unemployment, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on multidimensional inequality in the provinces of Iran. The proximity of provinces has also worsened the inequality conditions in the neighboring provinces.
Discussion and Conclusion
Four variables including unemployment, inflation, per capita real government expenditure, and per capita real disbursed financial facilities have a significant positive effect on the multidimensional Gini coefficient, worsening income distribution. The most significant impact is seen with per capita real government expenditure, which is not allocated effectively to enhance welfare and improve economic conditions, thus not improving income distribution and reducing inequality. The effects of the other variables are in the following order: per capita real disbursed financial facilities, unemployment, and inflation. It is recommended to consider all welfare dimensions in the household consumption basket, create equal conditions for access to bank facilities, allocate a specific quota of facilities to lessdeveloped provinces, allocate government expenditures to expand public services and infrastructure in deprived provinces, consider the interactive effects between provinces in policymaking, and implement effective policies to improve welfare conditions and balanced income distribution across all provinces
Golnar Khalesi, Khosrow Piraee,
Volume 16, Issue 2 (8-2016)
Volume 16, Issue 2 (8-2016)
Abstract
One of the fundamental problems in regional economic development is determining the ways in which government can allocate resources of society so that economic growth and income equality among provinces can be achieved simultaneously. In this study, a Vector Auto Regressive Model is estimated using seasonal data during Q1: 2000- Q4:2009. Inter-provincial income inequality is obtained with both Gini Coefficient and Theil Index. The results show that, in short run, income inequality among provinces accelerates economic growth and in long run decelerates it, however, it does not return to its initial level. Economic growth in short run accelerates income inequality among provinces, but decelerates it in long run. Robustness tests with Theil Index, confirm our primary results applying Gini Coefficient.
Batol Rafat, Elaheh Jazizadeh,
Volume 16, Issue 3 (11-2016)
Volume 16, Issue 3 (11-2016)
Abstract
Distribution of income in society is so important that almost all economists consider it as one of the main aims and missions of the government. As credit constraints cause inequality in society, thus the development of financial intermediaries and financial markets in national level, which affects access of the low-income and poor individuals to credit and financial services, can influence significantly income redistribution in the country. This study aims to examine the relationship between financial development and inequality among the Iranian provinces. By using fixed effects panel data model, and applying Galor-Zeira theory, the relationship between financial development and income distribution is tested in Iran during 2000-2011. The results show that increasing proliferation of financial intermediaries has negative impact on Gini coefficient and results in more equitable income distribution across the provinces.
Dr Hossein Raghfar, Dr Esmaeel Safarzadeh, Fahime Aliakbari Salami,
Volume 18, Issue 1 (4-2018)
Volume 18, Issue 1 (4-2018)
Abstract
Inequality is a major problem in the developing countries. It is also an acute and critical subject in Iran compared with other developing economies. Besides the existence of inequality, its social effects have made its explanation crucial. The aim of this research is to measure the multidimensional inequality in urban areas of Iran during three presidential periods: 1989 -1997, 1997-2005 and 2005-2013. Income, health and education are the dimensions under study. This research uses household expenditure-income survey data for the selected periods. Gini coefficient is measured for one-dimensional inequalities in terms of each dimension, generalized entropy is computed for the beginning and ending years of each period, and the multidimensional inequality is measured by using the Bourguignon index. Results indicate that the Gini coefficient decreased in terms of income dimension in all three periods while it increased in terms of health dimension during all periods. In education dimension, Gini index increased in the second period and decreased in other periods. The measured entropy indices are of some fluctuations in all periods for all dimensions. The measured multidimensional inequality index provides a wide range of results for different substitution and inequality aversion parameters. In general, this index indicates worse conditions in the second period compared with other periods.
Parviz Davoodi, Mr. Mohammad Sarlab,
Volume 19, Issue 2 (6-2019)
Volume 19, Issue 2 (6-2019)
Abstract
Improving the distribution of income is one of the main goals of governments in economic policy, regardless of the orientation of different systems. The purpose of this study is to investigate the distributive effects of monetary policy on income distribution in urban and rural areas of Iran. In this regard, the values of macroeconomic variables during the period of 1959-2014 and the household budget data over the period of 1997-2014 were used. The monetary policy was considered in three scenarios, including the increase in facilities granted to the private sector, the decrease in the reserve requirement ratio and decrease in the excess reserves ratio. The results showed that expansionary monetary policy improves the distribution of income in the short run, but in the long run it worsens the distribution of income due to its inflationary effect. An increase in facilities granted in the short term reduces the Gini coefficient in urban and rural areas, and whole country. However, it increases the Gini coefficients in all three sections in the long run. Reducing the reserve requirement ratio in the short run reduces Gini coefficients, but it does not change the whole Gini coefficient in the long run, but it increases the Gini coefficients in urban and rural areas. The effect of reducing excess reserves ratio is similar to that of reducing reserve requirement ratio.
Mr. Reza Shakeri Bostanabad, Dr. Zahra Jalili,
Volume 20, Issue 4 (12-2020)
Volume 20, Issue 4 (12-2020)
Abstract
The distribution of resources and potentials is of crucial importance in the regional economy, social justice, poverty reduction and economic growth and development. Thus, fair distribution of income is one of the most important concerns of policymakers and economic researchers. However, since the income distribution index (Gini coefficient) is limited to range between zero and one, the use of standard linear models may not measure accurately the effect of other variables on it. Therefore, this study attempts to identify the variables affecting income distribution in the provinces of Iran over the period 2005-2016 using a Fractional Panel Probit Model. This approach is able to estimate the average partial effects of dependent variables with fractional data ranging from zero to one. The results show that the relationship between economic growth and income distribution does not support the Kuznets’s hypothesis. Among the control variables, per capita government expenditure, financial development and inflation have negative and significant effects on the Gini coefficient. According to the findings, it is suggested that the government should implement policies to promote financial development and to increase the efficiency of financial instruments, as well as to invest on education and health in order to benefit all strata of society.
Volume 22, Issue 3 (4-2020)
Abstract
In Iran, allocating tractors and agricultural machinery to regions that have different characteristics has been a challenge. This study was carried out in order to develop an optimal and practical model for distribution of agricultural machinery throughout the country. Gini coefficient was used in order to investigate whether current status of tractor distribution is suitable. This coefficient confirmed that the current tractor power distribution is not appropriate since there were no relationships between Gini coefficient of distributed machinery power and crop production or farm area. Accordingly, two main techniques were applied to develop a suitable agricultural machinery distribution pattern; i.e. a Fuzzy Analytical Hierarchy Process (FAHP) and a Weight Restriction Data Envelopment analysis (WR-DEA) technique. A power distribution category was defined in order to show qualitatively how much machinery power should be sent to each province. The outputs of both FAHP and WR-DEA models showed that three and nine provinces need ‘much more power’ and ‘more power’, respectively, while four and three provinces need ‘absolutely no more power’ and are ‘currently suitable’, respectively. The sensitivity analysis revealed that none of the developed models was sensitive to the weights defined by a panel of experts. The similarity of the results obtained from both models implies that the provided agricultural machinery distribution pattern is reliable and can be used in the country.
Mrs Maryam Rishehchi Fayyaz, Dr Mohammad Ali Falahi, Dr Mehdi Feizi,
Volume 24, Issue 3 (9-2024)
Volume 24, Issue 3 (9-2024)
Abstract
Introduction
Inequality in income distribution and social class inequality are among the most serious challenges faced by societies. Revolutionary movements often strive to reduce inequality and establish a more just society. The social class inequality and unfair income distribution have adverse social, economic, and cultural impacts on the community. Therefore, one of the governments’ primary and essential tasks is to create equitable opportunities and address social inequalities. Therefore, it is necessary to identify the influential factors and define precise and reliable variables for measuring inequality.
Methodology
In this research, various methods for estimating the Gini coefficient are applied. This thesis will employ panel data models to investigate the effects of variables such as employment rate in the service sector, per capita income, inflation, and government expenditure on the Gini coefficient.
Results and Discussion
The final results of this study demonstrate that: first, per capita income significantly negatively impacts income inequality in the studied provinces during this period. In other words, as the per capita income of provinces increases, the level of income inequality decreases. Second, according to the findings of this research, government expenditure in each province have a positive and meaningful effect on income inequality. As government expenditure increases, income inequality will also rise. Inflation also positively and significantly impacts inequality, as increasing inflation leads to higher income inequality among provinces. Finally, employment in the service sector has a positive and significant effect on income inequality in the Iranian provinces, meaning that as the employment share in the service sector increases, income inequality will also increase.
Conclusion
Income inequality does not solely encompass economic issues, it will also extend to a wide range of social, economic, and even political matters. For this reason, achieving social justice has been one of the most complex and significant responsibilities of governments throughout history. Establishing fairness and equality in society can lead to development goals, economic growth, prosperity, increased security, and overall societal well-being. To attain a reasonable level of income equality, it is imperative first to define a suitable index for measuring the extent of inequality that is precise, measurable, and reliable. Subsequently, it is necessary to identify the key and influential factors contributing to income inequality and, ultimately, take steps to reduce income inequality."
The main objective of this research is to investigate the impact of employment in the service sector on income inequality in the provinces of Iran during the years 2011-2019. As the results have shown, throughout the study period, employment in the service sector has affected income inequality in the Iran's provinces. However, contrary to the results in most developed countries, employment in the service sector has worsened income inequality in provinces. There are multiple reasons for the results obtained. As explained in the theoretical background, a major contributing factor in developing countries like Iran is the prevalence of low-paying service jobs that attract many individuals. Many service jobs within this category do not require specialized skills or infrastructure, making them appealing to individuals seeking employment. Employing more individuals from this group in service jobs does not decrease income inequality. It may exacerbate income inequality within society.
In all economies, service sector complements other sectors and facilitates the conduct of different activities, greatly influencing the quality of outcome. If educational, health, and recreational services are not available in society, the workforce will not be efficient, and desirable productivity will not be achieved, thus affecting the economy negatively. In addition, in production sector, service institutions have the highest efficiency in adding value to goods. Service institutions can be divided into three main categories: (1) primary institutions, including research and development institutions. (2) secondarty institutions that operate in activities such as engineering, legal, and consultancy services. (3) Final institutions that play a role in activities such as packaging, sales, and advertising. Another advantage of the service sector is related to education. The more educated the workforce, the higher the productivity level will be.
The concepts mentioned above are just a few of the job advantages in service sector. Nevertheless, in most developing countries, including Iran, more attention is paid to the industrial sector. This is despite World Bank data showing that about 70-80 percent of employment in advanced countries is in service sector, and special attention is paid to that. Most fundamental discussions also revolve around employment opportunities there. Despite all the advantages and experiences of different countries, Iran has not been able to use the existing capacities in this sector effectively. Many policymakers still view the service sector as low-level jobs, brokerage, and intermediaries, which has prevented serious attention to this sector, even though the service sector includes profitable jobs and contributes significantly to the growth and development of the country. Employment in this sector can also help employment in the industrial and agricultural sectors achieve higher productivity levels.
Inequality in income distribution and social class inequality are among the most serious challenges faced by societies. Revolutionary movements often strive to reduce inequality and establish a more just society. The social class inequality and unfair income distribution have adverse social, economic, and cultural impacts on the community. Therefore, one of the governments’ primary and essential tasks is to create equitable opportunities and address social inequalities. Therefore, it is necessary to identify the influential factors and define precise and reliable variables for measuring inequality.
Methodology
In this research, various methods for estimating the Gini coefficient are applied. This thesis will employ panel data models to investigate the effects of variables such as employment rate in the service sector, per capita income, inflation, and government expenditure on the Gini coefficient.
Results and Discussion
The final results of this study demonstrate that: first, per capita income significantly negatively impacts income inequality in the studied provinces during this period. In other words, as the per capita income of provinces increases, the level of income inequality decreases. Second, according to the findings of this research, government expenditure in each province have a positive and meaningful effect on income inequality. As government expenditure increases, income inequality will also rise. Inflation also positively and significantly impacts inequality, as increasing inflation leads to higher income inequality among provinces. Finally, employment in the service sector has a positive and significant effect on income inequality in the Iranian provinces, meaning that as the employment share in the service sector increases, income inequality will also increase.
Conclusion
Income inequality does not solely encompass economic issues, it will also extend to a wide range of social, economic, and even political matters. For this reason, achieving social justice has been one of the most complex and significant responsibilities of governments throughout history. Establishing fairness and equality in society can lead to development goals, economic growth, prosperity, increased security, and overall societal well-being. To attain a reasonable level of income equality, it is imperative first to define a suitable index for measuring the extent of inequality that is precise, measurable, and reliable. Subsequently, it is necessary to identify the key and influential factors contributing to income inequality and, ultimately, take steps to reduce income inequality."
The main objective of this research is to investigate the impact of employment in the service sector on income inequality in the provinces of Iran during the years 2011-2019. As the results have shown, throughout the study period, employment in the service sector has affected income inequality in the Iran's provinces. However, contrary to the results in most developed countries, employment in the service sector has worsened income inequality in provinces. There are multiple reasons for the results obtained. As explained in the theoretical background, a major contributing factor in developing countries like Iran is the prevalence of low-paying service jobs that attract many individuals. Many service jobs within this category do not require specialized skills or infrastructure, making them appealing to individuals seeking employment. Employing more individuals from this group in service jobs does not decrease income inequality. It may exacerbate income inequality within society.
In all economies, service sector complements other sectors and facilitates the conduct of different activities, greatly influencing the quality of outcome. If educational, health, and recreational services are not available in society, the workforce will not be efficient, and desirable productivity will not be achieved, thus affecting the economy negatively. In addition, in production sector, service institutions have the highest efficiency in adding value to goods. Service institutions can be divided into three main categories: (1) primary institutions, including research and development institutions. (2) secondarty institutions that operate in activities such as engineering, legal, and consultancy services. (3) Final institutions that play a role in activities such as packaging, sales, and advertising. Another advantage of the service sector is related to education. The more educated the workforce, the higher the productivity level will be.
The concepts mentioned above are just a few of the job advantages in service sector. Nevertheless, in most developing countries, including Iran, more attention is paid to the industrial sector. This is despite World Bank data showing that about 70-80 percent of employment in advanced countries is in service sector, and special attention is paid to that. Most fundamental discussions also revolve around employment opportunities there. Despite all the advantages and experiences of different countries, Iran has not been able to use the existing capacities in this sector effectively. Many policymakers still view the service sector as low-level jobs, brokerage, and intermediaries, which has prevented serious attention to this sector, even though the service sector includes profitable jobs and contributes significantly to the growth and development of the country. Employment in this sector can also help employment in the industrial and agricultural sectors achieve higher productivity levels.
Mrs Marziyeh Hosini, Dr Monireh Rafat,
Volume 25, Issue 1 (3-2025)
Volume 25, Issue 1 (3-2025)
Abstract
Aim and Introduction
Inclusive growth strategy is a new concept in the field of growth and development in the economy, which is used by policymakers in a special way. In various political discourses, inclusive growth is a result of basic meanings such as large and fair growth, economic growth in alinmment with the development of human growth, pro-poor, accessible and participatory growth, sustainable growth from an economic and environmental perspective, and many private concepts. On the other hand, foreign direct investment (FDI) can be considered as a means of financing countries, which is one of the best tools for economic development.
Considering its contribution and long-term implication, it is a narrow approach to lemmatize the role of FDI in promoting economic growth only. The new developments in growth literature take poverty and inequality also in the account. Hence, the paper links FDI with a broader term, Inclusive Growth. Inclusive growth is a growth process that includes every segment of society. It creates and distributes opportunities in an equitable manner and utilizes a major part of the labour force. It also moves them out of poverty and enhances productive employment. The evidence from a long list of literature, consulted for this research suggest that the resulted effect of FDI on inclusive growth is highly defined by the host economy’s own institutional quality.
Methodology
In literature, inclusive growth is defined as the maximization of the social opportunity function. As it undertakes the spectrum of efficiency and equity under one umbrella. The concept of social opportunity function itself was derived from the idea of generalized concentration curve introduced initially by (Ali & Son, 2007) in inclusive growth literature. This concept of generalized concentration curve was later used to form social opportunity index by calculating the area under the curve (Anand, Mishra, and Peiris, 2013).
Considering the fact that opportunity can take any forms such as health care, education or several other monetary and non-monetary opportunities. The study will use income as a determinant of opportunity. As it is the most common and widely used measure of determining individuals’ access to certain other kinds of opportunities.
The aim of the present study is to analyze the effect of attracting foreign direct investment on inclusive growth in the Shanghai Cooperation members during the period of 2000-2022. Therefore, in order to calculate the inclusive growth index, to introduce the study model of this research and examine it the panel data method has been used. For estimating the model, threshold panel in Stata software has also been applied, to analyze the effect of foreign direct investment attraction on inclusive growth.
Results and Discussion
The results presented in this paper are fixed effect robust estimates, which automatically addresses any underlying existence of heteroscedasticity. Hausman specification test has been used to select between the two widely used panel estimation techniques, fixed and random effect estimation. Result for the overall sample of world economies shows a significant positive effect of FDI on inclusive growth and GDP. The estimation of the model was based on the fixed effects method in the stata software, and the results of the estimation of the model show that except for the exchange rate variable, the rest of the model variables have a significant effect on inclusive growth. The threshold limit for the foreign direct investment attraction variable is 4.875 billion dollars, based on which the Gini coefficient variable above and below this threshold limit will have different effects on inclusive growth. When the attraction of foreign direct investment is lower than this threshold, the Gini coefficient has a significant effect on the inclusive growth variable in the countries under study. In other words, with one unit increase in the Gini coefficient, it causes a decrease of 0.005 units in the inclusive growth index. This issue is in line with the view of dependency advocates.
The second key variable, institutional quality, has shown a significant effect on overall economic growth. The results show that a good and developed financial system may increase the available volume of financing investment. Supervision of investment projects that reduces the cost of obtaining information and increases productivity during projects and accelerates economic growth.
Conclusion
The purpose of the study was to investigate the proposition that, foreign direct investment can be used as a financing tool for growth inclusiveness. The study calculated and used the inclusive growth variable following the methodology of social welfare function which is also known as the social opportunity function.
The study reached to following conclusions:
Foreign direct investment can be used as a financing tool for inclusive growth. A deep underpinning of its impact on inclusive growth variable suggested that the impact of FDI on increasing the overall income is positive and significant. Yet it does not significantly influence the distribution of the opportunities. Hence, FDI does not influence inclusive growth through equity channel but by increasing the average opportunities.
The results of the research show that the Gini Coefficient Index, which is considered as a threshold change above and below the foreign investment attraction threshold, has a different effect on the overall growth index. When Foreign Direct Investment is less than the threshold, with a unit increase in the Gini Coefficient, leads to a worsening of the equitable distribution of income. As a result the index of inclusive growth, is in line with the views of the dependency theory. If Foreign Direct Investment is above the threshold, with one unit increase in the Gini Coefficient, which leads to a worsening of the equitable distribution of income, the index of inclusive growth increases, will be in line with the theory of modernization
Inclusive growth strategy is a new concept in the field of growth and development in the economy, which is used by policymakers in a special way. In various political discourses, inclusive growth is a result of basic meanings such as large and fair growth, economic growth in alinmment with the development of human growth, pro-poor, accessible and participatory growth, sustainable growth from an economic and environmental perspective, and many private concepts. On the other hand, foreign direct investment (FDI) can be considered as a means of financing countries, which is one of the best tools for economic development.
Considering its contribution and long-term implication, it is a narrow approach to lemmatize the role of FDI in promoting economic growth only. The new developments in growth literature take poverty and inequality also in the account. Hence, the paper links FDI with a broader term, Inclusive Growth. Inclusive growth is a growth process that includes every segment of society. It creates and distributes opportunities in an equitable manner and utilizes a major part of the labour force. It also moves them out of poverty and enhances productive employment. The evidence from a long list of literature, consulted for this research suggest that the resulted effect of FDI on inclusive growth is highly defined by the host economy’s own institutional quality.
Methodology
In literature, inclusive growth is defined as the maximization of the social opportunity function. As it undertakes the spectrum of efficiency and equity under one umbrella. The concept of social opportunity function itself was derived from the idea of generalized concentration curve introduced initially by (Ali & Son, 2007) in inclusive growth literature. This concept of generalized concentration curve was later used to form social opportunity index by calculating the area under the curve (Anand, Mishra, and Peiris, 2013).
Considering the fact that opportunity can take any forms such as health care, education or several other monetary and non-monetary opportunities. The study will use income as a determinant of opportunity. As it is the most common and widely used measure of determining individuals’ access to certain other kinds of opportunities.
The aim of the present study is to analyze the effect of attracting foreign direct investment on inclusive growth in the Shanghai Cooperation members during the period of 2000-2022. Therefore, in order to calculate the inclusive growth index, to introduce the study model of this research and examine it the panel data method has been used. For estimating the model, threshold panel in Stata software has also been applied, to analyze the effect of foreign direct investment attraction on inclusive growth.
Results and Discussion
The results presented in this paper are fixed effect robust estimates, which automatically addresses any underlying existence of heteroscedasticity. Hausman specification test has been used to select between the two widely used panel estimation techniques, fixed and random effect estimation. Result for the overall sample of world economies shows a significant positive effect of FDI on inclusive growth and GDP. The estimation of the model was based on the fixed effects method in the stata software, and the results of the estimation of the model show that except for the exchange rate variable, the rest of the model variables have a significant effect on inclusive growth. The threshold limit for the foreign direct investment attraction variable is 4.875 billion dollars, based on which the Gini coefficient variable above and below this threshold limit will have different effects on inclusive growth. When the attraction of foreign direct investment is lower than this threshold, the Gini coefficient has a significant effect on the inclusive growth variable in the countries under study. In other words, with one unit increase in the Gini coefficient, it causes a decrease of 0.005 units in the inclusive growth index. This issue is in line with the view of dependency advocates.
The second key variable, institutional quality, has shown a significant effect on overall economic growth. The results show that a good and developed financial system may increase the available volume of financing investment. Supervision of investment projects that reduces the cost of obtaining information and increases productivity during projects and accelerates economic growth.
Conclusion
The purpose of the study was to investigate the proposition that, foreign direct investment can be used as a financing tool for growth inclusiveness. The study calculated and used the inclusive growth variable following the methodology of social welfare function which is also known as the social opportunity function.
The study reached to following conclusions:
Foreign direct investment can be used as a financing tool for inclusive growth. A deep underpinning of its impact on inclusive growth variable suggested that the impact of FDI on increasing the overall income is positive and significant. Yet it does not significantly influence the distribution of the opportunities. Hence, FDI does not influence inclusive growth through equity channel but by increasing the average opportunities.
The results of the research show that the Gini Coefficient Index, which is considered as a threshold change above and below the foreign investment attraction threshold, has a different effect on the overall growth index. When Foreign Direct Investment is less than the threshold, with a unit increase in the Gini Coefficient, leads to a worsening of the equitable distribution of income. As a result the index of inclusive growth, is in line with the views of the dependency theory. If Foreign Direct Investment is above the threshold, with one unit increase in the Gini Coefficient, which leads to a worsening of the equitable distribution of income, the index of inclusive growth increases, will be in line with the theory of modernization
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