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Dr Naeim Shokri, Dr Abbas Assari Arani, Dr Ali Asgary, Dr Amirhosein Mozayani, Dr Nematollah Akbari,
Volume 22, Issue 3 (9-2022)
Volume 22, Issue 3 (9-2022)
Abstract
Today, the share of government aid from the public expenditures to support military and civil servants' pension funds has increased from about 11% in 2013 to 19% in 2021 and this trend has been increasing in recent years. This study aims to use DSGE models to simulate and apply corrective measures to enhance the financial misalignment of Iran's pension system. For this purpose, the model has been calibrated once for the PAYG-DB system that is currently used in Iran and then for the system based on financial provision based on the amount of partial savings to compare their welfare and distributional effects. The simulation results show that people reduce their savings by switching to a partial savings system, which increases consumption in all generations and capital accumulation in the whole society. In the second part of the article, impulse response functions were used to investigate the effects of emerging diseases and population aging variables on the financial misalignment of pension funds. The results show that the financial misalignment of pension funds increases following the positive shock in the above variables. Based on the results, parametric reforms such as a mechanism linking the retirement age to life expectancy and transition to a partial savings system can reduce financial misalignment and increase financial sustainability in Iran's pension system.
Dr Mohammad Shiri, Dr Parya Torabi Kahlan, Dr Lida Kalhori, Dr Roshanak Aliakbari Saba, Mrs. Tahere Amini,
Volume 23, Issue 1 (3-2023)
Volume 23, Issue 1 (3-2023)
Abstract
Aim and Introduction
The poverty is not affected only by income level. Some variables such as lack of access to welfare and health facilities, deprivation of education, physical weakness and vulnerability to diseases can be influential factors in poverty. Accordingly, indexes such as the poverty line, the percentage of poor people, and the intensity of poverty, which are used to study of the poverty in the society, do not fully represent the situation of poverty dimensions. Therefore, for measuring poverty in different dimensions, Oxford Poverty and Human Development Initiative in collaboration with United Nations Development Programme introduced the Multidimensional Poverty Index in 2010. This index includes deprivations such as low levels of health, lack of education, inadequate living standards, disability, low quality work, threats of violence, and living in areas with hazardous environments that poor people face in their daily lives. Several researches have been conducted on multidimensional poverty at the national and international levels, which have estimated the multidimensional poverty index using the Alkire-Foster methodological framework. At the same time, the multidimensional poverty of children has been neglected at the national level. This paper aims to study of multidimensional poverty among Iranian children based on the Alkire-Foster methodological framework. The multidimensional poverty of under five children using Multiple Indicator Demographic and Health Survey data in four dimensions of "living standards", "health", "support" and "development" has been measured.
Methodology
The Alkire-Foster methodology has been used for measuring the multidimensional poverty index. For measuring the children multidimensional poverty index (MPI) in Iran, data of the Multiple Indicator Demographic and Health Survey has been used. This survey covers the latest available data on various sociodemographic and health subjects of children, women and men. A comprehensive and new framework for measuring child poverty in Iran has been provided using the indicators of child mortality, cooking fuel, drinking water, sanitation discharge and housing from the global framework. The other indicators such as vaccination index and insufficient care has been extracted from other researches.
Findings
The results show that MPI of children in Iran is equal to 0.002. The incidence of multidimensional poverty is 0.5% and the intensity of child poverty is 38.6%. In general, the results show that girls compared to boys experience more multidimensional poverty and as mothers' education levels increase, children experience less multidimensional poverty. Children who live in large households (5 people or more) experience more multidimensional poverty compared to children who live in small households. Children in developed provinces experience multidimensional poverty less than other children and finally, children under five in the first economic quintile (the lowest economic level of the society) have the highest multidimensional poverty among all households in Iran.
Among children under five whose mothers have primary education, "health" dimension plays the most important role in measuring the multidimensional poverty index. In less developed provinces, the most important factor in mesearunig multidimensional poverty among children under five is "child development" dimension. Also, in households that have a low level of economic and social status (based on economic quintile variable), “child development " and "living standards” are important respectively.
Discussion and Conclusion
The purpose of presenting the Child multidimensional poverty index is to provide understandable and important statistics for clarify level and form of multidimensional poverty. The findings of this study, which was conducted for the first time in Iran, show that although value of the child multidimensional poverty index based on "living standards”, "health", "support" and "child development" is not a large number, however children in social and demographic groups have had encounters with different levels of multidimensional poverty. Considering that the growth and development of the children in the appropriate context is the basis for formation of a healthy and stable family and developed society, it is necessary to make policies in order to reduce the multidimensional poverty of children.
Dr. Maryam Khodaverdi Samani, Dr. Gholamreza Nemati, Dr. Alireza Kashefi, Dr. Parvaneh Salatin,
Volume 23, Issue 3 (8-2023)
Volume 23, Issue 3 (8-2023)
Abstract
Aim and Introduction
Today, planners and decision makers of countries need timely and accurate evaluation of their decisions and policies. The issue of time and precision is so important that it provides the possibility of implementing possible changes and modifications of patterns and plans, and prevents wasting resources and opportunities. Fortunately, various indicators have provided such a possibility to evaluate these policies and decisions. Misery index is one of the most important measures of social welfare. This index is obtained from the linear combination of inflation and unemployment. This index was introduced by Aokan (1999) and expanded by Barro (1996). An increase in the misery index is associated with many social and economic costs, such as an increase in crime, poverty, divorce, a decrease in social security, damage to mental health, the collapse of families, a decrease in health expenses, and a decrease in life expectancy. Inflation causes the imposition of welfare costs by reducing the value of people’s financial assets, and on the other hand, it harms production by creating uncertainty in the decisions of institutions for investment and creating other costs. Inflation leads to sub - optimal allocation of resources, economic inefficiency and social, cultural and political disorder of the society. Unemployment like inflation is the cause of chaos in the economic conditions of the society. Unemployment has caused people to suffer from social problems such as crimes, addiction and moral corruption. Unemployment causes people to be caught in social problems such as crime, addiction and moral corruption.
Methodology
Knowledge and awareness of the state of misery index in the regions of the country in certain time horizons are very important for the planners of the region and economic policy makers of the country. Considering the importance of the misery index, this question is raised: Which factors affect the convergence of the misery index in the provinces? In this regard, several studies have been conducted in the field of misery index. However, none of the studies have investigated the influence of the factors affecting the convergence of the misery index in the provinces using spatial econometrics.
In economic literature, there are several methods for investigating the convergence. Absolute beta convergence and conditional beta convergence have been used in this study. Absolute beta convergence is formed independently of initial conditions and other characteristics of an economy.
For this purpose, using theoretical foundations and empirical studies, the variables of economic growth, monetary indiscipline, human capital, and information and communications technology (ICT) were added to the convergence model as explanatory variables. Absolute beta convergence and conditional beta convergence models have been estimated using the spatial econometric method over the period 2006-2020.
In this study, after defining the spatial weight matrix, the unit root test is used to examine the "stationary" of the variables. Moran test and Lagrange multiplier test are used to detect spatial autocorrelation and examine the presence of spatial effects, respectively. Chow's test is used to determine whether the data is a panel, and Hausman's spatial test is used to use the fixed or random effect method. Finally, the model is estimated, and effects of space spillovers are analyzed with "spatial econometrics method" by accounting for direct and indirect effects in Stata software.
The calculations of the overflow coefficients of each province on other provinces and the drawing of maps were done using R software and Maptools, Spdep and IMPact function packages for the year 2019.
The statistical data including inflation and unemployment rates are used to calculate misery index. Gross domestic product, population, number of university graduates (as human capital index) are extracted from statistical yearbook of the provinces and Statistical Center of Iran. The penetration coefficient of the internet (as ICT indicator) is extracted from Ministry of Communications and Information Technology, as well as facilities and deposits after deducting legal trust are gathered from the Central Bank of Iran. The statistical population of this study is the provinces of Iran except for Alborz province.
The results of stationary test using Levin, Lin and Chu (2002) method showed that all variables are stationary at level. Also, the null hypothesis of Moran's test regarding the absence of spatial effects in absolute convergence model and conditional convergence model was rejected. Therefore, the presence of spatial effects in absolute and conditional convergence models was confirmed. According to the conducted tests, the spatial auto-regression method (SAC) was used in this study. The results of the spatial Hausman test also showed that the models should be estimated using the fixed effects method.
Findings
The results of estimating the models showed that economic growth and human capital have a negative and significant effect, ICT and monetary indiscipline of banks have a positive and significant effect on the convergence of the misery index in the provinces. According to the speed of convergence, in the case of annual absolute convergence of about 10.9 % and in the case of conditional convergence of about 12.6 % , the gap between the " current growth rate of the misery index " of the provinces and the " long - term equilibrium misery index " of the provinces will be resolved. In the case of conditional convergence, the time required to eliminate half of the aforementioned gap is about 5.5 years. It should be noted that in this study, the misery index is a negative variable. The interpretation of the beta coefficient means that there is an opposite relationship between the initial situation and the average growth rate of the misery index: That is, regions with a lower "misery index" move towards the average misery index with a higher speed and higher growth rate than other regions. This means that the economic situation of the provinces is getting worse. Therefore, it is expected that the provinces will converge to their long - term equilibrium misery index and the gap between the current growth rate of the province's misery index and its long - term equilibrium will be resolved.
Discussion and Conclusion
According to the positive and significant effect of the monetary indiscipline index on the convergence of the misery index in the provinces, it can be said that with the increase of monetary indiscipline in the banks, liquidity has increased at the community level. Consequently, it has caused an increase in the general level of prices and an increase in the misery index. On the other hand, due to the economic situation of Iran, the existence of economic and banking sanctions and the impossibility of financing and investing in foreign sectors, the government's credit facilities and debt to banks have increased, and the monetary indiscipline index of banks is increasing, and as a result, the liquidity risk of banks is increasing. As a result, the lending power of banks will decrease, that is, it is not possible to grant large bank loans to drive the productive and entrepreneurial sectors into spur the economic growth of the provinces, and this will cause a decrease in employment, a decrease in the level of production, and then an increase in unemployment. This is why the misery index increases in the provinces. The spatial coefficient of the interval of the dependent variable is positive and significant. The existence of a positive and significant coefficient of the spatial dependence variable shows the positive effect of the poverty index of neighboring provinces on each other, so the distance between the provinces of the country has an effect on the convergence of the poverty index.
Today, planners and decision makers of countries need timely and accurate evaluation of their decisions and policies. The issue of time and precision is so important that it provides the possibility of implementing possible changes and modifications of patterns and plans, and prevents wasting resources and opportunities. Fortunately, various indicators have provided such a possibility to evaluate these policies and decisions. Misery index is one of the most important measures of social welfare. This index is obtained from the linear combination of inflation and unemployment. This index was introduced by Aokan (1999) and expanded by Barro (1996). An increase in the misery index is associated with many social and economic costs, such as an increase in crime, poverty, divorce, a decrease in social security, damage to mental health, the collapse of families, a decrease in health expenses, and a decrease in life expectancy. Inflation causes the imposition of welfare costs by reducing the value of people’s financial assets, and on the other hand, it harms production by creating uncertainty in the decisions of institutions for investment and creating other costs. Inflation leads to sub - optimal allocation of resources, economic inefficiency and social, cultural and political disorder of the society. Unemployment like inflation is the cause of chaos in the economic conditions of the society. Unemployment has caused people to suffer from social problems such as crimes, addiction and moral corruption. Unemployment causes people to be caught in social problems such as crime, addiction and moral corruption.
Methodology
Knowledge and awareness of the state of misery index in the regions of the country in certain time horizons are very important for the planners of the region and economic policy makers of the country. Considering the importance of the misery index, this question is raised: Which factors affect the convergence of the misery index in the provinces? In this regard, several studies have been conducted in the field of misery index. However, none of the studies have investigated the influence of the factors affecting the convergence of the misery index in the provinces using spatial econometrics.
In economic literature, there are several methods for investigating the convergence. Absolute beta convergence and conditional beta convergence have been used in this study. Absolute beta convergence is formed independently of initial conditions and other characteristics of an economy.
For this purpose, using theoretical foundations and empirical studies, the variables of economic growth, monetary indiscipline, human capital, and information and communications technology (ICT) were added to the convergence model as explanatory variables. Absolute beta convergence and conditional beta convergence models have been estimated using the spatial econometric method over the period 2006-2020.
In this study, after defining the spatial weight matrix, the unit root test is used to examine the "stationary" of the variables. Moran test and Lagrange multiplier test are used to detect spatial autocorrelation and examine the presence of spatial effects, respectively. Chow's test is used to determine whether the data is a panel, and Hausman's spatial test is used to use the fixed or random effect method. Finally, the model is estimated, and effects of space spillovers are analyzed with "spatial econometrics method" by accounting for direct and indirect effects in Stata software.
The calculations of the overflow coefficients of each province on other provinces and the drawing of maps were done using R software and Maptools, Spdep and IMPact function packages for the year 2019.
The statistical data including inflation and unemployment rates are used to calculate misery index. Gross domestic product, population, number of university graduates (as human capital index) are extracted from statistical yearbook of the provinces and Statistical Center of Iran. The penetration coefficient of the internet (as ICT indicator) is extracted from Ministry of Communications and Information Technology, as well as facilities and deposits after deducting legal trust are gathered from the Central Bank of Iran. The statistical population of this study is the provinces of Iran except for Alborz province.
The results of stationary test using Levin, Lin and Chu (2002) method showed that all variables are stationary at level. Also, the null hypothesis of Moran's test regarding the absence of spatial effects in absolute convergence model and conditional convergence model was rejected. Therefore, the presence of spatial effects in absolute and conditional convergence models was confirmed. According to the conducted tests, the spatial auto-regression method (SAC) was used in this study. The results of the spatial Hausman test also showed that the models should be estimated using the fixed effects method.
Findings
The results of estimating the models showed that economic growth and human capital have a negative and significant effect, ICT and monetary indiscipline of banks have a positive and significant effect on the convergence of the misery index in the provinces. According to the speed of convergence, in the case of annual absolute convergence of about 10.9 % and in the case of conditional convergence of about 12.6 % , the gap between the " current growth rate of the misery index " of the provinces and the " long - term equilibrium misery index " of the provinces will be resolved. In the case of conditional convergence, the time required to eliminate half of the aforementioned gap is about 5.5 years. It should be noted that in this study, the misery index is a negative variable. The interpretation of the beta coefficient means that there is an opposite relationship between the initial situation and the average growth rate of the misery index: That is, regions with a lower "misery index" move towards the average misery index with a higher speed and higher growth rate than other regions. This means that the economic situation of the provinces is getting worse. Therefore, it is expected that the provinces will converge to their long - term equilibrium misery index and the gap between the current growth rate of the province's misery index and its long - term equilibrium will be resolved.
Discussion and Conclusion
According to the positive and significant effect of the monetary indiscipline index on the convergence of the misery index in the provinces, it can be said that with the increase of monetary indiscipline in the banks, liquidity has increased at the community level. Consequently, it has caused an increase in the general level of prices and an increase in the misery index. On the other hand, due to the economic situation of Iran, the existence of economic and banking sanctions and the impossibility of financing and investing in foreign sectors, the government's credit facilities and debt to banks have increased, and the monetary indiscipline index of banks is increasing, and as a result, the liquidity risk of banks is increasing. As a result, the lending power of banks will decrease, that is, it is not possible to grant large bank loans to drive the productive and entrepreneurial sectors into spur the economic growth of the provinces, and this will cause a decrease in employment, a decrease in the level of production, and then an increase in unemployment. This is why the misery index increases in the provinces. The spatial coefficient of the interval of the dependent variable is positive and significant. The existence of a positive and significant coefficient of the spatial dependence variable shows the positive effect of the poverty index of neighboring provinces on each other, so the distance between the provinces of the country has an effect on the convergence of the poverty index.
Estimation of Vulnerability Index of Modern Slavery in Urban and Rural Areas of Iran by Fuzzy Method
Mr. Faramarz Khalighi, Dr. Hossein Sadeghi Seghdel, Dr. Bahram Sahabi, Dr. Sajjad Faraji Dizaji,
Volume 23, Issue 3 (8-2023)
Volume 23, Issue 3 (8-2023)
Abstract
The findings of the studies by the International Labor Organization and the International Organization for Migration (2022) show that all over the world, more than forty million people are victims of modern slavery. On the other hand, studies of the Global Slavery Index (2016) show that there are more than 495,000 "modern slaves" in Iran. The emergence of such a damage is a stimulus to investigate and study this phenomenon and its determinants by calculating the vulnerability indicators for Iran.
Considering that there is no effective quantitative index in the field of improving the condition of slaves in Iran, the general goal of this research is to estimate a fuzzy index that includes the dimensions of vulnerability of slaves between 1996 and 2018.
We investigate the slavery situation in four dimensions: 1) Political and civil support; 2) Economic, social and health rights; 3) personal security and 4) Refugees and Conflict. The findings of this research show that the above-mentioned index has a downward trend during period under study.
Introduction
Slavery is any type of system in which the principles of property rights apply to humans and allow people (slaves) to be bought, sold, or owned by others like property. Over the years, this concept has been objectified in various situations such as labor, military, pre-service, etc. The life of a slave, with all its difficulties and hardships, is not the end of his personal life, in the sense of losing all the opportunities of a normal life; because it is possible for a slave to free himself. A slave soldier can be promoted to a senior military rank, or even a slave can become an important person in society. However, in the 15th century, the "Atlantic slave trade" destroyed this possibility. In such a way that over 400 years, 12 million Africans were transported as slaves to European and American colonies and did not have the possibility to return to a normal life. Even if they were freed from slavery, they were still deprived of some rights. Until the end of the 18th century and the beginning of the 19th century, efforts were made to dismantle the system of slavery and the slave trade, and this issue was banned in most countries.
Considering that there is no effective quantitative index in the field of improving the condition of slaves, the general goal of this research is to estimate a multidimensional index that includes the dimensions of vulnerability and the number of slaves. In other words, the main goal of this research is to calculate an index in the field of the status of slaves, separated by gender and province. The existence of this index helps policy makers to organize their actions in the field of slaves' vulnerability.
Methodology
In this section, using an analytical-descriptive method, variables in four groups 1. Political and civil support; 2. Economic, social and health rights; 3. personal security and 4. war and asylum are categorized and, the vulnerability index of slaves will be estimated using the theory of fuzzy sets over the years. To calculate the fuzzy index of each of the aforementioned dimensions of the vulnerability index of slaves, it is necessary to consider variables for each of these dimensions.
The indexing method for the vulnerability of slaves is three-step, so that first, a fuzzy index will be created for each of the above-mentioned dimensions using the fuzzy method. In the second stage, by combining two political and civil indicators, its fuzzy index is made, and for the economic and social dimensions, the corresponding fuzzy index is obtained.
Results and Discussion
Using the aforementioned data, the system was simulated with a fuzzy approach, and the vulnerability index of slaves was obtained by separating urban and rural areas and by gender, as described in the following diagram:
According to the above graph, it is clear that the trend of slavery in the country is decreasing and it has experienced a total decrease of 50%. Having said that, the conditions of the villagers are more difficult than the urban dwellers, and girls have experienced more vulnerability. However, in urban areas, the trend of slaves for boys and girls has been the same.
Conclusion
Paying attention to the vulnerability of modern slavery requires the creation of appropriate platforms and contexts in economic, social and cultural dimensions in the regions of the country, and increasing the role and function of people in different economic-social types also creates platforms for development. Therefore, it is necessary to review the definitions related to development programs from the perspective of anti-slavery and to formulate and apply different levels of programs according to the characteristics and conditions of boys and girls in urban and rural areas. Therefore, according to the results of this research, it is suggested that the key policy priorities to reduce or eliminate forced labor and forced marriage should be changed and formulated in such a way that the rights and freedom of workers to determine wages and choose workplaces are recognized, and policies should be fair and anti-discriminatory in hiring workers
Mrs Sedigheh Hossaini, Dr Saman Ghaderi, Dr Zana Mozaffari, Mr Ramin Amani,
Volume 24, Issue 2 (5-2024)
Volume 24, Issue 2 (5-2024)
Abstract
Introduction
The Covid-19 pandemic, as one of the recent world crises, has brought costs to the economies, which has drawn the attention of researchers and politicians to the concept of economic vulnerability in the form of a warning index to evaluate this external shock. The main aim of this study is to investigate the impact of the COVID-19 pandemic on economic vulnerability in high, medium, and low-income levels countries. This study was conducted for 150 countries using the Panel Smooth Transition Regression (PSTR) approach over 2020-2021. In this regard, the Briguglio method was used to calculate the Economic Vulnerability Index. The results of this research indicate that the COVID-19 pandemic has had a positive and significant effect on the economic vulnerability of countries. The linear test results confirm the non-linear relationship between the variables. Moreover, by considering a transfer function with a threshold parameter (the level of COVID-19 morbidity and mortality), a two-regime model is presented to specify the non-linear relationship between the pattern variables for three groups of high, medium, and low-income countries. The slope parameter (transfer rate) for these three groups of countries is 5.9876, 6.1569, and 3.9987, respectively. The model estimation results show that in both linear and non-linear regimes, COVID-19 has a positive impact on the economic vulnerability of countries with high, medium, and low incomes, meaning that an increase in the COVID-19 pandemic has led to a decrease in the economic vulnerability of these groups of countries.
Methodology
Through extensive research and data collection, a sample of 150 countries for the period 2020-2021 has been selected. The primary criterion for selecting countries and the period is the availability of data. The research database includes sources such as the World Bank, the International Monetary Fund, and the United Nations Development Organization. The dependent variables in this study are the Vulnerability Index. The Vulnerability Index is constructed based on the Briguglio method using four components: 1) Trade openness 2) Export concentration 3) Dependency on strategic imports, and 4) Exposure to natural disasters. Other variables included in the model are the number of COVID-19 deaths, per capita gross domestic product (GDP), foreign direct investment, and remittances as a percentage of GDP, which have been collected from the World Bank and other reliable sources. This study used Panel Smooth Transition Regression (PSTR) approach. PSTR is a statistical model that is commonly used to analyze the non-linear relationships between economic variables. This model is particularly useful for investigating the behavior of variables that exhibit non-linear patterns or changes in their behavior over time. PSTR is a flexible model that can be used to capture the complex relationships between different variables, making it a popular choice in various fields, such as economics, finance, and social sciences. The PSTR model is an extension of the Smooth Transition Regression (STR) model, which is a non-linear regression model that allows for the specification of the transition function between two different regimes. In the PSTR model, the transition function is extended to include panel data, which allows for the analysis of the non-linear relationships between variables across multiple units, such as countries or firms, over time. PSTR is a powerful tool for analyzing the impact of various economic factors on different regions or countries. For example, it can be used to investigate whether the impact of a particular economic policy or event is uniform across different countries or regions, or whether it varies depending on the level of economic development or other relevant factors. Additionally, PSTR can be applied to different types of data, including cross-sectional, time series, and panel data, making it a versatile tool for analyzing a wide range of economic phenomena.
Results and Discussion
the vulnerability model indicates that the slope parameter, which represents the speed of transition from one regime to another, is equal to 1191.414, and the regime change location is 435.6, with the logarithm of its anti-value being 2213094. Therefore, as long as the COVID-19 pandemic (mortality) value is less than the anti-logarithm values, the variables will behave according to the first regime. If the value of the COVID-19 pandemic exceeds the anti-logarithm values, the variables will follow the second regime. Based on the results of the two regimes, it is evident that the COVID-19 pandemic variable has had a positive and significant impact, both linear and nonlinear on countries. This means that the increase in the COVID-19 pandemic has led to an increase in the economic vulnerability of countries. In other studies, such as Brzyska & Szamrej (2021), Marti (2021), and Puertas, it has been demonstrated that the COVID-19 pandemic has had a positive and significant effect on the vulnerability of countries in the European Union, which mostly includes high-income countries.
Conclusion
This paper examines the impact of the COVID-19 pandemic on economic vulnerability in 150 countries during 2020-2021. The results obtained from the Panel Smooth Transition Regression (PSTR) model confirm a nonlinear relationship between the variables and the presence of two threshold regimes with a threshold for economic vulnerability and model. It also indicates that the COVID-19 pandemic has a positive effect on vulnerability. This means that an increase in the COVID-19 pandemic has led to an increase in vulnerability and a decrease in economic resilience in these countries.
The Covid-19 pandemic, as one of the recent world crises, has brought costs to the economies, which has drawn the attention of researchers and politicians to the concept of economic vulnerability in the form of a warning index to evaluate this external shock. The main aim of this study is to investigate the impact of the COVID-19 pandemic on economic vulnerability in high, medium, and low-income levels countries. This study was conducted for 150 countries using the Panel Smooth Transition Regression (PSTR) approach over 2020-2021. In this regard, the Briguglio method was used to calculate the Economic Vulnerability Index. The results of this research indicate that the COVID-19 pandemic has had a positive and significant effect on the economic vulnerability of countries. The linear test results confirm the non-linear relationship between the variables. Moreover, by considering a transfer function with a threshold parameter (the level of COVID-19 morbidity and mortality), a two-regime model is presented to specify the non-linear relationship between the pattern variables for three groups of high, medium, and low-income countries. The slope parameter (transfer rate) for these three groups of countries is 5.9876, 6.1569, and 3.9987, respectively. The model estimation results show that in both linear and non-linear regimes, COVID-19 has a positive impact on the economic vulnerability of countries with high, medium, and low incomes, meaning that an increase in the COVID-19 pandemic has led to a decrease in the economic vulnerability of these groups of countries.
Methodology
Through extensive research and data collection, a sample of 150 countries for the period 2020-2021 has been selected. The primary criterion for selecting countries and the period is the availability of data. The research database includes sources such as the World Bank, the International Monetary Fund, and the United Nations Development Organization. The dependent variables in this study are the Vulnerability Index. The Vulnerability Index is constructed based on the Briguglio method using four components: 1) Trade openness 2) Export concentration 3) Dependency on strategic imports, and 4) Exposure to natural disasters. Other variables included in the model are the number of COVID-19 deaths, per capita gross domestic product (GDP), foreign direct investment, and remittances as a percentage of GDP, which have been collected from the World Bank and other reliable sources. This study used Panel Smooth Transition Regression (PSTR) approach. PSTR is a statistical model that is commonly used to analyze the non-linear relationships between economic variables. This model is particularly useful for investigating the behavior of variables that exhibit non-linear patterns or changes in their behavior over time. PSTR is a flexible model that can be used to capture the complex relationships between different variables, making it a popular choice in various fields, such as economics, finance, and social sciences. The PSTR model is an extension of the Smooth Transition Regression (STR) model, which is a non-linear regression model that allows for the specification of the transition function between two different regimes. In the PSTR model, the transition function is extended to include panel data, which allows for the analysis of the non-linear relationships between variables across multiple units, such as countries or firms, over time. PSTR is a powerful tool for analyzing the impact of various economic factors on different regions or countries. For example, it can be used to investigate whether the impact of a particular economic policy or event is uniform across different countries or regions, or whether it varies depending on the level of economic development or other relevant factors. Additionally, PSTR can be applied to different types of data, including cross-sectional, time series, and panel data, making it a versatile tool for analyzing a wide range of economic phenomena.
Results and Discussion
the vulnerability model indicates that the slope parameter, which represents the speed of transition from one regime to another, is equal to 1191.414, and the regime change location is 435.6, with the logarithm of its anti-value being 2213094. Therefore, as long as the COVID-19 pandemic (mortality) value is less than the anti-logarithm values, the variables will behave according to the first regime. If the value of the COVID-19 pandemic exceeds the anti-logarithm values, the variables will follow the second regime. Based on the results of the two regimes, it is evident that the COVID-19 pandemic variable has had a positive and significant impact, both linear and nonlinear on countries. This means that the increase in the COVID-19 pandemic has led to an increase in the economic vulnerability of countries. In other studies, such as Brzyska & Szamrej (2021), Marti (2021), and Puertas, it has been demonstrated that the COVID-19 pandemic has had a positive and significant effect on the vulnerability of countries in the European Union, which mostly includes high-income countries.
Conclusion
This paper examines the impact of the COVID-19 pandemic on economic vulnerability in 150 countries during 2020-2021. The results obtained from the Panel Smooth Transition Regression (PSTR) model confirm a nonlinear relationship between the variables and the presence of two threshold regimes with a threshold for economic vulnerability and model. It also indicates that the COVID-19 pandemic has a positive effect on vulnerability. This means that an increase in the COVID-19 pandemic has led to an increase in vulnerability and a decrease in economic resilience in these countries.
Mr Hamidreza Naeb Khosroshahi, Dr Mohammadreza Nahidi Amirkhiz, Dr Mohammadali Motafakker Azad, Dr Seyyed Ali Paytakhti Oskooe,
Volume 24, Issue 3 (9-2024)
Volume 24, Issue 3 (9-2024)
Abstract
Introduction
Economic development is one of the main goals of all countries, and most scientists believe that development is only accessible if there is equality. For this reason, despite the differences and contradictions in schools and societies, the issue of inequality and especially economic inequality has been always a vital concern of economists and policymakers all over the world. Meanwhile, since justice is one of the fundamental goals of Islam, Islamic economists have a more scrutinizing and much clear vision of equality. Apart from the importance of economic equality in Islam, it has a cucial role in social security systems and equality concepts as well. Takaful insurance, is a widely used Islamic model in insurance risk coverage which has fundamental differences with conventional insurance mechanisms. Takaful is cooperative, not profit oriented, and fully allined and complied with Islamic rules and regulations. This study is aiming at investigating the effect of various layers of social security system on Islamic-economic equality in the Iranian provinces during 2008-2021. GMM prediction model is applied for predicting the effect of Takaful on inequality and directing houshold religious expenses towards Takaful insurance.
Methodology
According to previous theoretical and experimental literature, economic inequality can be affected by inequality in previous years. Therefore, in this study a dynamic econometric method is used to include the lagged dependant variable as one of the explanatory variables. In general, if a variable depends on vaiables of previous periods, among other independent ones, it is better to use a dynamic panel data model. Generalized method of moments is one of the common and widely used dynamic approaches. The reason for the popularity of this method is that it is very flexible and requires only some weak assumptions. Therefore, Generalized Method of Moments (GMM) greatly solves the problems of static panel data methods related to autocorrelation, variance heterogeneity, and skewness. The reason for using this method is that, firstly, there is a possibility that the current dependent variable is affected by the lagged variables, and secondly, since one of the ways to control the endogeneity of variables is to use instrumental variable and due to the fact that it is very difficult to find such an instrument, it is possible to use lagged variables as appropriate instruments applying GMM estimator.
Findings
The results of this research indicate that the inequality of the previous period has a positive and significant relationship with current economic inequality in all three models. This means that high inequality in the previous period causes high inequality in the current period. Moreover, consistent with some studies, GDP has a positive and significant relationship with economic inequality. It means that an increase in GDP is associated with increased inequality. This result indicates that in Iran, there is no antipoverty growth. Inflation rate has also a negative relationship with inequality in all models, and this relationship is significant in two models. Following some previous studies, this result can be interpreted as the negative relationship can be caused by the fact that the inflation of luxury goods is higher than the inflation of essential goods and therefore, increased inflation is more detrimental to the rich. In addition, all three layers of social assistance, basic social insurance, and supplementary social insurance significantly reduce inequality. Meanwhile, basic social insurance has the greatest effect, and social assistance has the least effect on reducing inequality. In addition, based on the results, it can be stated that by directing houshold religious expenses towards Takaful insurance, which is an Islamic insurance and a type of basic social insurance, it is possible to reduce Islamic-Economic inequality in 2023 and 2024. The amounts of the decreases are predicted to be a minimum of 0.31 and 0.25 (Chahar Mahal and Bakhtiari) and a maximum of 5.95 and 5.91 (Markazi).
Discussion and Conclusion
According to the results, investing in all three layers of social security can lead to a reduction in inequality. Therefore, it is suggested not to ignore any layer in policymaking. Due to the greater impact of basic insurance on equality, it is thought to consider it as the basic layer of social security and focus on this layer to reduce inequality more. Managers and policymakers can also focus on Takaful as one of the basic types of insurance and help to provide Islamic-Economic equality by directing houshold religious expenses towards Takaful. Moreover, it is suggested that the governmental plans should be based on combining economic growth with improved welfare and income distribution which is one of the main goals of the Islamic economy. It is also suggested that the religious and cultural officials should create the necessary explanation and enlightenment related to Takaful and social responsibility of people. The government responsiblity in creating a foundation and guiding people to fulfill their social responsibility by strengthening and developing Zakat headquarters and communicating with social security organization should not be underestimated.
Economic development is one of the main goals of all countries, and most scientists believe that development is only accessible if there is equality. For this reason, despite the differences and contradictions in schools and societies, the issue of inequality and especially economic inequality has been always a vital concern of economists and policymakers all over the world. Meanwhile, since justice is one of the fundamental goals of Islam, Islamic economists have a more scrutinizing and much clear vision of equality. Apart from the importance of economic equality in Islam, it has a cucial role in social security systems and equality concepts as well. Takaful insurance, is a widely used Islamic model in insurance risk coverage which has fundamental differences with conventional insurance mechanisms. Takaful is cooperative, not profit oriented, and fully allined and complied with Islamic rules and regulations. This study is aiming at investigating the effect of various layers of social security system on Islamic-economic equality in the Iranian provinces during 2008-2021. GMM prediction model is applied for predicting the effect of Takaful on inequality and directing houshold religious expenses towards Takaful insurance.
Methodology
According to previous theoretical and experimental literature, economic inequality can be affected by inequality in previous years. Therefore, in this study a dynamic econometric method is used to include the lagged dependant variable as one of the explanatory variables. In general, if a variable depends on vaiables of previous periods, among other independent ones, it is better to use a dynamic panel data model. Generalized method of moments is one of the common and widely used dynamic approaches. The reason for the popularity of this method is that it is very flexible and requires only some weak assumptions. Therefore, Generalized Method of Moments (GMM) greatly solves the problems of static panel data methods related to autocorrelation, variance heterogeneity, and skewness. The reason for using this method is that, firstly, there is a possibility that the current dependent variable is affected by the lagged variables, and secondly, since one of the ways to control the endogeneity of variables is to use instrumental variable and due to the fact that it is very difficult to find such an instrument, it is possible to use lagged variables as appropriate instruments applying GMM estimator.
Findings
The results of this research indicate that the inequality of the previous period has a positive and significant relationship with current economic inequality in all three models. This means that high inequality in the previous period causes high inequality in the current period. Moreover, consistent with some studies, GDP has a positive and significant relationship with economic inequality. It means that an increase in GDP is associated with increased inequality. This result indicates that in Iran, there is no antipoverty growth. Inflation rate has also a negative relationship with inequality in all models, and this relationship is significant in two models. Following some previous studies, this result can be interpreted as the negative relationship can be caused by the fact that the inflation of luxury goods is higher than the inflation of essential goods and therefore, increased inflation is more detrimental to the rich. In addition, all three layers of social assistance, basic social insurance, and supplementary social insurance significantly reduce inequality. Meanwhile, basic social insurance has the greatest effect, and social assistance has the least effect on reducing inequality. In addition, based on the results, it can be stated that by directing houshold religious expenses towards Takaful insurance, which is an Islamic insurance and a type of basic social insurance, it is possible to reduce Islamic-Economic inequality in 2023 and 2024. The amounts of the decreases are predicted to be a minimum of 0.31 and 0.25 (Chahar Mahal and Bakhtiari) and a maximum of 5.95 and 5.91 (Markazi).
Discussion and Conclusion
According to the results, investing in all three layers of social security can lead to a reduction in inequality. Therefore, it is suggested not to ignore any layer in policymaking. Due to the greater impact of basic insurance on equality, it is thought to consider it as the basic layer of social security and focus on this layer to reduce inequality more. Managers and policymakers can also focus on Takaful as one of the basic types of insurance and help to provide Islamic-Economic equality by directing houshold religious expenses towards Takaful. Moreover, it is suggested that the governmental plans should be based on combining economic growth with improved welfare and income distribution which is one of the main goals of the Islamic economy. It is also suggested that the religious and cultural officials should create the necessary explanation and enlightenment related to Takaful and social responsibility of people. The government responsiblity in creating a foundation and guiding people to fulfill their social responsibility by strengthening and developing Zakat headquarters and communicating with social security organization should not be underestimated.
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