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Dr Elham Nobahar, Dr Seyed Kamal Sadeghi, Mr Hadi kheirollahi zaki,
Volume 24, Issue 3 (Autumn 2024)
Volume 24, Issue 3 (Autumn 2024)
Abstract
Introduction
Crime is a multifaceted phenomenon that has always attracted the attention of economists, sociologists, lawyers and psychologists. Many experts and economic pioneers consider it necessary to achieve economic development to improve the level of security and reduce crime in the society. Since the occurrence of any phenomenon is affected by various factors, the occurrence of crime as an undesirable phenomenon is not excluded from this rule. Various economic, social and political factors affect crime in society. Identifying these factors can help a lot in the correct understanding and appropriate policy making in order to control and reduce the crime rate in the society. Meanwhile, one of the most important economic factors affecting crime is unemployment. Unemployment is one of the most important macroeconomic variables, which clearly affects many social phenomena, including crime. In this regard, the main goal of the present study is to investigate the relationship between unemployment and crime and to identify factors affecting crime in the Iranian cities. The statistical population of the current research is the cities of Iran and the time range under investigation is 2016.
Methodology
In this study, the spatial causality test was used to investigate the relationship between unemployment and crime. The first step in investigating the spatial causality relationship between the studied variables is to perform the spatial independence test of the variables. In the second step, the existence of spatial dependence between variables is examined. If both the investigated variables have a spatial structure and there is a spatial dependence between the two variables, then the spatial causality test is performed in the third step. In this study, the spatial econometric approach has also been used to estimate the crime model in the cities of Iran. In this regard, the presence of spatial effects in the model has been tested using Moran's I test, and then the most appropriate spatial regression model has been selected and estimated based on the Lagrange coefficient (LM) test and the LR diagnostic tests. The software packages used in this study are Matlab 2023, GeoDa 1.16 and Stata 15.
Findings
The results of the spatial tests show that both crime index and unemployment rate have a spatial structure and the spatial dependence between these two variables was also confirmed, so in the third step, the spatial causality has been tested. The results of spatial causality test indicate the existence of a two-way causality relationship between the crime index and the unemployment rate. In other words, unemployment was the cause of crime during the period under investigation, and unemployment also led to the occurrence and increase of crime. According to the results of the spatial causality test, the crime model of the Iranian cities was developed in terms of the unemployment variable and several control variables. In order to estimate the model, the presence of spatial effects was first investigated using Moran's I test. The results of this test indicate the presence of spatial effects in the model. Also, based on the results of the Lagrange coefficient and likelihood ratio tests, the Spatial Durbin Model (SDM) was chosen as the most appropriate method for estimating the model. The results of the estimation of the crime model indicate that the spatial lag coefficient is positive and significant at a high level, which indicates the existence of spatial dependence in the model. The positiveness of this coefficient shows that an increase in crime in one city causes an increase in crime in neighboring cities. Also, according to the results of the research, the variables of unemployment, industrialization, urbanization and divorce rate are the most important variables affecting crime rate. The results show positive and significant relationships between unemployment, urbanization, divorce rate, and crime. The industrialization variable also has a negative and significant effect on crime. Also, the spillover effect of the unemployment variable is negative and significant. Based on the results, the higher the unemployment rate and the urbanization rate in the cities, the crime rate will also increase in those cities. On the other hand, as cities move toward industrialization and the number of industrial enterprises in them increases, the rate of crime will decrease more.
Discussion and conclusion
The findings reveal that, unemployment is one of the most important variables affecting crime in the Iranian cities. So, it is recommended that authorities pay special attention to sustainable policies regarding employment and its proportional distribution in cities. Considering excessive growth of urbanization and its detrimental impact on rampant crime rates, it is suggested that statesmen and policy makers create more facilities and pay special attention to rural areas to provide reverse migration in order to prevent occurrence of various crimes, which are happenning due to population increase especially in informal settlements of larger cities.
Crime is a multifaceted phenomenon that has always attracted the attention of economists, sociologists, lawyers and psychologists. Many experts and economic pioneers consider it necessary to achieve economic development to improve the level of security and reduce crime in the society. Since the occurrence of any phenomenon is affected by various factors, the occurrence of crime as an undesirable phenomenon is not excluded from this rule. Various economic, social and political factors affect crime in society. Identifying these factors can help a lot in the correct understanding and appropriate policy making in order to control and reduce the crime rate in the society. Meanwhile, one of the most important economic factors affecting crime is unemployment. Unemployment is one of the most important macroeconomic variables, which clearly affects many social phenomena, including crime. In this regard, the main goal of the present study is to investigate the relationship between unemployment and crime and to identify factors affecting crime in the Iranian cities. The statistical population of the current research is the cities of Iran and the time range under investigation is 2016.
Methodology
In this study, the spatial causality test was used to investigate the relationship between unemployment and crime. The first step in investigating the spatial causality relationship between the studied variables is to perform the spatial independence test of the variables. In the second step, the existence of spatial dependence between variables is examined. If both the investigated variables have a spatial structure and there is a spatial dependence between the two variables, then the spatial causality test is performed in the third step. In this study, the spatial econometric approach has also been used to estimate the crime model in the cities of Iran. In this regard, the presence of spatial effects in the model has been tested using Moran's I test, and then the most appropriate spatial regression model has been selected and estimated based on the Lagrange coefficient (LM) test and the LR diagnostic tests. The software packages used in this study are Matlab 2023, GeoDa 1.16 and Stata 15.
Findings
The results of the spatial tests show that both crime index and unemployment rate have a spatial structure and the spatial dependence between these two variables was also confirmed, so in the third step, the spatial causality has been tested. The results of spatial causality test indicate the existence of a two-way causality relationship between the crime index and the unemployment rate. In other words, unemployment was the cause of crime during the period under investigation, and unemployment also led to the occurrence and increase of crime. According to the results of the spatial causality test, the crime model of the Iranian cities was developed in terms of the unemployment variable and several control variables. In order to estimate the model, the presence of spatial effects was first investigated using Moran's I test. The results of this test indicate the presence of spatial effects in the model. Also, based on the results of the Lagrange coefficient and likelihood ratio tests, the Spatial Durbin Model (SDM) was chosen as the most appropriate method for estimating the model. The results of the estimation of the crime model indicate that the spatial lag coefficient is positive and significant at a high level, which indicates the existence of spatial dependence in the model. The positiveness of this coefficient shows that an increase in crime in one city causes an increase in crime in neighboring cities. Also, according to the results of the research, the variables of unemployment, industrialization, urbanization and divorce rate are the most important variables affecting crime rate. The results show positive and significant relationships between unemployment, urbanization, divorce rate, and crime. The industrialization variable also has a negative and significant effect on crime. Also, the spillover effect of the unemployment variable is negative and significant. Based on the results, the higher the unemployment rate and the urbanization rate in the cities, the crime rate will also increase in those cities. On the other hand, as cities move toward industrialization and the number of industrial enterprises in them increases, the rate of crime will decrease more.
Discussion and conclusion
The findings reveal that, unemployment is one of the most important variables affecting crime in the Iranian cities. So, it is recommended that authorities pay special attention to sustainable policies regarding employment and its proportional distribution in cities. Considering excessive growth of urbanization and its detrimental impact on rampant crime rates, it is suggested that statesmen and policy makers create more facilities and pay special attention to rural areas to provide reverse migration in order to prevent occurrence of various crimes, which are happenning due to population increase especially in informal settlements of larger cities.
Mr Hadi kheirollahi zaki, Dr Kamal Sadeghi,
Volume 25, Issue 1 (Spriing 2025)
Volume 25, Issue 1 (Spriing 2025)
Abstract
Aim and Introduction
Globalization in recent decades has brought developed and developing economies closer to each other through trade, technology transfer, capital flows, bonds, and employment opportunities, and the positive impact of globalization has been linked to the availability of economic advantages. Globalization has certain adverse effects that cause the release of pollutants, ecological imbalances, and issues related to global climate change. The effects of greenhouse gas emissions may adversely affect sustainable economic growth through welfare-reducing channels. Other adverse effects of globalization include environmental damage, price fluctuations, over-specialization, elimination of local industries, and social and industrial deterioration. Economists argue that globalization activities improve domestic economic structure by integrating trade, technology transfer, and financial activities. As a result, the growth of global economic activities may lead to more energy consumption and greenhouse gas emissions.
Achieving sustainable environmental development along with preventing environmental degradation has always been a serious issue for policy makers. Globalization and diversification of exports are one of the most important factors affecting this issue.
In this study, the impact of globalization variables and export diversification on the environment of 7 selected countries of the Persian Gulf is investigated. The focus of this study is on the combination of export diversification and globalization index (from the economic, political and social aspects), to investigate the performance of pollutants and as a result determine the EKC hypothesis in the Persian Gulf countries.
Methodology
In order to conduct an empirical analysis of globalization, export diversity and environmental degradation, we use the panel data approach. The standard approach in spatial econometrics is that one should first start the analysis with a non-spatial model and then check whether the benchmark model needs to be developed by considering spatial interaction effects or not. The used sample includes 7 sections and the time period includes the years 1995 to 2020. The decision to select the sample is based on the availability of data from the World Bank. It will be used to estimate non-spatial fixed and random effects models. The fixed effects model controls for heterogeneity by allowing a separate interval for each cross section. While the random effects model shows the unobserved features of the country in the error term.
Findings
Export diversity has a positive and significant effect on carbon dioxide emissions, therefore creating diversification in exports in Persian Gulf countries will increase carbon dioxide emissions. The issue that has caused the high concentration of the export portfolio in these countries is the focus on the export of oil and gas and petrochemical products, which are inherently polluting industries. The findings also show that economic growth has a negative relationship with CO2 emissions. A one percent increase in economic growth reduces CO2 emissions by 1.67 percent based on the results of the Spatial Panel. The square effect of economic growth is also positive and significant, and this shows that the relationship between CO2 emissions and economic growth is U-shaped, such a U-shaped relationship basically shows that economic growth is not critical in reducing CO2 emissions in the countries in question. Considering that exports in the Persian Gulf countries are highly concentrated in the oil and gas and petrochemical sectors, and these sectors cause high pollution, therefore, the policy implications should be based on supporting the more efficient use of renewable energy in the economy of these countries. It should be noted that investment or tax incentives on technologies that consume renewable energy can be significant policy tools.
Discussion and Conclusion
Sustainability of economic development requires environmental sustainability as part of a dynamic process. The results of this study showed that energy consumption and diversification of exports aggravates environmental degradation in Persian Gulf countries. The variety of export products significantly affects CO2 emissions in selected countries. In fact, export diversification can be useful not only for rapid economic growth but also for environmental pollution management. For example, companies should avoid producing goods that cause high CO2 emissions. This issue should be evaluated in expanding the export portfolio and products with high CO2 emissions can be imported. Of course, all these consequences require accurate knowledge of the scale of environmental pollutants in the economy of countries for each sector. Business and political efforts to diversify the portfolio of export products directly affect environmental quality. Countries can clarify information on capital flows related to investment companies to improve environmental regulations. Developing countries need to adopt efficient and effective environmental practices in activities related to foreign investment. To improve environmental quality from the perspective of energy policy, policymakers should focus on clean energy policies. Improving energy efficiency, investing in renewable resources, increasing the use of cleaner energy sources, and reducing energy intensity are the main options for reducing carbon emissions
Globalization in recent decades has brought developed and developing economies closer to each other through trade, technology transfer, capital flows, bonds, and employment opportunities, and the positive impact of globalization has been linked to the availability of economic advantages. Globalization has certain adverse effects that cause the release of pollutants, ecological imbalances, and issues related to global climate change. The effects of greenhouse gas emissions may adversely affect sustainable economic growth through welfare-reducing channels. Other adverse effects of globalization include environmental damage, price fluctuations, over-specialization, elimination of local industries, and social and industrial deterioration. Economists argue that globalization activities improve domestic economic structure by integrating trade, technology transfer, and financial activities. As a result, the growth of global economic activities may lead to more energy consumption and greenhouse gas emissions.
Achieving sustainable environmental development along with preventing environmental degradation has always been a serious issue for policy makers. Globalization and diversification of exports are one of the most important factors affecting this issue.
In this study, the impact of globalization variables and export diversification on the environment of 7 selected countries of the Persian Gulf is investigated. The focus of this study is on the combination of export diversification and globalization index (from the economic, political and social aspects), to investigate the performance of pollutants and as a result determine the EKC hypothesis in the Persian Gulf countries.
Methodology
In order to conduct an empirical analysis of globalization, export diversity and environmental degradation, we use the panel data approach. The standard approach in spatial econometrics is that one should first start the analysis with a non-spatial model and then check whether the benchmark model needs to be developed by considering spatial interaction effects or not. The used sample includes 7 sections and the time period includes the years 1995 to 2020. The decision to select the sample is based on the availability of data from the World Bank. It will be used to estimate non-spatial fixed and random effects models. The fixed effects model controls for heterogeneity by allowing a separate interval for each cross section. While the random effects model shows the unobserved features of the country in the error term.
Findings
Export diversity has a positive and significant effect on carbon dioxide emissions, therefore creating diversification in exports in Persian Gulf countries will increase carbon dioxide emissions. The issue that has caused the high concentration of the export portfolio in these countries is the focus on the export of oil and gas and petrochemical products, which are inherently polluting industries. The findings also show that economic growth has a negative relationship with CO2 emissions. A one percent increase in economic growth reduces CO2 emissions by 1.67 percent based on the results of the Spatial Panel. The square effect of economic growth is also positive and significant, and this shows that the relationship between CO2 emissions and economic growth is U-shaped, such a U-shaped relationship basically shows that economic growth is not critical in reducing CO2 emissions in the countries in question. Considering that exports in the Persian Gulf countries are highly concentrated in the oil and gas and petrochemical sectors, and these sectors cause high pollution, therefore, the policy implications should be based on supporting the more efficient use of renewable energy in the economy of these countries. It should be noted that investment or tax incentives on technologies that consume renewable energy can be significant policy tools.
Discussion and Conclusion
Sustainability of economic development requires environmental sustainability as part of a dynamic process. The results of this study showed that energy consumption and diversification of exports aggravates environmental degradation in Persian Gulf countries. The variety of export products significantly affects CO2 emissions in selected countries. In fact, export diversification can be useful not only for rapid economic growth but also for environmental pollution management. For example, companies should avoid producing goods that cause high CO2 emissions. This issue should be evaluated in expanding the export portfolio and products with high CO2 emissions can be imported. Of course, all these consequences require accurate knowledge of the scale of environmental pollutants in the economy of countries for each sector. Business and political efforts to diversify the portfolio of export products directly affect environmental quality. Countries can clarify information on capital flows related to investment companies to improve environmental regulations. Developing countries need to adopt efficient and effective environmental practices in activities related to foreign investment. To improve environmental quality from the perspective of energy policy, policymakers should focus on clean energy policies. Improving energy efficiency, investing in renewable resources, increasing the use of cleaner energy sources, and reducing energy intensity are the main options for reducing carbon emissions
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