spatial econometrics

Today, the issue of employment and unemployment is highly problematic and crisis-prone economically, socially, and politically. The lack of adequate employment in a society can challenge social trust in the government and, consequently, its political legitimacy. Terrorism has a negative impact on the economic performance of countries, but the impact varies from country to country. The negative impact of terrorism is very low in high-income countries, but very high in low-income countries. The reason is that rich countries can use their resources to fight terrorism, but low-income countries are poor and do not have institutions that can respond to the negative impact of terrorism.The Middle East is a region of great ethnic and religious diversity. The high share of energy supply, the concentration of regional and extra-regional powers in recent years accounts for a high share of terrorist attacks in the Middle East, which, in addition to human losses, have large and negative impacts on investment, tourism, and economic growth in the Middle Eastern countries. On the other hand, factors such as political risk, socio-political unrest, high levels of corruption, political instability, political uncertainty, oil price, and lack of transparency have led to an increase in terrorist attacks and the effects of sustained terrorist attacks in these countries.

Spatial econometrics adds spatial effects to the power of periodic or mixed (panel) regression models. Thus, in spatial econometrics, sample information has a spatial component. When the data have a spatial component, two issues can be discussed, including spatial dependence and spatial heterogeneity.In spatial econometric models, it is necessary to choose the numerical value of spatial directions in order to model spatial responses. For this purpose, we have two sources of assumptions. The first is concerned with the position in the coordinate plane, which is expressed by latitude and longitude and such that the distance of each point in the place or the distance of each observation located at each point can be calculated relative to fixed or central points or observations. The second assumption is that the source of spatial information is neighborhood and proximity, which expresses the relative location in space of a seen peripheral unit compared to other such scales. The degree of proximity and contiguity will be available based on the data obtained from the model of the community under study. According to these data, it can be determined which areas are adjacent to each other. In this case, the scales (areas) that have a neighborhood relationship have a higher degree of connectedness than the units that do not have neighbors. The adjacency matrix contains the elements 0 and 1, where the components on the main diameter are equal to zero and the components outside the main diameter are equal to one if two countries are adjacent to each other, and zero otherwise. Therefore, the objective of the current study is to examine the impact of shocks caused by terrorist activities on employment in the selected countries of the Middle East region during the period 2000-2021 using the spatial econometric model.

The results of the research showed that terrorist activities have a negative and significant impact on the level of employment in the affected countries and lead to a decrease in the level of employment and economic activities there in both direct and indirect ways. The result shows that one of the goals of terrorism is to divert the business environment from normal to critical conditions. Based on other research results, the variable of GDP per capita, inflow of foreign direct investment and trade have positive and significant effect on the level of employment in the selected countries of the Middle East, while the variable of inflation rate has negative effect on the employment there.

Conclusions and policy implications:

 According to the results of the research, in order to control the effectiveness of terrorist activities in the selected countries of the Middle East, the institutional quality, political and economic stability, and the structure of democracy should be enhanced. Therefore, if these conditions are accompanied by the instability of internal politics and low institutional quality, it creates a double effect for increasing terrorist activities. Of course, political instability and the existence of corruption and lack of transparency can contribute to the financing of terrorism too. Therefore, it is recommended that the laws and policies of governments in these countries be more stable and transparent in order to counter the creation of terrorist groups. Moreover, since terrorist shocks impose many economic costs on these countries, the cost of securing the region can be considered as an investment in improving the productive environment. Therefore, increasing the budget to deal with terrorist attacks and their complications, as well as funding regional cooperation to deal with terrorism, can bring significant economic benefits to these countries. Another important policy that is recommended is to provide more guarantees in these countries to protect the interests of investors against terrorist attacks. To this end, government guarantees and legal and economic protections for foreign investments to ensure the stability of their operations can reduce investment uncertainty to some extent. In this regard, even the insurance system of the countries can be activated and support foreign investors against terrorist risks. These joint activities can create common interests in unity and cooperation to fight terrorism. Finally, planning to keep economic and investment areas away from terrorist targets and ensuring the security of foreign investment areas and targets can also reduce foreign investment uncertainty to some extent.

Housing is a critical economic sector, with its growth benefiting households. However, rising prices in recent years have diminished household welfare. Using provincial-level data (2011–2021) and a spatial econometric approach, this study analyzed the factors driving housing price increases. The findings revealed that urbanization and economic growth positively influenced housing prices, while financial development had negative spillover effects, underscoring the role of traders in price determination. Although industrialization had no direct effect, its spillover effects were found to be positive, highlighting the service sector’s influence. The study confirmed the housing price divergence and recommended enforcing tax laws on vacant properties and increasing financing in the housing sector to improve Iran’s housing market.

Identification and analysis of energy consumption components can provide opportunities to optimize energy consumption, especially if combined with spatial analysis. The main purpose of the present research is to analyze the spatial panel of the determining factors of energy consumption components (activity, intensity and structure) for 31 provinces of Iran. For this purpose, first, with the factor analysis approach, energy consumption was decomposed by using the latest available data during the period of 2011-2017, and then, using spatial panel data regression, the determining factors of the components of energy consumption in the provinces were investigated. Based on the findings, firstly, Spatial Durbin Model has been selected as the optimal spatial model. Secondly, value added(activity index), industry share(structure index) and urbanization share have direct and significant spillover effects on energy consumption components. The positive effect of industry's share on structural and intensity components can be caused by changing the economic structure towards energy-intensive and low-tech activities. As expected, technical efficiency has a negative and significant effect on the intensity component of energy consumption, and in this regard, spatial effects have strengthened the direct effect. Based on the results, it is recommended to pay attention to the spatial structure of the provinces in energy planning. Secondly, it is recommended to improve the efficiency of economic activities and human capital. Emphasizing the intensity and structural components in order to reduce energy consumption can neutralize the positive effects of variables such as urbanization.

Different provinces of Iran are facing a shortage of investment resources to achieve economic growth and employment development. One of the factors that can provide the necessary opportunities for economic growth and employment creation is government spending in different regions. According to the regional economic perspective, increasing government spending in one region can also affect employment in surrounding regions. Therefore, the aim of this study is to investigate the direct and indirect effects (spillovers) of government spending on employment in different regions of Iran during the period 2010-2021 using a spatial econometric model. The model in question was estimated after conducting the necessary tests with the Spatial Durbin Model (SDM) with fixed effects. The estimation results showed that government spending had a direct and positive effect on employment in different regions of the country. Also, the spillover effects of government spending have been positive and significant. Foreign direct investment also has a positive and direct effect on employment in the country's provinces. Also, its indirect (spillover) effects on employment in the country's provinces (adjacent regions) are positive and significant. The direct and spillover effects of GDP in different regions have also been positive and significant on employment. According to the results, it is recommended that the government increase its spending, especially its investment spending in regions with low employment, and provide the infrastructure needed to increase employment.

Interest rate is one of the most important effective tools in policymaking. It affects investments, stability, economic growth and the real sector of the economy. The main purpose of this study is to investigate the effect of real interest rates on convergence of banks' efficiency in provinces. The results using spatial econometrics during the period 1400-2011 showed that the real interest rate has a positive and significant effect on the efficiency of banks in the provinces. The absolute convergence rate was 0.211 and in conditional models was 0.222 and 0.228, which shows that in conditional condition, the convergence rate of provinces was higher. With the introduction of real interest rates, the pace of convergence has also increased. In other words, 11.2% in absolute convergence mode and 22.2% and 28.2% in conditional convergence mode are resolved from the economic gap of provinces to stable state. Also, economic growth has a positive and significant effect and human capital and ICT have a negative and significant effect on the convergence of banks' efficiency in the provinces.

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.

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.

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.

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.

Fiscal decentralization can improve the efficiency of public service delivery through preference matching and allocative efficiency. Local governments possess better access to local preferences and, consequently, have an informational advantage over the central government in deciding which provision of goods and services would best satisfy citizens’ needs The implementation of financial decentralization, with the aim of improving management processes and transferring resource management and spending, from the central government to local governments is one of the factors improving the efficiency of public services, including health services. so, the aim of the present study is to investigate the effect of financial decentralization indicators on the efficiency of providing health services in Iran's provinces by spatial econometric method in 2006-2016.

The methodology is based on a two-step approach, estimating efficiency coefficients and analyzing the impact of fiscal decentralization on the latter. In a first step, the efficiency of public service delivery is estimated using stochastic frontier techniques. In a second step, this paper estimates the effects of fiscal decentralization on the estimated efficiencies.

The results show that there is a nonlinear relationship between decentralization and efficiency, and therefore the optimal value for decentralization can be achieved. Provinces below the optimal value can improve the efficiency of their health services by increasing decentralization. In fact, the initial levels of financial decentralization have a positive effect on efficiency, but after passing the maximum point, the increase in financial decentralization leads to a decrease in the efficiency of public health services.

The goal of financial decentralization is to increase the efficiency of health services. But its effective implementation requires the identification of provincial capacities; Therefore, it is recommended that the optimal limit be determined and identified before attempting to decentralize financially.Thus, by determining an optimal level of decentralization for each province, financial decentralization based on certain goals and based on the capabilities and capacities of the provinces will be operational and similar and equal treatment in this field will be avoided.Financial decentralization emphasizes the proper transfer of taxes and expenditures to different levels of government to improve the production of public goods and services. nonlinear relationship between financial decentralization and the efficiency of health care services indicates the optimal level of financial decentralization. Financial decentralization, if more than the optimal amount, will worsen the efficiency of service delivery due to the cost of decentralization through factors such as increasing corruption, increasing regional inequalities and lack of necessary infrastructure, lack of favorable political and economic environment. Findings under expenditure decentralization and under revenue decentralization point to the need for a favorable institutional and political environment. Effective autonomy of local governments is required to allow preference matching and the allocative efficiency hypothesis to operate. Strong accountability of local authorities vis-à-vis the local population is necessary to allow the productive efficiency hypthesis to operate. Corruption needs to be tackled to prevent misuse of public resources. And capacity needs to be strengthened at the local level. Absent those conditions, fiscal decentralization can worsen public service delivery.

Extended Abstract: 
Urbanization in Iran has undergone rapid and dramatic changes, and different forms of settlement and social life have always existed in urban, rural, and nomadic areas. transformations in rural, nomadic, and urban communities, and their social foundations and forces play a crucial role in shaping the urban form, urbanization, and its relationship with urbanism. Ideologies and economic and political processes throughout history have directly influenced the social-spatial structures of society, including urban settlements. In fact, cities are human spaces that effectively reflect the impacts of policymakers' decisions on spatial structures and urban classes. Therefore, they provide valuable locations for studying the historical evolution of a society. Based on this premise, the political economy of the city aims to examine the relationship between these historical transformations and their secondary processes and structures within urban space.
Studying the population dynamics and characteristics of urbanization in a historical context in any country can provide a scientific analytical foundation for understanding its economic, social, and political transformations. It can also serve as a useful guide to determine the country's position in the global economic system and the changes that have occurred in this role over time. Thus, given the importance and necessity of this subject, this study attempts to answer the following question:The main issue and question addressed in this research, which encompasses its nature, is the study of the impact of political economy on the urbanization trends in Iran in the time period from 1921 to 1978. The research question can be formulated as follows: How has the political economy influenced the mechanisms of urbanization in Iran? The study aims to provide answers to the ambiguities surrounding this research question.
 
MethodologyThe present study is applied in terms of its objective and descriptive-analytical in terms of data collection. It focuses on examining the impact of political economy on urbanization trends from 1921 to 1978. Data gathering was conducted through two documentary (library) research. After reviewing the theoretical foundations and research literature, a series of indicators and criteria were extracted. A quantitative approach was used to analyze the comprehensive data covering all of Iran in the time period from 1921 to 1978, considering the statistics and figures related to the number of cities. The analysis of research variables was performed using the statistical method of "J-statistic" and analyzed using the SPSS software. The J-statistic is calculated by multiplying the number of observations by a chi-square distribution with degrees of freedom equal to the difference between the number of instrumental variables and the number of estimated coefficients.
 
According to the results of the null hypothesis test of Moran's test, the presence of spatial effects in the model of urban population growth in the country's provinces is confirmed at a high level of significance. Additionally, based on the Lagrange coefficient (LM) test statistics between the two models, namely the spatial lag and spatial error models, the spatial error model is selected as the most appropriate model. According to the results, at a significance level of 5%, the spatial lag model is rejected in comparison to both the spatial error and fixed effects models. Considering that the Lagrange coefficient test results also indicate the superiority of the spatial error model over the spatial lag model, the spatial error model will be used in estimating the model of population growth in the country's cities. Furthermore, the results indicate a statistically significant coefficient of spatial autocorrelation (λ) at a high level, affirming the existence of spatial dependence in the disturbance components of the population growth model and the number of cities in the country.
The coefficient of spatial autocorrelation indicates to what extent the urban population growth in one province is influenced by shocks occurring in the population growth of other provinces in the country.Among the economic variables, poverty index, unemployment rate, and specialization index have been identified as the most influential economic factors on urban population growth in the country's provinces. The poverty index, as a control variable, has a negative effect on urban population growth and is statistically significant at a higher level. This means that cities with higher poverty rates have lower population growth. This suggests that poverty and deprivation are among the key drivers of migration flows.
In other words, provinces with higher unemployment rates (lower employment rates) have experienced higher migration rates to developed urban areas and consequently have had lower population growth. This result supports Michael Todaro's theory, which states that individuals are generally motivated to migrate in search of employment or better job opportunities. According to Todaro's theory, job search is one of the main reasons for migration. On the other hand, cities (or provinces) that have higher levels of development in infrastructure have shown less inclination for migration because individuals usually migrate in search of employment or better job opportunities.Therefore, provinces (cities) with a higher share of injected budget and infrastructure and public services have lower migration rates and have experienced higher population growth rates.
 
Among the economic indicators, variables such as poverty, unemployment rate, and specialization were identified as the most influential factors on urban population growth. In terms of social indicators, the migration rate, general fertility rate, and active population were considered significant factors. However, according to the results, the infrastructure index (road network) included in the model did not have a significant effect. Additionally, the poverty index had a negative impact on urban population growth, which was statistically significant at a higher level. However, the Gini coefficient as a measure of inequality did not have a significant effect on urban population growth. It should be noted that the presence of spatial dependence in the model of urban population growth was confirmed in this study, but the causes of spatial dependence and the variables contributing to it were not discussed or examined.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.

Today, the issue of protecting the environment and preventing its destruction is considered as one of the most important issues of global society. In neoclassical economics, capital and labor were considered as the engine of economic growth, but in recent decades, energy has become one of the main elements of economic growth. In a way, the economic growth of any country depends on the growth of its energy input (Zheng and Walsh, 2019). Along with energy use, greenhouse gas emission is also a term that is often used and the two are interconnected (Achampeng, 2018; Bacon et al., 2019; Gross and Aydin, 2019 and Reza et al., 2019). According to a report from the International Energy Agency, about 67% of the total carbon dioxide emissions are caused by the energy sector, and it shows that reducing air pollution can be achieved by controlling energy consumption. In an effort to respond to the dangers of climate change, studies suggest ways to reduce greenhouse gas emissions, including; a) use of renewable energies; and b) the efficiency of using energy resources (Chang et al., 2018). Studies such as Alvarez-Hranz et al. (2017); Yuan et al. (2018); Lin and Zhou (2019) and Chen et al. (2019) proposed the use of renewable energy technology to reduce greenhouse gas emissions from energy consumption. However, the best and most cost-effective way to reduce air pollution and climate change caused by energy consumption is the optimal use of energy (Lopez-Pena et al., 2012). Triani et al. (2016) claim that strengthening energy efficiency in the industrial sector is the best tool in terms of cost efficiency to reduce greenhouse gas emissions from energy sources. Therefore, energy efficiency is considered as one of the main strategies for reducing greenhouse gas emissions.Considering the importance of environmental quality and the role of energy efficiency in its realization, in this article we try to examine the impact of good governance indicators on energy efficiency and its spatial effects. Therefore, in the field of energy efficiency, one of the goals of this research is to empirically examine the issue of whether the institutional arrangements of neighboring countries affect the institutional quality of the country itself and, as a result, whether energy efficiency is affected in this way. Therefore, we seek to answer these questions, is there a spatial spillover effect of institutional quality? If such spatial spillover exists, how much can it explain a country's level of energy efficiency? Also, the lack of agreement between the experimental studies in the obtained results and the reporting of different results in them is another factor of investigating the issue in the present research. Spatial studies use spatial econometrics instead of common econometrics. Researchers in business, commercial and demographic studies that deal with spatial data and observations and can replace common econometrics with spatial econometrics. The most important differences between spatial econometrics and conventional econometrics are issues such as spatial autocorrelation and spatial heterogeneity, while the aforementioned issues are not discussed in conventional econometrics and it is ignored that not considering this issue causes a violation of the Gauss-Markov assumptions in this research with a random border approach and patterns Spatial econometrics examines the spatial impact of institutional quality on energy efficiency for a country group consisting of 89 countries and for the period 2002-2020. First, in order to avoid false regression, unit root tests are performed and their results are reported accordingly. The reported results indicate that the variables of logarithm of energy efficiency, logarithm of gross domestic product, logarithm of added value of industry sector, logarithm of added value of service sector, logarithm of urbanization population and logarithm of governance quality index are all at the same level. To estimate and analyze the model, the population spatial weight matrix and the gravity model were used, which were standardized using the row standardization method of the elements of this matrix. The considered model in relation (9) was estimated by SAR, SEM, SAC and SDM methods, and the best estimation method is decided by using the relevant tests. Studies have been conducted on the effect of institutional quality and governance on energy efficiency; But the understanding of the relationship and influence of government institutions on energy efficiency is still limited due to few studies, especially in the era of globalization, where countries interact more with each other and their policies and executive actions are affected by each other. Therefore, in this study, with the aim of investigating and analyzing the effects of institutional quality and governance and their spillover effects on energy efficiency, data from 89 countries were used in the period of 2002-2018. In this study, energy efficiency is estimated using the stochastic frontier analysis model and the spillover effects of institutional quality and governance are investigated with spatial panel patterns. In general, the experimental results show that energy efficiency has spatial correlation in the studied countries, and more importantly, the experimental results support the existence of spillover effects of governance quality on energy efficiency. In the current study, the direct effect of governance quality on energy efficiency was positive, although this effect was not statistically significant, but the spillover effects of this variable on energy efficiency had a positive and significant effect. Therefore, the level of energy efficiency of a country can not only be affected by the economic structure of each country, but in addition to the quality of institutions and executive policies of the country itself, it can also depend on the quality of institutions and governance of neighboring countries. This result shows that the country being surrounded by countries with good governance and institutional framework can affect the performance of efficiency and quality.

Innovation in a region or country is influenced by many variables. One of these variables is the uncertainty in the economic and political environment in that region and country. Based on this, the aim of this study is to investigate the effect of global uncertainty (including economic and political uncertainty) on the level of innovation in selected OPEC member countries, including Iran, Saudi Arabia, Kuwait, Qatar, the United Arab Emirates, Algeria, Nigeria, and Ecuador in the period of 2011- 2022. To estimate the relationship between the variables, the econometric model of the Spatial Durbin Model (SDM) has been used to examine the spatial and indirect effects in addition to the direct effects. The results of the model estimation showed that the global uncertainty variable had negative and significant direct and domestic effects on the level of innovation in these countries. Also, the spatial and indirect effects of this variable have been negative and significant on the innovation rate of countries. Two variables, the amount of facilities granted by banks to the private sector and the corruption control index had positive and significant direct effects. The indirect and spatial effects of these two variables are negative and significant.

Investigation of the importance and the impact of various factors on the economic growth of countries is crucial in short-term and long-term planning in various countries. Traditional theories and models of economic development only consider capital and labor as economic growth factors for nations and regions. Today, economists consider innovation, along with knowledge and technology, to be one of the fundamental variables in the economic development and development of countries.Knowledge and innovation can generate social welfare in diverse regions and countries and contribute to achieving sustainable economic growth. In this regard, it is crucial to note that the path of innovation development varies across regions and countries, and that a distinct innovative geography is created based on these differences. The issue of inter-regional or inter-country spillover effects of various variables, such as innovation spillovers, is a second crucial aspect of economic growth and development planning in different regions or countries. Thus, innovation can impact both the economic development of the innovating country and the economic growth of neighboring countries with trade linkages to that country. Examination the spatial dimension of the problem will be crucial for determining how spillovers occur and their effectiveness in the innovation process as well as economic growth and development, whereas excluding inter-regional (inter-country) effects will bias the results and misleading results. On the other hand, considering the inter-regional (inter-country) effects of innovation and other variables in the model can help in the planning of regional development in different countries.

 THEORETICAL FRAMEWORK:

According to new theories, there are four distinct categories of innovation: product innovation, process innovation, organizational innovation, and marketing innovation. There is substantial evidence that various categories of innovation have distinct economic effects in countries. These differences are primarily attributable to variations in the level of pertinent externalities (spillovers) and the capacity of innovators to internalize the public benefits of these activities (fit). Thus, innovative knowledge penetrates the production process in two different ways. The first instance is when a company utilizes new technical knowledge developed during the production process. The second consequence is the spillovers of such knowledge. However, knowledge diffusion in other innovation institutions can only be observed once innovation and technology have reached a certain level.The concept of knowledge spillover is closely associated with the correlation effect, where in the recipient of an innovation assimilates it to facilitate economic advancement. The spillover effect has the potential to yield beneficial outcomes by fostering innovation and facilitating economic progress, but it can also have negative consequences. The adverse impact of knowledge spillover primarily arises from external circumstances, as well as the inherent uncertainties and risks associated with research and development endeavors. Consequently, the inability of spillovers to fully realize the benefits of their research and development endeavors diminishes enterprises' motivation to allocate resources towards innovation. The positive impact of knowledge spillover is directed towards individuals or organizations that possess absorptive potential, enabling them to effectively assimilate and utilize sophisticated information and technology.

The primary objective of the present study is to examine the direct and spillover effects of innovation on economic growth within the D8 group of countries during 2012 -2021. This investigation will be conducted through the utilization of a spatial econometric model. Spatial econometrics is widely regarded as a major development in the field of estimation, having emerged alongside the introduction of the "New Economic Geography (NEG)" theory. This technique is associated with the research conducted by Krugman (1991), Fujita, Krugman, and Venable (2001), as well as Venables and Puga (1998). The econometric models under consideration has the capability to incorporate both spillover and indirect impacts of variables, in addition to the direct effects that are typically addressed in classic econometrics.

Based on the results of the model, the direct effect of innovation index on economic growth has been positive and significant. Also, the indirect effects of this variable have been positive and significant. Therefore, it can be said that the amount of innovation in the studied countries has both domestic and international spillover effects (through the establishment of trade relations) on the economic growth of the countries.

CONCLUSIONS & SUGGESTIONS:

Based on this, it is suggested that the studied countries pay special attention to the issue of innovation. Provide the necessary incentives to strengthen innovation in these countries, such as paying special attention to patents. Because having a patent is one of the motivating factors for innovation and further to achieve new technologies. This can be the basis for creating new processes in production, inventing new methods in countries. Paying attention to the spillover and indirect effects of innovation can also be very important. Based on this, it can be suggested that countries should pay attention to the fact that they prioritize the trade of goods with more knowledge (accumulation of knowledge and its transfer) in order to benefit more from the spillover effects of innovation. The higher the trade and especially the import of goods with knowledge and innovation, the countries can use the knowledge and innovation stored in these goods to strengthen knowledge and innovation within the country and economic growth will be strengthened.

In developing countries, economic growth is the main concern of policy makers and economic thinkers. Knowing the tools and factors affecting economic growth is essential and requires deeper investigations. The importance of knowing the effective factors in the growth and development of countries in today's growing world is undeniable. The degree of effectiveness and recognition of these factors can be an important step towards accelerating growth and development. Accelerating economic growth is a tendency in developing countries. Economists are looking for an answer to the main question, what are the reasons for the difference in the economic growth of the countries of the world? In examining the factors affecting economic growth, two groups of causes can be mentioned. The first group is related to direct factors such as the accumulation of human and physical capital, and the second group includes final factors such as institutions, social capital, etc. In relation to political factors, the situation of developing countries is slightly different from their situation and performance regarding economic factors, especially, the internal economic structure of countries is very vulnerable to adverse factors. Political instability, as the most important internal factor, has the closest interaction with the concept of economic security in influencing the performance of macroeconomic variables, including production. The insecurities that arise in the atmosphere of political instability and violent behavior (such as terrorist activities) in developing countries cause the country's inability to successfully attract foreign capital, capital flight and reduction of capital. Investments are made. Among the indicators of political instability, which has been raised as one of the sensitive issues of the international community, especially developing countries, and its effects on the developments of international economic and political relations, is the phenomenon of terrorism. In this context, Asimoglu (2001), believes that with more efficient and better institutions, more investment will be made in the field of physical and human capital, security, improvement in property rights and less deviations in policies. Among the variables affecting growth and investment, security is a key category. Security is a complex concept and due to the existence of constituent quality indicators and its complexity, both theoretically and empirically, it is a source of controversy. Terrorism is a fundamental factor disrupting economic and social security.

The purpose of this research is to investigate the relationship between terrorism and economic growth in selected countries of the Middle East using the panel spatial econometric method during the period of 1980-2019 using the spatial Durbin model (SDM). Statistics and information required for variables of GDP per capita, foreign trade as a percentage of GDP, bank credits granted to the private sector, foreign direct investment as a percentage of GDP and inflation rate from the World Bank website and For the terrorism variable, it has been extracted from the global database of terrorism, separately for 9 selected countries in the Middle East region.

First, in order to check the spatial dependence of the Moran and Jerry C test, the spatial dependence of the countries was confirmed and based on the significance of the Moran test, the research model was estimated in the spatial panel framework. According to the results of the research, terrorist activities show negative and destructive effects on the economic growth of these countries, and this result is consistent with the results of other studies such as Hamida (2018) and Sanafdiari (2017). According to the results of the research, the variables of foreign direct investment, foreign trade, and bank credits have a significant and positive effect on the economic development of the studied countries, of which foreign investment and foreign trade have the greatest impact on economic growth. Also, the inflation rate has a negative and significant effect on the economic growth of the above countries, and these results are consistent with the results of other studies such as Kavah (2007), Khan (2019), Haider et al. (2015) and Sana and Shafi (2018). Be 

Terrorism and the increase in casualties caused by accidents have had a negative effect on economic growth. Terrorism affects economic growth through different channels. The increase in threats and terrorist incidents leads to insecurity in the country of origin and negatively affects the arrival of tourists. Terrorism also negatively affects investment in tourism-related fields by reducing the sense of security and prevents the strengthening of this sector. The direct effect of these terrorist incidents is to create an atmosphere of insecurity on the economy; Because it destroys and diverts productive economic resources. Scarce productive resources that could have been used to produce goods and services in society are now gone. Also, the resources and budgets allocated for other useful sectors of the economy, as a result of terrorist incidents, should now be used to strengthen the country's security. None of these changes, which are necessary to create security, will not create additional wealth for the society and will not raise the level of well-being, and will also negatively affect economic growth. On the other hand, foreign direct investment is one of the main drivers of economic development and its flow has strong effects on the country's economy. Terrorist activities reduce security and reduce investors' trust in countries exposed to terrorist activities, which leads to a decrease in the flow of foreign direct investment.

Employment is one of the most important issues of economic and social planning . One of the factors affecting employment is research and development. Therefore, the aim of this study is to investigate the effect of R&D on employment in the industrial sector in the provinces during 2006 - 2019 using the spatial econometric model. The results showed that the industrial value added had the greatest direct and indirect effect on the employment of the industrial sector. The spatial effect of this variable was negative and significant. The direct effect of industrial investment on industrial employment is positive but insignificant. The indirect effect of the industrial investment on the industrial employment of the neighboring provinces is negative, but it has not had a significant effect on the employment of the neighboring provinces. The direct effect of industrial R&D on the employment is positive and significant. Also, its spatial impact or spillover on the employment of neighboring provinces has been calculated to be positive and significant. Therefore, the increase of industrial research and development in one province leads to the increase of employment in neighboring provinces. Considering the importance of employment in the industry, this matter should be taken into consideration.

Tax revenues are considered one of the best and most reliable sources of income for governments, and are one of the most fundamental tools for the economic development of any country. The stability and continuity of tax collection leads to stability in the government's planning to provide the services needed by the country in various fields. Hence, in order to plan as well as possible to increase tax revenues, it is necessary to know about the tax efforts of the provinces of the country. Tax effort indicates the extent or limits in which the government has been able to discover existing tax bases and utilize its tax capacity. Therefore, the main purpose of this study is to calculate the tax effort of Iran's provinces. In this regard, first the tax ratio model of Iran's provinces has been estimated using spatial econometric methods. After estimating the model, the tax capacity of the country's provinces was calculated and used to compute the tax effort of each province. The results of this study show that during the study period, the tax effort index of all provinces of Iran except Tehran province is less than 0.84, indicating very low tax effort of the country's provinces. Tehran province's tax effort index was also between 0.85 and 1.24. Therefore, it can be said that all provinces of the country except Tehran province have low tax performance and there are many unused tax capacities in these provinces.

The process of urban growth and development in the past decades has been strongly influenced by the approach of political economy. In Iran, urban development has been formed as an exogenous phenomenon based on the growth of services, which is by no means a continuation of its historical urbanization (before 1920) but a dynamic imposed from outside and the product of unequal economic and social relations with industrialized countries alongside of future's decisions as a catalyst. It is tomorrow. In the present research, which has been done using an analytical method and a quantitative approach, the effect of sanctions on the housing sector between 2006 and 2017 has been investigated. To explain the research model, five categories of political, economic, institutional, social and physical factors were considered. Moreover, using spatial econometric models with three types of cross-sectional data, time series and integrated data were studied. Due to the lack of access and lack of sufficient information in the statistical period, regarding the studied indicators, in first step, the cities of provincial capitals and then the cities of the 2nd and 3rd degree districts were evaluated. Furthermore, based on cities data, the housing price growth model was analyzed using the spatial error model. Due to the variance heterogeneity in this model, KP-HET estimator is used. The results of survey indicate that existence of spatial effects of sanctions on housing price growth in the cities of Iran during the study period. As among the economic variables; Poverty index, unemployment rate and specialization, and among the social variables, migration rate, general fertility rate and active population were considered as the most important factors affecting housing price growth. These variables have been both a cause and a consequence of the disorganization of a coherent pattern of price growth in later periods.

The Middle East is one of the regions with a wide range of ethnic and religious diversity. The high share of energy supply has also led to the concentration of regional and supra-regional powers in the region. In recent years, a large share of terrorist attacks has taken place in the Middle East, which in addition to human losses, has had a major negative impact on investment, tourism and economic growth in the Middle East. Therefore, identifying the effect of terrorist activities on attracting foreign direct investment of these countries in the economic and security policies of these countries is important and necessary. Foreign investors are often reluctant to be aware of all the risks involved. The risks posed by terrorist incidents are no exception to this principle, especially when the target of terrorist attacks is to intimidate a foreign investor. The risks of terrorism increase the cost of starting a business by spending a lot of money on security and insurance of economic activity, the cost of preventive measures, and the high wages of employees who are at risk. These costs reduce the expected performance of investment activity, and as terrorist risks rise above a certain level, the foreign investor will move its capital to a safer area. Political factors are slightly different from their conditions and function in terms of economic factors. The economic base of countries, especially developing countries, is very vulnerable in the face of unacceptable domestic factors. Political instability, as the main internal factor, has the closest reaction to the content of economic security in terms of effectiveness on factors of production. In developing countries, uncertainties that arise in the face of political instability and the perpetration of violent norms (such as terrorist attacks) lead to declining investment, the country's inability to successfully attract foreign investment, and capital flight. د گردد. The manifestation of terrorism is one of the indicators of political instability that is considered as one of the serious problems of the international community, especially in developing countries, and its consequences are broad on the development of global economic and political ties.

The purpose of this study is to investigate the relationship between terrorism and the inflow of foreign direct investment in the Middle East using spatial econometrics during the period 2008-2019 using the space autocorrelation model (SAC). Statistics and information required for the three variables of foreign direct investment, inflation rate and degree of trade openness from the World Bank website and for the variable of terrorism, from the global database of terrorism and for the index of political instability, property rights and democracy from The ICRG site affiliated with PRS GROUP has been extracted for the period 2008-2019 in 15 Middle Eastern countries.

First, to investigate the spatial dependence of Moran and Jerry C tests, the spatial dependence of countries was confirmed and based on the significance of Moran test, the research model was estimated in the framework of spatial autocorrelation. According to the research results, terrorist activities show negative and destructive effects on attracting foreign direct investment in these areas and this result is consistent with the results of other studies such as Panahi (2013) and Salmani (Salmani, 2014) is. According to the research results, the variables of degree of trade openness and democracy have a positive and significant effect on attracting foreign direct investment in the study areas, while the variables of political instability, property rights and inflation have an impact. Negative and significant on attracting foreign direct investment in the study areas, among which the number of terrorist attacks has the most negative impact on attracting foreign direct investment, as well as property rights index, political instability, degree of trade openness. , Democracy and inflation rate have the greatest impact on the economic growth of these countries, respectively.

Foreign direct investment is one of the main components of economic development and its flow has great effects on a country's economy. In other words, terrorist activities reduce the security and confidence of investors in countries exposed to terrorist activities and reduce the flow of foreign direct investment. On the other hand, the anti-terrorist security costs imposed on the economy reduce the economic potential. The economic effects of international terrorism can be analyzed in the short and long term. In the short run, terrorism leads to financial losses, losses and the creation of an insecure investment environment, and in the long run, international terrorism diverts capital resources by increasing national security spending and counter-terrorism activities. The transition to these costs and tax increases. To explain why spatial regression is used in this study, it can be added that the variable of terrorist activities in area j will not be affected only by internal factors in that area. When the number of terrorist activities in the neighboring country increases, it has a negative effect on attracting foreign direct investment to neighboring countries (spillover effects) and also if the terrorist activities are effective in region j, it indicates the phenomenon of spatial dependence that conventional econometrics is possible. Does not estimate and identify these effects and factors.

Over the past three decades, many countries have implementedeconomic reforms that include trade liberalization policies and there is astrong interest in the gender impact of these reforms. On the other hand,trade liberalization determines the structure of employment, the extent ofpoverty, and the distribution of income and wages. The purpose of thispaper is to estimate the effect of trade liberalization on women'semployment using panel data from selected Islamic countries in theframework of a spatial econometric approach. The 1999 to2018 statisticswere used for this purpose. The results show that trade liberalization has adirect and significant impact, and tariff barriers have a significant andreverse impact on the employment of women in the Selected IslamicCountries. Also, the commercial liberalization of one country has had apositive effect on the employment of women in other countries. Thismeans that with the increasing commercial liberalization of each country,the average employment rate of women in other Selected IslamicCountries has increased.

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.

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.

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.

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.