فهرست مطالب shekoofeh farahmand

Extensive and efficient infrastructure is critical for ensuring the effective functioning of the economy. Investing in public infrastructure represents an essential investment in economic development and standard of living of city residents. Therefore, it is necessary to find new methods of financing in providing services and developing urban infrastructure in metropolises and increasing the welfare of urban society. However, the current approach to revenue mobilization for cities is unlikely to meet the substantial financing needs. Instead, there is a need for a metropolitan public financing strategy that is integrated into national urban development plans and matches national development objectives. In the literature related to city finance, despite the importance of providing suitable urban infrastructures, the discussion about how to fund them, especially in Iran, is rarely done. Therefore, the purpose of this research is to provide a suitable model for providing financial sources for public infrastructure in metropolitan cities with an emphasis on Isfahan metropolis.

In this research, a mathematical model for calculating the urbanization tax has been introduced, in which the cost recovery coefficients are related to the optimal size of the cities. Therefore, an equilibrium model is constructed based on cost-benefit analyses and applied to nine Iranian cities with population more than one million people. The panel data regression analysis was performed on a fourteen-year period (2006-2020) using the Transcendental Logarithmic (Translog) function. The obtained results are placed in the basic mathematical model. It should be noted that Excel2016 and Stata12 software were used to estimate the model and analyze the results.

The results of estimating the regression models related to determining the optimal size of the cities indicate that all the metropolises have exceeded their optimal size. Among the nine metropolitan cities studied, Kermanshah, Karaj and Qom have the largest excess population. Isfahan and Ahvaz have the lowest excess population. The results of calculating the urbanization tax for Isfahan Municipality indicate that the recovery of public infrastructure depreciation costs in the first year can generate more income than the income from property tax for Isfahan metropolis.

Providing infrastructure and public services by municipalities for the urban population, especially in metropolises, is a very difficult task and requires access to capital facilities. However, the way to collect these funds and how to provide the infrastructure budget has been less attention. In order to provide public services and urban infrastructure, municipalities should collect the costs related to a certain infrastructure as much as possible from the individuals, companies, localities and groups that benefit from it.Therefore, in this study, all the urban infrastructures of Isfahan metropolis are divided into three categories based on the benefits they create. The first category is infrastructures whose benefits are assigned to certain individuals and groups. The second category is infrastructures whose benefits are mostly limited to one place or a specific area within the city. The last category also includes those services and infrastructures whose benefits are allocated to the entire city and its residents.The results show that about 38% of infrastructure costs in Isfahan metropolis are related to the third category. Considering the allocation of these infrastructures to all residents, their cost can be collected through the urbanization tax and according to the optimal size of the cities. The results related to the city size model show that the population of all Iranian metropolises has exceeded its optimal size, so it is suggested to continue receiving infrastructure costs until full recovery.The results of this research emphasize that although the urban costs have decreased with the increase in population, the urban benefits have decreased more, and in general, diseconomies of scale have been created. However, people will not necessarily involve these diseconomies of scale that they bring to the city in their decisions related to work and migration. Therefore, it is recommended to receive these costs from them.

Consideration of the importance of the role of housing in the economy, especially in metropolitan areas such as Tehran, the analysis of house pricing and identifying the factors affecting housing prices is very importance. A noteworthy point in the study of housing price changes in the metropolis of Tehran is that the rate of price growth in different areas of Tehran has not been the same. Experience shows that price changes start in one district and then spread to other districts. Therefore, we should consider proximity and spatial dependence of housing prices in urban distrists.

THEORETICAL FRAMEWORK:

In the analysis of housing price data, the spatial dependence between observations must be taken into consideration. Accordingly, many experimental studies have shown strong evidence of spatial dependence in the housing market between urban areas. Spatial dependence on housing prices is also referred to as the wave effect, implying that housing prices in a district cause changes in neighboring districts' prices. Behavioral economics is a theoretical basis that can express the phenomenon of spatial dependence between urban districts. Regarding the theories of behavioral economics, nearby urban areas have the same culture, history, environment, and policies. Other phenomena that express the spatial dependence in the housing market of urban districts include migration theory, capital transfer, arbitrage, and spatial patterns.

 A critical issue in studies using spatial econometric techniques is the choice of the type of spatial model. Depending on the type of spatial interaction, we will encounter a variety of spatial models. To select spatial models, we can first consider the general spatial model and with the relevant tests to ensure the existence of the type of spatial interaction factor. Then, the appropriate type of model can be selected. According to Elhorst (2014), using the spatial lag fixed-effect model, we have modeled the housing prices in 22 districts of Tehran city in this study. Some variables affecting housing prices are related to the demand side of the housing market, and some are related to the supply side. Here, the explanatory variables in the model are the annual population growth rate of the districts, and the annual growth rate of the real disposable per capita income, which shows the demand side influencing the housing price, as well as the number of building permits and the annual unemployment rate as the supply-side variables that affect housing prices. The dependent variable is the districts' average annual real growth rate of housing prices.

According to the spatial specification results, the dynamic SAR model has been selected as the appropriate model. The estimated coefficient of the spatial lag of the dependent variable with a time lag is 0.033, which is statistically significant and indicates a positive effect. It implies that the spatial lag of the dependent variable with a time lag has influenced the growth rate of housing prices in the 22 districts of Tehran. Among the explanatory variables affecting the growth rate of housing prices in the 22 districts of Tehran, it is observed that, except for the unemployment rate variable, the other variables have a significant effect on the growth rate of housing prices in Tehran districts. The analysis of the local Moran scatterplot demonstrates that the spatial correlation of the housing price growth rate in the northern districts of Tehran is different from the southern districts.

 CONCLUSIONS & SUGGESTIONS:

Among the explanatory variables affecting the growth rate of housing prices in Tehran districts, except for the unemployment rate, other variables have statistically significant impacts. Two variables of the growth rate of income per capita and population growth rate have positive effects. However, the number of building permits has negatively influenced housing prices' growth rate. The statistically significant estimated coefficient of spatial lag of the dependent variable in the model implies the spatial effects of the housing price growth rate. All the necessary tests indicate that the null hypothesis, which indicates the lack of spatial autocorrelation, has been rejected, and a spatial correlation among the housing price growth rates of districts has been confirmed. The local Moran scatterplot illustrates that the Spatial correlation of housing price growth rate in the northern districts of Tehran is entirely different from the southern areas of Tehran. It is recommended that urban policymakers should not ignore the spatial relationship between housing prices in 22 districts of Tehran. Also, it is recommended to the policymakers, due to the different spatial correlation rate of the housing price growth rate in the southern areas of Tehran city compared to the northern districts of the city, for each of the northern and southern areas of Tehran, they should make different policies.

The analysis of data on housing prices and their growth rates, typical of spatial data, is undoubtedly affected by spatial dependence. This means that housing prices and their growth in one district are affected by housing prices in neighboring districts. However, the other issue regarding housing prices in different districts is the heterogeneity of spatial dependence. This suggests that there are differences in the spatial dependence of housing prices in urban districts over time so that the spatial effects in urban districts when prices rise are different from the effects when prices fall. The theoretical analysis of this phenomenon is based on the theories of behavioral economics. In this study, the heterogeneity of spatial dependence of housing price growth rates was investigated for 22 districts of Tehran. Using a dynamic fixed effects spatial panel model, the effects of determinants on growth rates were estimated for 22 districts of Tehran. The test results indicate the existence of nonlinear relationships in the model. Therefore, the model was estimated by a smooth transition panel regression model with a transfer function in which the spillover rate of housing price growth rates from neighboring counties was determined as a transfer variable. The results show that the coefficient of spatial dependence for housing price growth rates is higher in boom times than in recession for Tehran districts. Thus, it can be concluded that there is heterogeneity in the spatial dependence of housing price growth rates in the urban districts of Tehran over time.JEL Classification: C31, C33, R31.

Today, global warming is one of the most important human concerns in the fields of economy, energy and environment. The most important element in global warming is the burning fossil fuels that release the greenhouse gases including CO2. The researches by the Intergovernmental Panel on Climate Change show that global warming will rise more than 2 degrees centigrade by the end of the century with respect to the pre-industrial era, if no effort is made to reduce CO2 emissions. Since the MENA region is one of the most vulnerable regions in the world due to climate change, so the main purpose of this study is to assess the effects of climate change on the economic variables in MENA region until 2105. For this purpose RICE model is used which is based on the computational general equilibrium model. The results indicate that the global average temperature will rise to 4.49 degrees centigrade until 2105 year in comparison to the pre-industrial era, if no policy is implemented to prevent rising temperatures. The trend of regional GDP and consumption are similar and will increasingly move. In the long-run, the capital accumulation will increase in the upper-middle income, the lower-middle income and the high income countries, respectively; while employment will increase in the lower-middle income, the upper-middle income and the high income countries, respectively. Environmental damage is the most in the high income countries in comparison to the other groups in MENA region.

The Earth's temperature has climbed by 0.7 degrees Celsius (°C) during the last 100 years, and the worldwide average temperature is expected to rise between 1.8 and 6.4 degrees °C by 2100. Climate change, particularly rising temperatures, according to IPCC , the Middle East and North Africa (MENA) area will face challenges throughout the twenty-first century. As a result, the study's aims are to evaluate the impact of policies which eliminate or targetize fossil fuel subsidies in order to reduce global warming, as well as the impact of these policies on economic variables (GDP, consumption, capital accumulation, employment, and environmental impact) in the MENA until 2100. For this purpose, a Dynamic Regional Integrated Climate-Economy Model (RICE) is utilized to do this. The findings suggest that in the long run, if no strategy to limit temperature rise is enacted and carbon subsidies persist, the average world temperature would rise by 4.74 degrees °C, while an optimal policy based on fossil fuel taxation will increase the average global temperature by 4.49 °C, and a policy reforming fossil fuel subsidies will increase the average global temperature by 4.24 °C. Generally, carbon tax measures in the MENA area will lower average world temperature increase by 0.5°C compared to other scenarios.

ncreasing investment in research and development is a factor in increasing productivity in regional production and the growth of innovative areas. Knowledge and innovation overflow is an inevitable concept that is resilient to place. The purpose of this paper is to analyze the impact of expanding research and development costs on regional growth in different neighborhood ranks. For this purpose, has been used a combined model and investigation of research and development spatial overflow in 31 provinces of Iran. The research results show that; Natural logarithm variables of GDP, percentage of research and development costs to regional GDP, average years of education and population structure directly affect regional growth. However, the spatial lag of the natural logarithm of the GDP rate and the spatial lag of the variable population structure have an inverse effect on regional growth.

This study tries to predict the rental rates in district six of Isfahan for five years in the future by using an agent-based model. According to this simulation, district of Hezar Jerib has the highest and Hemat Abad has the lowest rental rate. Districts of Sa'adat Abad, Abshar, Baghnegar, Feiz, Masjed Mosala, Kuye Emam, Takht-e Foulad and Shahid Keshvari are followed by the district of Hezar Jerib. From the demand point of view, the high rental rate in Hezar Jerib district is due to higher comfort index in that region. From the supply point of view, the high rental rate in Hezar Jerib district is due to low supply of residential units.

Slum textures are one of the inevitable consequences of city expansion, which can be the source of many undesirable economic, social and structural problems. Choosing an appropriate urban management strategy can play a crucial role in improving urban structure in its different areas including the slums. The aim of this research is to determine the priorities in upgrading the slum texture of Bushehr city with an emphasis on the level of livability and urban good governance, using AHP method. Therefore, according to experts opinions the priorities of livability and urban good governance sub-indicators and the priorities of slum texture neighborhoods for upgrading were determined. The sampling method was non-random and purposive. According to the results, in the slum neighborhoods, sub-indicators of livability including health, quality of economic indicators (job satisfaction and income level) and the sub-indicators of urban good governance including the rule of law and corruption control are in priority, respectively. The priority of the seven slum neighborhoods of Bushehr for upgrading is respectively as follows: The Third Tangak, The Second Tangak, The First Tangak, Saretol, Rayani, Rishehr and Emamzadeh.

Economic specialization and diversification in an urban area are main factors forming agglomeration economies. Agglomeration economies increase productivity of clustered firms in an area. This research investigates the impact of specification and diversification in economic activities on labor productivity in the provinces of Iran during 2000-13. Therefore, first, urban economic specification and diversification are measured using appropriate indices. Then, the indices are entered in the productivity model as an independent variable. Since used data has locational dimension and the spatial dependence diagnostic tests are significance, the specified model is estimated through spatial econometric techniques.
The results show in both spatial lag and error, specialization and diversification of economic activities, as well as capital stock and government budget have a significant positive with productivity. But human capital has a U-shaped relationship with productivity. In addition, the estimated coefficients of spatial lag and spatial error are positive and statistically significant and indicate spatial dependence of productivity in the provinces of Iran.

In each country, there are a few large cities along with a large number of small and medium size towns. Industrialization and the concentration of resources in large cities causes economic growth. However, resource shortages in small and medium-sized cities would decrease growth. Hence, the effect of city size distribution on economic growth is ambiguous. The objective of the study is to investigate the relationship between the city size distribution and growth in thirty provinces of Iran in 2006-11 through Solow-Swan growth model. The model has been specified as a spatial Durbin model in the form of a dynamic panel data. Results indicate the estimated coefficients are negative for both time and space lags of income per capita. The estimated coefficients of the variables of the Gini-coefficient and the Hirschman-Herfindahl index, as well as the spatial lags of these two are all positive and significant which show positive direct and spatial effects of the distribution of cities size on growth. The coefficients of other independent variables including education, inflation, budget, and fertility rate emerge significant with the expected sign.

Societies have paid attention to safety. This study examines the relationship between socio-economic factors and crime, emphasizing on immigration. Due to the locational aspect of the data, spatial econometric techniques are used. The model has been specified in the form of Spatial Durbin Panel Data Model (SDPDM). The specified model has been estimated for 30 provinces of Iran in 2006-11 by considering two variables of theft and murder. In model I, unemployment, urbanization and income per capita have had significant positive impacts on theft, while industrialization and Gini coefficient have inversely influenced theft. In model II, economic growth and income per capita have had significant positive impact on murder rate. Result show spatial dependence.

Working capital management is one of the most important issues for financial managers, and they always try to determine the rational level of working capital to manage their activities. Cash conversion cycle is the indicator used for measuring working capital. When a firm uses its sources rationally to react to unexpected financial situation, sources of working capital may provide competitive ability for the firm. In this study, a sample of 257 companies listed in the Tehran Stock Exchange in a period of11 years from 2002 to 2012 was selected to assess the expected effects of working capital and financial flexibility on competitive ability of the firms. Data analysis was carried out by the generalized momentum method.The results indicated that there exists a positive and significant relationship between current asset turnover period and competitive ability, and that there are negative and significant relationships between the three variables of receivables collection period, payable turnover period, and cash conversion cycle, and the variable of competitive ability. Also, the results showed that there are not significant relationships between the three variables of inventory turnover period, current ratio, and quick ratio, and the variable of competitive ability. The results of this study revealed that working capital management has widely effects on the competitive ability in market and the functional efficiency of the firms, and that working capital ability has positive effects on the competitive ability in products market, but such effects reduce when working capital ability decreases below a certain level.

During recent decades، decentralization has been regarded in various societies as an instrument for making public sector policies more efficient، and its numerous advantages and disadvantages have been discussed. Each decentralization policy has three dimensions including Political decentralization، Administrative decentralization and Fiscal decentralization. This paper evaluates the impact of fiscal decentralization on the interaction between economic growth and regional equity in the distribution of fiscal resources in provinces of Iran by using panel data method. The results verify a nonlinear relation between fiscal decentralization and economic growth، so that economic growth rises with fiscal decentralization increase to a specific level and then it decreases because of disadvantages of decentralization. There is a relationship between fiscal decentralization and equitable distribution of fiscal resources too. Growth and equitable distribution variables change in the opposite direction between two levels of decentralization، and move in the same direction out of this interval. There is also a tradeoff between growth and equitable distribution of fiscal resources.

The economic convergence concept arises from the Solow-Swan growth model. Accordingly, two hypotheses are considered: absolute and conditional convergence. The first implies the convergence of economies towards a steady-state. The second hypothesis is based on the convergence of each economy toward its own steady-state. Indeed, it refers to different structures of economies. In experimental studies, for testing the conditional hypothesis, different determinants are entered in the growth model to capture the differences in structures. However, one coefficient is estimated for β-convergence and one convergence speed is obtained. This paper examines the convergence hypotheses for Asian countries over the period of 1999-2009 using the geographically weighted regression (GWR) approach. GWR provides useful means for dealing with spatial variation in convergence speed. In this way, convergence coefficients can be computed for considered countries. The results show that, speed of convergence varies over different countries. Also, the spatial variation of steady- state incomes is significant.

In the recent literature on poverty and growth two main questions are receiving increasing attention: How much do the poor share in aggregate economic growth? And what factors explain differences (across space or over time) in the impacts of economic growth on poverty? In economic activities, with the growth of the agricultural sector, it is expected that extreme poverty will be reduced and income distribution will become more appropriate. Agricultural sector contains employment opportunities, both direct and indirect, which increase national output more than many others sectors. Research shows that the most successful economies are those that push the industry towards increasing exports. Studies show that the growth rate of the service sector (in terms of employment) is higher. Education, health and recreation services, have a positive impact on the quality of the organization. Professional services, including special skills for increasing competitiveness of firms provide special expertise for a business company which is competitive. One of the other policies that come to fight poverty is increasing human capital through training people. Increasing levels of education lead to increasing individual employment. This means that the main level of a nation's life is the ability to use skills, awareness about issues related to health and education. Income inequality is another important factor affecting poverty which is in a close relationship with it. In fact, as income inequality increases, the gap between the poor and the rich becomes wider. Since the growth of agriculture, industry and service sectors and the impact of variables such as education, health and social assistance on them are important, the question is what relationships might exist between these variables and poverty and welfare? Previous research has shown that growth in average income is correlated with reduction in the occurrence and depth of poverty. Looking at 67 countries, Ravallion and Chen (1997) find that inequality changes were uncorrelated with growth rates between 1981 and 1994, implying that poverty declines are strongly correlated with growth in mean incomes. They estimated that the elasticity of poverty incidence (at the “$1-a-day” line) to mean household income was about −3. Ravallion (2001) finds a lower elasticity of −2.1, when an econometric correction is made for measurement errors in surveys. Dollar and Kraay (2002) also found that “growth is good for the poor:” in a sample of 92 countries, over four decades, the mean incomes of the poorest 20% of the population grew on average at the same rate as overall mean incomes. For India, Ravallion and Datt (1996) found that growth in the agricultural and (especially) service sectors had a higher impact on poverty than manufacturing growth. Using state-level data over time for India, Ravallion and Datt (2002) found that the elasticity of poverty to non-agricultural growth varied significantly across states, and was greater in states with higher initial literacy and farm productivity, and lower landlessness and infant mortality. There is a relationship between poverty and social welfare, as it is shown in figure (1). We studied the poverty and welfare impacts of economic growth in provinces of Iran using information on poverty and social welfare, output by sector and a number of controls variables for a period spanning 8 years. We used value added information for sector growth data bases and household information for calculating the social welfare index and poverty index.We applied sectorial variation in these data to shed light on the determinants of poverty dynamics in Iran. Since we have a panel of 28 provinces in 8 years, we allow the regression coefficients to vary by provinces. The estimation method is GMM. In this method we use instruments and lags for variables. To motivate our specification choice, consider first the following model in levels:Discussion of Result & Iran's disappointingly low rate of poverty reduction and high welfare between the 2000 and 2007 was not due only to weak economic growth — though this was certainly key. It also reflected a low growth elasticity of poverty reduction, consistent with the country's high level of inequality. In this paper, we investigated three possible sets of factors that determine the distributional component of poverty reduction and more social welfare. We did find marked differences in the poverty-reducing effect of growth across different sectors, with growth in the service sector being consistently more pro-poor than either in agriculture or industry sectors.

Location analysis could lead to reduction of costs of establishing and running economic activities. Sometimes، choosing an incorrect location could dramatically increase the costs. A suitable location for economic activities is one of the most important factors in having a good urban space for citizens، firms and municipalities. In cities، most of firms are service providers. Due to the existence of external economies of scale and reduction of costs، especially transportation costs، firms are usually located near together. Clustering similar firms can lead to decreasing costs، facilitating shopping for buyers and attracting potential buyers. This study tries to investigate the distribution of economic activities in Isfahan، as well as determining specialized and diversified zones of the city. It also analyses effective factors on locating different activities. Thus، specialization and diversification of all 14 zones of Isfahan are measured and then a regression model is specified and estimated by GMM approach. Results show that number of banks has positive effect on location of different activities. Meanwhile، specialization and diversification، which are the result of the economies of scale in localized and urbanized agglomerations، are critical factors on choosing locations in the city.

Economic convergence is one of the important topics of new macroeconomics. It refers to tendency of income per capita of countries (regions) to converge to their steady-state value. There are two kinds of convergence: conditional and absolute convergence. This paper examines income convergence between 22 MENA countries during the period of 1970-2003 by using the neoclassical growth model of Barro- Salla-i-Martin for both kinds of convergence. Non-linearity of the underlying relationships, the restrictiveness of assumptions of functional forms and econometric problems in the estimation and application of theoretical models advocate for the use of Artificial Neural Networks (ANN) algorithms. We show that by changing the quantitative tools of analysis and using ANN, the results become more precise. Results show that absolute convergence and conditional convergence are significant but the rate of convergence is low.

There are different studies in urban literature on the determinants of urban growth, from the theoretical and empirical points of view. The most completed theoretical model is Henderson model (1988, 1997, and 1999), which is tested by some empirical studies. As Henderson model shows, the set of national product, specialization and technological progress are the determinants of urban growth. Using this model, the paper investigates the urban growth of Iran over the period 1986-2006. The national product is divided into four groups including agriculture and mining; industry and construction; public, personal and distribution services; and information-based services. The specialized cities are determined based on the last three groups and the Henderson’s theorems are tested for them. Eventually, the effect of each type of specialization is tested on urban growth in Iran. The results demonstrate that specialization has positive effect on urban growth in Iran.

Urbanization agglomeration that is named Jacobs externalities, refers to the role of economic diversification in urban. Localization agglomeration, Marshal-Arrow-Romer (MAR) externalities, is related to the concentration of firms activated in a special industry within a specified place. The purpose of this research is to explore the impact of different types of agglomeration economies on employment growth for provinces of Iran in 1996-2006. Empirical results demonstrate a U-shaped relationship between specialization and urban growth We find a positive impact of Jacobs’s externalities on employment growth in provinces of Iran.

This study investigates the relationship between conditional conservatism and the cost of equity capital. The conditional conservatism rate is measured, using Callen et al (2009) at firm-year level; and the impact of conditional conservatism on cost of equity capital at firm and portfolio level is studied, using the three Fama and French (1993) factor model. The data used consists of a sample of 82 firms that are publicly traded in the Tehran Stock Exchange (TSE) in the period 2001-2009. A multi-variable regression model is used for testing of hypotheses in a cross-sectional and time series framework. The results from hypotheses testing show that there is a significant negative relationship between conditional conservatism and cost of equity capital, and that the higher the degree of conditional conservatism the lower is the firm’s cost of equity capital. The results also show that there is a positive relationship between conditional conservatism and portfolio’s cost of capital. This relationship is statistically significant for both the firms with medium and high conservatism portfolios, but not for the firms with low conservatism portfolio.

There is a significant relationship between economic growth and the degree of urban concentration, as measured by primacy or the share of the largest city in an urban system. In accordance to urban economic theories, there is an inverse-U shape relationship between urban concentration –urban primacy- and economic growth. That is, as economy grows, urban concentration increases, approaches an optimal level and then declines. If distortion from the optimal level is happened, it can lead economic growth to reduce. Some countries have significantly excessive primacy and some have too little. Additionally, trade is one of the key factors that can affect urban concentration. In this study, urban primacy of some selected Asia- Pacific countries is computed and its effect on economic growth is tested using Solow-Swan growth model. It also looks at the determinants of primacy and policy instruments that might be effective in reducing excessive primacy. Results show that primacy has significant effect on economic growth. Moreover, as trade influences primacy, it can be thus considered as an effective policy instrument in controlling urban over-concentration.

A key issue for many countries and even for international organizations including «The World Bank» and «The United Nations» is how to attack poverty. In many countries of theworld, millions of people are hungry, lacking shelter and clothing, sick and uncared for, illiterate and not schooled. These, all cause to reduce efficiency and productivity of labor, and hence decrease income. Also, being in a geographical region in which there are poor countries is itself a factor of poverty. In fact, there is a poverty trap in such regions. That is, being poor and being in a poor region are factors which lead to longer and deeper poverty. Many Muslim and Arab countries are classified as low income countries and they are also contiguous to other low income ones. Studying poverty in these countries is necessary and can be helpful for deciding about both domestic and common regional polices for them. Therefore, this study focuses on poverty in Arab and Muslim nations, and analyzes this subject through spatial econometric techniques, because spatial econometrics is a suitable method for considering spatial and geographical effects. Countries under study are clustered in accordance of both income poverty indices.