مجله اقتصاد و توسعه منطقه ای
پیاپی 11 (بهار و تابستان 1395)

Per capita Ecological Footprint (EF) or Ecological Footprint Analysis (EFA), is a means of comparing the consumption and lifestyles while checking this based on the nature's ability to account for this consumption. The tool can inform the policymakers by examining to what extent a nation uses more or less than what is available within its territory, or to what extent the nation's lifestyle would be replicable worldwide. The footprint can also be a useful tool to educate the people about the nature capacity and over-consumption with the aim of altering personal behaviors. Ecological footprints may be used to argue that many current lifestyles are not sustainable. Such a global comparison also clearly shows the inequalities of the resource use on this planet at the beginning of the twenty-first century. The ecological footprint analysis is now widely used around the Earth as an indicator of the environmental sustainability. It can be used to measure and manage the use of resources throughout the economy. It can be used to explore the sustainability of the individual lifestyles, goods and services, organizations, industry sectors, neighborhoods, cities, regions, and nations.
The ecological footprint accounting method at the national level is described in the Atlas Footprint 2010 or in greater detail in the calculation methodology for the National Footprint Accounts. The National Accounts Review Committee has also published a research agenda on how the method will be improved. There has been a difference in the methodology used by various ecological footprint studies. The examples include how the sea area should be counted, how to account for fossil fuels, how to account for the nuclear power, which data sources used, when average global numbers or local numbers should be used, when to look at a specific area, what areas for biodiversity should be included, and how imports/exports should be accounted for. However, as new footprint standards emerge, the calculation methodologies are converging.
The EF is an attempt to quantify sustainability. The EF is based on the fact that every human activity has an impact on the environment through the resources required by these activities and the wastes generated from them. The logic dictates that a certain area of land is required to produce resources and sequester the wastes. What differentiates EF from other methods of sustainability assessment is that all human enterprises are reduced to a single dimensional area. Ecological foot-printing itself is based on several assumptions, the primary ones being as follows: It should be possible to identify the resources required by an activity and quantify the wastes generated by it. These resources and wastes can then be converted to the land area values that are representative of the bio-productive land required to produce the resources and sequester the wastes. The EF represents the critical natural capital requirements of a defined economy or population in terms of the corresponding biologically productive areas (Rees & Wackernagel, 1992). Once the values for the resource consumption are generated, biological yield conversion factors are used to translate the resource flows into land values. These conversion factors can vary greatly depending on how they are calculated as well as the bio-productivity of the regions on which they are based. The resources themselves are divided into several sections such as housing, transport, consumer goods etc. while this can also vary based on the methodology which is used. Once calculated, the per capita footprint can be compared to the global Earth-share, which is the average land availability per person on the earth.
Any overshoot above this figure is termed the environmental deficit that indicates the degree to which a population is living beyond the nature’s means. An easy method for visualizing what the EF means is the example of the modern city with the associated resources and waste flows. A large dome covers the city and the only thing that can travel through this dome is light. Naturally, the inhabitants do not survive and the structure of their society breaks down. Imagine, if it were possible to stretch this dome, it encompassed the bio-productive area outside this city. The EF of the city/region is the total area the dome would have to cover to be able to sustain itself indefinitely with the same levels of consumption. That is, the total area required to provide all the resources and sequester all the wastes indefinitely. Thus, EFs are practical indicators for the impact or environmental overshoot of the region since high economic demand equates with an excessive resource requirement. This means more land is required to maintain production, which in turn, results in the depleted capital stocks. Productive land itself is a good proxy for the natural capital since it can supply the vital ecosystem services.
The article is classified in several sections, Calculation of agricultural land shows: South Khorasan has the highest ecological footprint and the Fars lowest agricultural ecological footprint among Iran provinces. Calculation of energy land shows: Isfahan has the highest ecological footprint and the Sistan and Bluchestan lowest energy ecological footprint among Iran provinces. Calculation of Pasture ground land shows: south khorasan has the highest ecological footprint and the Qazvin lowest Pasture ecological footprint among Iran provinces. Calculation of Forest land shows: Tehran has the highest ecological footprint and the Sistan and Bluchestan lowest Forest ecological footprint among Iran provinces. Calculation of Build up land shows: south Khorasan has the highest ecological footprint and the Western Azerbaijan lowest Build up ecological footprint among Iran provinces.
But this research results show that the inhabitants of Isfahan have footprint 2.412 acres for each person so Isfahan has the highest amount of the footprint between the provinces of Iran. Furthermore Sistan and Baluchestan's footprint was 1.962 hectares for each person that has the least amount of ecologic value between the provinces of Iran

Renewable energy is derived from the natural processes that are replenished constantly. In its various forms, it derives directly from the sun, or from the deep heat generated from the earth. It isdefined as the electricity and heat being generated from solar, wind, ocean, hydropower, biomass, geothermal resources, biofuels, and the obtained hydrogen from the renewable resources. The renewable energy resources exist over the wide geographical areas in contrast to other energy sources, which are concentrated in a limited number of countries. The rapid deployment of the renewable energy and energy efficiency result in the significant energy security, climate change mitigation, and the economic benefits. The results of a recent review of the literature concluded that as the greenhouse gas (GG) emitters begin to be held liable for the damages emerging from GHG emissions in which lead to the climate change, the liability mitigation value would increase to provide powerful the incentives for the deployment of renewable energy technologies. At the national level, at least 30 nations around the world have already renewable energy contributing to more than 20% of energy supply. The national renewable energy markets are projected to continue to grow strongly in the coming decade and beyond while some 120 countries have various policy targets for the longer-term shares of the renewable energy including the 20 percent of the targeted electricity generated from the European Union by 2020. Some countries have much higher long-term policy targets of up to 100 percent renewables. Outside Europe, a diverse group of 20 or more other countries have targeted the renewable energy shares in the 2020-2030 rangimg from 10 to 50 percent.
This study is an investigation of the climatic characteristics of the regions of Khorasan and the neighboring areas within the interior regions (Semnan, Sistan, Yazd, and Mazandaran) as well as the foreign regions (Turkmenistan and Afghanistan). Besides, it is probingthe technical-economic conditions of the renewable-fossil hybrid power generation along with the impact of the implementation of 2030 renewable energy outlook policies of Khorasan regional electricity hybrid production system as well.
Analytic programming was inspired by the numerical methods in Hilbert functional spaces and by GP. The principles of AP are somewhere between these two philosophies: The idea of the evolutionary creation of symbolic solutions arise from GP, whereas the general ideas of the functional spaces and the construction of the resulting function by means of a search process (usually done by the numerical methods such as Ritz or Galerkin method) are adopted from Hilbert spaces. Like GP or GE, AP is based on a set of functions, operators and so-called terminals, which are usually constants or independent variables. All these ‘mathematical’ objects create a set from which AP tries to synthesize an appropriate solution. The main principle of AP is based on Discrete Set Handling (DSH), proposed by Zelinka (2001). DSH can be seen as a universal interface between EA and the problem to be solved symbolically. That is, why AP can be carried out using almost any evolutionary algorithm. The set of the mathematical objects are functions, operators and so-called terminals (usually constants or independent variables). All these objects are mixed together consisting of functions with different number of arguments. Because of the variability of the content of this set, the article purposes of General Functional Set (GFS) is required. The structure of GFS is nested, for instance, it is created by the subsets of functions according to the number of their arguments. The content of GFS is dependent only on a user. Various functions and terminals can be mixed together. The subset structure presence in GFS is vitally important in AP. It is used to avoid the synthesis of the pathological programs, for instance, programs containing functions without arguments, etc. Performance of AP is, of course, improved if functions of GFS are expertly chosen based on the experiencies with the solved problem. The important part of the AP is the sequence of mathematical operations which are used for the program synthesis. These operations are used to categorize the individuals of the society into a suitable program. Mathematically saying, it is mapping the individual domain onto the program domain. This mapping consists of two main parts. The first part is called Discrete Set Handling (DSH) and the second one is the security procedures which do not allow for the pathological programs synthesis.
Simulation results show that the implementation of 2030 renewable energyies outlook policies will lead to 18.62 TWh optimal inter-regional and trans-regional exports which 2.32 TWh of this optimal export will be generated because of implementation of 2030 renewable energy outlook policies. This 14 percent increase in the inter-regional and trans-regional exports creates 5,000 jobs in Khorasan and increases the associated cost by 32 percent, but there would be little impact on the environmental emissions’ reduction. The related reason for this insignificant reduction in the environmental emissions is the low limited renewable power generation in the production system. Besides, thereason for the significant increase in the price is the high capital cost of the solar and wind production which needs strong financial support from the technical-engineering wind and the solar projects as they share the cost of production with the customers. The maximum potential production capacity in order to cope with the fluctuating nature of the renewable generation, is thebasic attempt for the development of the renewable electricity generation.
Most of the world's leading countries in the field of renewable energy have used Feed-in Tariff to create an affordable price for the renewable power generation systems. It achieves this by offering long-term contracts to renewable energy producers, typically, based on the cost of generation of each technology. In addition, feed-in tariffs often include tariff degression which is amechanism according to which the price (or tariff) ratchets down over time. This is done in order to track and encourage the technological cost reductions. Also, developing the required financial incentives and promoting the standards for connecting the renewable sources to the grid is called for. In addition, the rules regarding the sharing of costs with the common network can also provide the necessary legal and technical infrastructure to make the hybrid production system.

One of the economic problems in the developing countries is the debt problem. External debt occurs in the developing countries due to the elimination of the restrictions on the savings gap, the foreign exchange gap, and the fiscal gap in order to form the capital to accelerate the economic growth (Karakoy et al., 2012, p. 491). In contrast, borrowing and rising the external debt could be little in the economic growth of these countries due to theadverse economic effects such as debt overhang problems, crowding out effect, and uncertainty (Karakoy et al., 2012, p. 491). In general, there are three groups of theories regarding how to influence the external debt for the economic growth. The first group of theories relates reasonable debt levels to positive effects on growth; the second relates the high accumulated debt levels to the negative effects on growth (low growth), and the third combines those two effects while arguing that the impact of debt on growth is nonlinear by nature (Oleksandr, 2003). In this regard, the main purpose of this paper is to investigate the non-linear impact of the external debt on the economic growth in 8 Developing (8D) countries group including Indonesia, Iran, Bangladesh, Pakistan, Turkey, Malaysia, Egypt, and Nigeria.
Theoretical frame work
For the purpose of this paper, the researcher adopted the debt overhang theory. The debt overhang theory is based on the premise that if the debt will exceed the country's repayment ability with some probability in the future, the expected debt service is likely to be an increasing function of the country's output level. Thus, some of the returns from investments in the domestic economy are effectively taxed away by the existing foreign creditors while the domestic and new foreign investors are discouraged (Claessens, 1996). Under such circumstances, the debtor country shares only partially in any increase in output and exports because a fraction of that increase will be used to service the external debt. The theory implies that the debt reduction will lead to the increased investment and repayment capacity, thus, the portion of the outstanding debt becomes more likely to be repaid. When this effect is strong, the debtor is said to be on the wrong side of the debt Laffer curve. In this case, the debt Laffer curve is referred to the relationship between the amount of debt repaid and the size of the debt. However, the idea of the debt Laffer curve also implies that there is a limit at which the debt accumulation stimulates growth (Elbadawi et al., 1996). In reference to the debt Laffer curve, Lensink and White (1999) argue that there is a threshold at which more debt is detrimental to grow.
The liquidity constraint is captured as a crowding out effect, by which the requirement for the service debt reduces funds available for the investment and growth. A reduction in the current debt service should, therefore, lead to an increase in the current investment for any given level of future indebtedness (Cohen, 1993). Other channels which can affect the need to service a large amount of external obligations for the higher economic performance include the lack of access to the international financial markets and the stock debt on the general level of uncertainty in the economy (Claessens, 1996). However, debt has to be repaid. Funds borrowed will simply postpone the taxation. Hence, the purpose for which the funds are gained and their relative returns becomes crucial. If the government invests on the infrastructure such investments are capable of leading to the faster growth and the socio-economic development (Mowlaei & Golkhandan, 2014).
In order to determine the reaction of the economic growth to the external debt and other traditional sources of growth, the following logarithmic production function in a Panel Smooth Transition Regression (PSTR) model is used. In this model, countries are denoted by the subscript i and the subscript t denotes the time period (1991-2013). Other variables are defined as follows: GDP: Gross domestic product per capita; ED: The ratio of the total external debt to the gross domestic product; INV: The ratio of the fixed gross capital formation to the gross domestic product; EDU: The ratio of the education expenditure to gross the domestic product; GOV: The ratio of the government final consumption expenditure to the gross domestic product; OPEN: The degree of the economic openness index by the ratio of the sum of exports and imports to the gross domestic product; POP: Population; INF: Inflation rate; r: The number of transfer functions; g: Transfer functions; q: Transmission (threshold) variable; : Slope parameter; c: The vector of threshold parameters.
The linearity test results indicated that there is a strong nonlinear relationship among variables under consideration. Moreover, considering one transition function with one threshold parameter, that represents a two-regime model, is sufficient to specification of nonlinear relationship among variables. The results indicated that the threshold value is 34.12 percent and the estimated slope parameter is 1.83. In order to provide the clearer evidence of the obtained results, two extent regimes were investigated: First regime : Second regime : Based on the above results, in the first regime, the external debt has a little negative impact on the economic growth. Beyond the threshold level, in the second regime, this negative impact increases.
Conclusions & Suggestions: This paper investigates the threshold effects of the external debt on the economic growth in eight developing countries from 1991 to 2013 using Panel Smooth Transition Regression (PSTR) model as one of the most prominent regime-switching models. The linearity test results indicated a strong nonlinear relationship among the variables under consideration. Moreover, considering one transition function with one threshold parameter, that represents a two-regime model, is sufficient to specification of nonlinear relationship among variables. This negative impact increases if it is beyond the threshold value in the second regime. Therefore, not only the external debt has not played an important role in the acceleration of the economic growth in the eight developing countries; but also, its increase is the barrier to economic growth in these countries. The results have important implications for the policymakers of the eight developing countries. It is a major challenge for the governments to formulate a prudent debt management policy to control and maintain the level of indebtedness of their countries at a manageable level before it becomes too late and the country becomes involved in a debt overhang situation or, to a lesser extent, is in default.

Issues related to environment are one of the most important issues the communities are facing with in the recent decades. On the other hand, the resource scarcity and the necessity of development for Iran and other similar countries makes the issue of efficiency as a solution of the environmental crisis important. In this study, the effects of the variables energy intensity (as one of the most common indicators of efficiency), population, affluence (GDP per capita), and the energy use are examined on the carbon dioxide emission with the method of panel data for the period of 1996- 2010.
Nowadays due to the expansion of human economic activities, the environment has been destroyed dramatically at the local and international level, thus, considering carbon emission and its issues have become one of the most challenging issues during the recent decades (Deluna, 2008). Also, the existence of the bilateral relation between growth and the environmental development is one of the more important and complex problems which has always captured different points of view (Dincer,1999). Different countries are willing to achieve the balanced growth rate which requires special attention to the destructive pconsequences emerging as a result of the subsequent of energy consumption. The lack of attention to this matter can bring irreparable problems to the countries (Sadeghi & Sadat, 2004).
Too aggregation of the greenhouse gasses in atmosphere is one of the most important reasons of rapid changes in climate. Changes in climate, in turn, leads to an increase in world temperature, rising of the sea level , irregular weather condition, outbreak of floods, and other damages on earth. Solving these environmental problems with different subsequences is usually difficult. For example, to save the coastal areas replacing millions of population to other places is required (Delona, 2008). On the basis of the governmental climate change organization report only up to 2020, there is an opportunity to reverse the increasing trend of emission and its results.
Theoretical Framework
One of the most popular methods which is usually used for the environmental issues is the equation of Environmental Impact, Population, Affluence, and Technology (EIPAT). This Model considers the effects of important variables can improve the environmental conditions as the technical innovation and improvement in technology is considered at this method. On the basis of this methodology, three major elements have more impact on the environment. These variables are population, affluence, and technology. Any changes in the abovementioned variables affect the condition of the environment. The relation between the technical innovation and environment is apparent in this model. Meanwhile, in spite of Erlich and Holdern, (1971), population factor is at the core of this model, on the other hand population growth causes an increase in the consumption which, in turn, can affect the income. At the same time technology is implicitly considered at this framework. Technology improvement may get fixed or even decrease per energy consumption due to the increase in efficiency.
On the basis of the theoretical framework the main important variables which are selected in this study are, population, energy intensity which are the proxy of energy efficiency, affluence, energy consumption, and the foreign direct investment for the period of 1996-2010. Energy intensity is modified as a portion of energy consumption to GDP. The data is collected from the nine member countries which are Algeria, Angola, Indonesia, Iran, Oman, Kuwait, Saudi Arabia, and United Arab Emirates. The data base is collected from the World Bank data base. Also, the data from population (urban population), affluence (per capita Income), foreign direct investment, and energy consumption are collected from the World Bank data base. Due to the different data base used in the current work, the methodology is a logarithmic model. This study examines the relationship between the efficiency of energy and the economic growth among the selected OPEC member countries.
Results show that the population is a more important factor in carbon dioxide emission. Subsequent to population growth, are the demand increase in farm lands, energy resources, water requirements, and so on. All these lead to a destruction of environmental issues (Perman, et al.2003). The results also show that a huge percent of emission is related to the increase in the population rate. Meanwhile, the energy efficiency shows a significant effect on the environmental issues. It means while the energy density increases, the emission also rises and vice versa. Hence, the improvement in energy efficiency will affect the quality of environment. Also, there is a significant positive relation between per capita income and the dioxide carbon emission (Asgharpour, et al.2013).
Energy efficiency also has a meaningful positive effect on the environmental indices. It means that by the increase of energy intensity, dioxide emission will also increase, and vice versa. The findings confirm the obtained results of Delona, 2008, Diters, 1998, and Rose. One of the most important factors in the rise of energy intensity, is the low quality and the price of the productions compared to the similar productions in other countries. The main reason for this, is because of the old manufacturing structure in the developing countries along with the cultural and social factors.

Regional inequality on social and economic grounds is one of the important obstacle in economic development. Thus, one of the main issues for policy making and planning in designing a comprehensive social and economic plan is the balanced development in different regions. The recognition of each region situation in relation to other cases is a necessary factor in decreasing inequalities and the optimal allocation of financial and physical resources to different regions and cities. This paper aims to study the development level in the cities of Khuzestan based on the health care indicators using numerical taxonomy. In this study, 36 health indicators are used to determine and compare the degree of development in the cities of Khuzestan in 2008 and 2013.
Theoretical Framework
Health is one of the forms of human capital that can affect the economic performance for the individuals at the macro level. Usually the healthier people produce more, because due to the mental, emotional and physical aspects, they use technology and tools better and more efficient than others (Currie & Madrian,1999) Bleaky believes that health, has a positive effect on the educational achievements. Similarly, the higher extent of healthy, increases the efficiency of the trained manpower (Lotfalipour Fallahi, & Borji, 2011). The effect of health on the labor supply is ambiguous. On the one hand, healthier people have higher productivity and thus the higher wages. The increase in income, leads to greater incentives to supply more labor (the substitution effect). On the other hand, the increase in income may motivate more leisure and may reduce the labor supply, accordingly(the income effect).If the income effect dominates the substitution effect, the economic growth will reduce (Suhrcke et al., 2005).
The method of this study is descriptive and analytical while using the numerical taxonomy technique. the geographic scope of the study is the cities of Khuzestan in Iran. the statistical and the data collection techniques are the library and the tables of formal reports. The numerical taxonomy technique was first suggested by Anderson in 1763 and later in 1968 was considered by Hellwing as a method for ranking and determining the development degree of different nations. This is an efficient method for the ranking, classification, and the comparison of countries and different areas taking their development degree into account along with dividing a certain set into relatively heterogeneous (Bidabadi,1983) .The performance steps are as follows: 1. The constitution of data matrix and the calculation of the average and the standard deviation of every column
2. The constitution of standards matrix for the elimination of different units and their replacement with a single unit
3. The calculation of composite distances between areas
4. Determination of the homogeneous areas
5. Determining the model or paradigm of areas and grading the development level of areas
. The setting consisted of 20 cities in .Khuzestan The status of these cities was investigated using 36 indicators of health care in terms of the level of development and accessibility by the numerical taxonomy technique in 2018 and 2013. The indicators were selected based on the literature review.
The results show that based on the health care indicators, in 2008, the cities of Behbahan and Ramshir, with the coefficients development degree of 0/5885 and 1/0083 were the most developed and the most undeveloped cities respectively while in 2013, the cities of Behbahan and Mahshahr¡ with the coefficients development degree of 0/7235 and 0/9742, were the most developed and the most undeveloped cities accordingly. Also, according to the results in 2008 , Behbahan, Ramhormoz, Ahvaz, Abadan, Shooshtar, Dashte Azadegan, and Baghmalek were above the development border (0/8157) while, Andimeshk, Hendijan, Mahshahr, Dezful, Masjedsolaiman, Shoosh, Omidieh. Khorramshahr, Shadegan, Izeh, Gotvand and Ramshir were below this line. In 2013, Behbahan, Lali, Ramhormoz, Baghmalek , Dashte Azadegan, Ahvaz, Masjeds Solaiman, Hendijan, Dezful, Shooshtar and Andimeshk were above the development border (0/8557) and Omidieh ,Ramshir, Abadan,Gotvand, Shoosh, Izeh, Khorramshahr, , Shadegan and Mahshahr were below the development border. Besides the results show the decrease of inequality between 2008 and 2013.
Suggestions: 1-According to the condition of cities of Omidiyeh, Abadan, Gotvand, Shush, Ize, Khoramshahr, Shadegan and Mahshahr in 2013, it is necessary that theauthorities bring balance to the cities of Khuzestan regarding the allocation of health care facilities, especially in Mahshahr that which is the most deprived city in 2013.
2-Since the cities of Izeh, Mahshahr, Khoramshahr, Shadegan, Shush and Hendijan , were undeveloped in both years and got relatively worse in 2013, the policies of the allocation of health facilities in Khuzestan, needs to be modified. to avoide a prolonged and more backwardness of these cities
3-Khoramshahr has suffered from the most damage during the war, in addition to being in the undeveloped group in both years, 2008 and 2013, due to the social and political, reasons and values, thus it is necessary that the authorities pay special attention to the allocation of health facilities to this city.

Regional agreements can facilitate the integration of world economies by opening the borders to the trade development while accelerating technological changes and maintaining the economic growth. Trade potential is defined as the trade that could be achieved at an optimum trade frontier with the open and frictionless trade possible through regional agreements based on the current level of trade, transport, and institutional technologies. Earlier studies have estimated the trade potential by using the gravity equation through OLS estimates as the potential trade. From the beginning of the gravity model of trade, the space is taken into account by considering the impact of distance variable and other relevant variables on the volume of trade, such as geographic contiguity, common language, and the common currency. However, these variables could not be satisfied alone if the aim is to consider the dependence on space. The Econometric literature suggests to model this phenomena with the appropriate spatial econometric models and methods.
The literature shows how, at an empirical level, the classical Gravity Model brings good results to explain the international trade. Since the gravity model has physical roots, the trade flow depends on the dimension of both the origin and the destination country as well as the distance between them. Recently, several studies have highlighted that an additional effect which should be taken into consideration is the spatial dependence. In the international trade, spatial dependence can be justified by the role of the third country effect. The so called third country effect is connected with two different phenomena: the location factor theory that fosters the spatial spillover effects and the persistence phenomena. For the first phenomena, it is asserted that if some structural changes happen in one country in a way that they affect its trade flow, they will affect the trade flow of the neighbors as well, thus, producing positive effects on the volume of flows. On the other side, the third country can foster persistence effect, which is based on the relative trade cost between countries i and j compared with the cost between i and k, where k is the third country. Assuming this phenomena, an increase in the competitiveness of the third country lowers its trade cost and, consequently, lowers the flow between the couple ij.
There are two econometric motivations for the use of spatial regression model that involves the spatial lag. The first motivation comes from viewing spatial dependence as a long-run equilibrium of an underlying spatio-temporal process; the second motivation shows that the omitted variables that exhibit the spatial dependence lead to a model with spatial lags of both the explanatory and the dependent variable. The first motivation results in a Spatially Autoregressive Model (SAR) that contains spatial lags of the dependent variable. The second econometric motivation leads us to a model with a spatial lag of both the explanatory and the dependent variables which is called Spatial Durbin Model (SDM). In this study, we modeled the country-to-country trade flow over the period from 2005 to 2014 for the Economic Cooperation Organization (ECO) using a dynamic spatial regression model. The sample was restricted to the 10 ECO countries for n=10 years, resulting in a n*n*T = 1000 observations. In order to choose between random versus fixed effect specification, a spatial Hausmann test was performed. This test highlights the strong preference for the fixed effect model. Also, we modified Wald test for groupwise heteroskedasticity in the fixed effect regression model and Durbin-Watson test for the Residual autocorrelation detection.
Results of SDM confirm the assumption of the effectiveness of spatial effects. In other words, there is a positive spatial relationship between the observations on the trade potential of ECO member countries.
The results shows that the sign in the basic components are similar to the existing literature. GDP of the origin as well as the destination country is significant, as predicted. Furthermore, the inverse distance has the predicted positive impact on the trade flow. Common language plays a positive role, thus, increasing the trade flow.
The results show a good fit of the spatial gravity model to the related data on the trade between ECO countries, hence, confirming the importance of the structural variables of the theoretical model through the presence of spatial dependence that motivates the choice of a SDM model with both the lagged dependent and the independent variable. This results in the confirmation of the theory relating to spillovers and locational factors. The results represent the importance of a common language, GDP origin, the destination countries, and the distance between the two countries and adjacency on trade flow between ECO member countries. Also, in this study spillovers are estimated by both the spatial autocorrelation coefficient and the indirect impact of the explanatory variables. The results shows significant spillover effects of trade and insignificant spillover effects of the explanatory variables.
Accordingly, select trade partners and new members from industrialized countries, with a GDP higher than the average of ECO members, is suggested.