In Mazandarn province, regional unemployment rates appear to vary widely. In the year 2006, in this province, unemployment rates were 10.85 percent. This disparity is widely in county level. For example, unemployment rate at Joybar and Savadkoh counties were 6.5 and 20.6 percent respectively. Because of regional differences in unemployment rate, geographical analyze is important.In this research, by using SPATIAL ECONOMETRICS models which is applied in SPATIAL autocorrelation and Iranian census data in the year 2006, we analyze the geographical distribution of unemployment in the 16 counties of Mazandaran province.On the basis of findings, there was positive SPATIAL autocorrelation phenomena in Mazandaran labor market at the county level. Counties marked by high unemployment rate, as well as those characterized by low unemployment rate, tended to be SPATIALly clustered, demonstrating the presence of ‘SPATIAL autocorrelation'.Also, we consider the spillover effect of county's shock on the others.

In 1988 professor Anslin provided a comprehensive review of SPATIAL ECONOMETRICS in his book entitled "SPATIAL ECONOMETRICS, Methods and Models". These techniques followed the main stream quantitative techniques in economic studies. However, it was claimed that these techniques were more adequate in regional and locational studies compared with the conventional ECONOMETRICS techniques. In studies where locational and SPATIAL aspects of the variables are significant, thus SPATIAL ECONOMETRICS techniques can be substituted with conventional methods. Therefore, in recent years SPATIAL ECONOMETRICS has been widely welcomed in regional sciences directly and indirectly. The main aim of this paper is to introduce the concept and subject of SPATIAL ECONOMETRICS to the persian users. It is also tried to introduce some of the most useful special ECONOMETRICS models and compare them with conventional models.

Researches in housing sector show that the effect of various economic factors on housing prices might be different in separate areas of a country and housing prices in different regions of the country have internal connections with each other. Modelling of these effects is done in the form of SPATIAL ECONOMETRICS. In this study, data related to 28 provinces of Iran during the period 2000 -2013 is used to estimate and compare the dynamic SPATIAL SDM panel models with SPATIAL SDM panel models and also to estimate the direct and indirect effects (space overflows) related to the explanatory variables in both the short and long term by using population SPATIAL weight matrix in Matlab software. In order to choose the best SPATIAL pattern consistent with the theoretical model of housing price determination, we have used Elhorst methodology and at every step, Likelihood ratio test (LR) and Lagrange multipliers tests (LM) are used to compare the SPATIAL patterns. We found out that dynamic SPATIAL model shows the best specification. By comparing the results of the dynamic SPATIAL panel models, lagged housing price variable and SPATIAL effects of this variable have a significant role in determining house prices. The results also show that only the SPATIAL effects of household spending variable have a significant effect on housing prices and other variables such as land price, construction costs, rental housing prices, have significant effect on housing prices in the provinces of Iran both directly and in the form of space overflow effects.

The aim of present study is to identify the convergence of productivity in the provinces of Iran from 2007 and 2010. In order to evaluate, the researcher used the absolute and conditional beta convergence. With respect to the importance of the neighborhood effect in the study, the SPATIAL economy method is used. The result shows that the absolute beta convergence has been approved and this coefficient has the numerical value 0.12.Thiscoefficientisstatistically significant. The conditional convergence coefficient is equal to 0.24, and the coefficient is statistically significant at the 1% level. The control variables in the conditional convergence included industrial diversification, industrial evenness, access to interstate road infrastructure, human capital. Industrial diversification and level of education have negative effect, and industrial evenness positive and access to the road infrastructure have positive effect on productivity convergence. Based on the results of the study it can be suggested that policy- makers and economic planners take more attention to the evenness industry based on the potential of each region.

On the theory, integration among countries that have common economic as well as political benefits, such as Persian Gulf Countries, may result in resource reallocation, an increase in products, trade and then economic welfare for members. This paper investigates the effect of trade integration on international trade flows among the members, using the trade gravity model. The contiguity effect must be considered because of SPATIAL dependence of the member countries. These countries have some common borders and therefore, SPATIAL dependence among them affects their trade flows. Also, the paper addresses the question of extent the contiguity factor can influence the intra-trade flows of the members. The estimation results show that the SPATIAL dependence hypothesis is confirmed in the model. Moreover, the coefficient of integration variable reveals the fact that trade flows among Persian Gulf countries are below potential level. Therefore, these countries should remove trade obstacles to benefit from potential trade as well as comparative advantages.  

In the second half of the twenty-first century, economic change, population growth and globalization were the main factors driving the deforestation in the South Asian countries. To identify the effects due to socioeconomic factors affecting deforestation in such countries, this study applied the SPATIAL ECONOMETRICS model based on data from 18 selected countries for the period between 2005 and 2015. The SPATIAL correlation tests were showing that ignoring the effects of SPATIAL correlation cause bias in results. The results of the model also confirmed the environmental Kuznets curve hypothesis for the selected countries with a turning point of $ 5, 107. Our findings illustrated that increasing GDP per capita in neighbouring countries through interregional mobility of inputs of production will increase deforestation in the target country. The increase in the exchange rate in neighbouring countries due to the increase in imports of forest products and the non-cutting of domestic forest resources will reduce deforestation in the target country. Increased population density and unemployment in neighbouring countries due to reduced job opportunities and increased migration to the target country, followed by increased demand for food and increased land demand, led to increased deforestation in the target country. Finally, increasing the human development index variable has reduced deforestation in the target country. However, changing this variable in neighbouring countries has not affected the deforestation of the target country. Therefore, in a world with increasing economic growth, it is suggested that to prevent deforestation by improving the human development index, eradicating the problem of unemployment, and eradicating poverty redouble efforts. As the results of this study showed, the population had a direct and significant effect on deforestation in selected countries. Due to the increase in population growth in different years, it is recommended that the population issue be given more attention by looking at the requirements of sustainable development to reduce environmental degradation, mainly deforestation. Because according to the results of this study, the lack of rapid population growth reduces deforestation in selected countries.

According to trade theories, economic integration results in increasing trade and income among trade partners. This paper tries to test the major factors affecting the exports of agricultural products in ECO members using SPATIAL econometric approach. For this purpose, the exports statistics of ECO members has been used in the form of panel data during 1992-2008. Agricultural exports function has been estimated using the Static (fixed and random effects) and Dynamic (generalized method of moments (GMM)) methods in panel data with classic and SPATIAL econometric approaches. The estimated results indicate the existence of SPATIAL dependence among the countries, so the using this estimation procedure is justified. GDP, Exchange rate and SPATIAL variables (such as proximity) have positive effects and Population has negative effect on agricultural exports. Finally, it is suggested that the estimation equations should consider the proximity between the countries and with the increase in the exchange rate and GDP, increase exports in order to provide the necessary basis. Population control policies may also apply.

Using SPATIAL ECONOMETRICS to investigate the factors affecting the share of cheese brands in the Mashhad market can improve the standard econometric degradation. In this research, we have been trying to select a model that considers SPATIAL communication between brands (with emphasis on diversity). The results of the SAC pattern estimated for the share of the Kalleh showed that the Kalleh diversity has a positive and significant relation with the share of the Kalleh, and the other variety of brands (Pegah and Sabah) has a negative and significant relationship. Also, the price of the Kalleh with the share of the Kalleh has a negative and significant relationship. The results of the SEM pattern estimated for Pegah share showed that Kalleh and Sabah diversity had a negative and significant relation with the share of Pegah cheese and Pegah diversity had a positive and significant relation with Pegah’ s share. The results of the SDM pattern estimated for Sabah showed Kalleh and Pegah variety have a negative and significant relation with the share of Sabah cheese and Sabah variety has a positive and significant relation with Sabah’ s share. The price of Kalleh has a negative and significant relationship with Sabah’ s share. Sabah also has a negative (statistically meaningless) relation with Sabah prices. Based on this research, it can be suggested that the brands of Kalah, Pegah and Sabah should increase the focus on cheese diversity in order to increase their share in Mashhad cheese market.

Undoubtedly, today the tourism industry is one of the most important sectors of the global economy that has been growing rapidly in world economic development. The result of this rapid growth has been the increase in annual growth rates in world GDP, exports, world trade, and services. The appropriate investment climate can sustain this industry. The investment climate is influenced by a set of factors related to legislative, regulatory, organizational, economic, social, political and other factors that determine the conditions of investment activity in a country, region or city. Therefore, this study examines the impact of tourism income on the investment climate in selected countries of the Middle East. Data were analyzed using the SPATIAL Durbin panel model over the period 2016–, 2006 for 15 selected countries in the Middle East. The results showed that there is a significant SPATIAL relationship among Middle Eastern countries. In other words, part of tourism revenue in the Middle East has been due to distance or proximity effects. Therefore, it is suggested to consider SPATIAL correlations between observations in estimating econometric models because if they are not included in the model, the results of biasing are unreliable.