Iran's provinces have experienced high inflationary pressures over the past few decades. This paper models the dynamics of inflation in terms of spatial effects between Iranian provinces using the hybrid Phillips New Keynesian Curve during the period (1392-1380). The results show that, the Phillips Keynesian curve is suitable for investigating the dynamics of inflation in Iran's provinces. Findings indicate that provinces focus on setting prices of their goods based on a combination of forward looking and backward looking rules, and that forward looking behaviors will have a stronger effect on the rate of inflation in the current period. Also in each province, the output gap as representative of the actual variables has an effect on the inflation rate of its current period. Finally, considering the significance of spatial auto-correlation between Iran's provinces, output gap, expected and lagged inflation rates in adjacent provinces have negative effects on the current inflation rate of the neighboring provinces.

One of the theoretical results of Solow-Swan neoclassical growth model is the convergence of per capita GDP in different regions. Conditional convergence model, in addition to the initial per capita GDP, concerns other variables that can affect long-term growth in areas under consideration. This study is to examine the disincentive role of crime in the establishment of the convergence of real per capita GDP among Iranian provinces (1379 to 1392). Conditional beta convergence and spatial econometric used to check integration. Crime index is calculated using TOPSIS method. The results show that the convergence of growth, though slow, is established. Crime index has negative and non-significant impact on the integration. ICT and human capital variables (education and health) have a positive impact on the province's average growth. Also negative sign for the spatial coefficient of dependent variable show that the concentration of economic power in one area for growth, reduces the power generated growth in adjacent areas.

The purpose of this paper is to study empirically the convergence of democracy in developing countries. For this purpose, the spatial econometric and panel data approach was used during the period 1990-2014. The results show that the geographic proximity of countries has a positive and significant effect on democracy. In other words, on average, the increase in the level of democracy in the geographic neighbors has led to a 6 percent increase in democracy, which reflects the political influence of each other. Also, foreign aids does not have a significant effect on the spread of democracy in developing countries. In general, the spatial effects of democracy or the theory of diffusion in developing countries are confirmed. Therefore, According to the theory of diffusion and convergence of democracy, increase or decrease in democracy in a country can increase or decrease democracy in neighboring countries.

Even though development of industry increases economic growth, it reduces the quality of the environment due to higher pollution coefficients. Therefore, creating an optimal structure for the industry to reduce the negative externalities is of great importance. Accordingly, by using the statistical evidence of selected countries for the period 2010-2017, and applying a spatial econometrics approach, this study investigates the effect of industrial agglomeration on entropy index as pollution agglomeration. The results show that there are spatial effects of pollutant emissions among the studied countries,also, the agglomeration of the industry reduces the agglomeration of pollutants due to the advantage of the spillover effect of knowledge and technology, and matching skills with jobs. In addition, the intensity of energy consumption increases the agglomeration of pollution. Moreover, regarding the relationship between GDP and pollution agglomeration, the Kuznets curve is confirmed indicating a nonlinear relationship between the two variables. Ultimately, the openness of economy in neighboring countries leads to reduction in pollution agglomeration, due to the effects of spatial spillover.

This paper aims to model total electricity demand (incremental) in order to estimate price and income elasticities using provincial data and the spatial panel data method. Electricity demand at the province level is influenced by climatic zones, which can be divided into temperate, cold and sub-tropical. This paper uses time series data for electricity demand in Iran’ s 28 provinces, taking into account climatic factors as well as income and price elasticities. We use Elhorst methodology and likelihood-ratio test to compare spatial patterns in order to select the best method compatible with the theoretical model. The results indicate a price elasticity of electricity demand (-0. 08), cross elasticity of electricity demand (-0. 6565), income elasticity (0. 11) and elasticity of demand to temperature changes (1. 9). In other words, electricity demand is minimally sensitive to changes in electricity prices and natural gas prices and income, but sensitive to changes in temperature (elastic). Our cross elasticities and income elasticity indicate that electricity and natural gas are substitutes for each other and can be considered essential goods based on their income elasticity.

The objective of this study was to investigate the factors affecting poverty and to determine poverty map of Fars Province urban areas using spatial econometrics approach. The dataset were obtained throughout 320 urban households participated in household expenditure survey of 2005. Moran's I value for poverty was -0.2125, indicating negative spatial autocorrelation. Moran's scattering graph also showed that most of townships and their neighbors may be placed into poverty subgroups of high-low and low-high. Results revealed that variables of family size, household head gender, percentage of household owning housing and type of employment have significant effects on poverty incidence. Results indicated that the spatial lag and error models have considerable improvement over OLS model.

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.

In recent years, with excessive extraction of groundwater resources, Hamedan-Bahar-plain’ s ground water level dropped severely. So it is important to apply appropriate management strategy for the optimal utilization of this resource. In the economic management of water resources, the main issue is a balance between supply and demand for water. In creating this balance, an important role is the economic value of water, like the prices of other inputs are. For this reason, to keep the sustainability of water resources in agriculture, water pricing method is used as an indirect method. The aim of this study was to estimate the economic value of water using spatial econometric approach. Because of the relationship between farms and groundwater resources, this study tried to answer the question of how this relationship affects the welfare of farmers. By accepting this issue, the use of spatial econometric approach is recommended. The correlation coefficient of the estimate showed that the use of spatial regression is superior to the classical regression model. The required data in this study were collected through field research and a questionnaire to farmers in 2016. The results show that the real price of water in potato production is 2040 rials per cubic meter. Therefore, controlling water consumption and balancing of supply and demand for water can be generated from the existing price gap for water pricing policies.

In recent years, the desire to create a monetary union at the international level has increased. According to economic theory, the formation of monetary unions and the adoption of a common currency encourages economic integration, controls monetary policy instability, reduces transaction costs in trade and can lead to an increase in real income through boosting trade. The proximity and neighborhoods of the countries have been introduced as one of the factors affecting trade and the formation of monetary unions. In this study, given the importance of this issue, the effect of the monetary union on bilateral trade has been investigated using the spatial econometric approach during the period of 2000-2015 for a selected countries of the world. The results of the research show that the effect of common currency on bilateral trade is positive, whose trade will lead to economic growth in the countries. Also, the spatial effects of the shared money and geographical distance have been confirmed. Hence, it can be concluded that countries that are adjacent to each other or have common currency would strengthen the trade between themselves, by creating monetary unions. Also, the results of the spatial econometric approach show that GDP and Trade openness index (in three spatial matrices) and real exchange rate (in the common currency matrix and the modified currency matrix) had a positive and significant effect on bilateral trade between the studied countries.

Alignment of industrial development and differences in the regional development has increased the importance of investigation of spatial aspects and of the main drivers in regional development that it is a factor in the spread of inequalities in the regions of each country. This study aimed to assess factors affecting regional development using spatial econometric model and it analyze the regional development problem in the provinces of Iran. For this purpose, the two-sided neighborhood matrix and spatial error model are used for 30 provinces during 1392. The results indicated a significant influence of political factors on increase or decrease the level of regional development disparities between provinces, particularly fiscal policy. Industrial investment as one of the important variables in the development and structural transition has a significant positive influence on regional development and because of the impact that rising income levels, backward and forward linkages and value chain can be a factor convergence is affecting regional development.