spatial econometrics

Due to the importance of climate change on agricultural production and the dependence of yield on rainfall, the purpose of this article is to investigate effect of climatic variables such as temperature, rainfall, fertilizer and onion inputs on saffron yield in cities of Khorasan provinces during the years 1398-1380. For this purpose, using Ricardin model and mixed spatial autoregressive model (SAR), the effect of climate change in three climates: hot and dry, temperate and cold in the mentioned provinces was investigated. The results of the model in three climates showed that the amount of rainfall, fertilizer and onion, contrary to temperature, have a positive and significant effect on saffron yield and the significance of the spatial interruption coefficient of the dependent variable confirms the existence of spatial effects. According to the results of this study, it is necessary to increase the serious events of high temperature and decrease rainfall and reduce the yield of saffron in future periods and the undeniable role of saffron in livelihood, employment and income generation of farmers in the region.

Carbon dioxide emission is one of important challenges facing humanity, which has attracted the attention of many researchers and policymakers in recent years. The purpose of this study is investigating the factors influencing carbon dioxide emission. For achieving the purpose of paper spatial econometrics model and panel data of MENA countries are used over the period of 2000-2015. The results indicate that carbon dioxide emission in the MENA region countries have significant effect on surrounding countries. Also, the variables of energy consumption (0.01), economic globalization (0.134), industrialization (0.405) and urbanization (0.042) have positive and significant effect on carbon dioxide emission in the MENA region. The interaction among energy consumption and globalization (0.361), energy consumption and, industrialization (0.234) and urbanization (0.085) have a positive and significant effect on carbon dioxide emission. According to the results of this study, it is necessary that policymakers should not only focus on the national economic benefits but also consider the national and regional environmental benefits in policy making.

To date, researches have presented numerous models for measuring environmental efficiency; however, reports suggested that they have not been able to consider the increasing spatial impact of certain factors affecting the environmental efficiency of agricultural products and for the most part the results are not logical.

In this study, first the environmental efficiency of rapeseed in designated provinces of Iran during the years 2011 to 2016 was measured and to evaluate the environmental efficiency of the specific measurement model was used. Then, in this study, using a Spatial Durbin Model, the factors affecting the environmental efficiency of rapeseed farmers (due to the utilization of water resources and other climatic aspects) in certain provinces of Iran have been investigated.

The results of this study showed that the average environmental efficiency of the entire country is about 0.73 during the mentioned period, which has increased with the relative improvement of environmental efficiency each year and also has spatial spillover effects. Direct and indirect effects indicate that domestic water consumption, degree of openness, technological progress in agriculture and industrial structure have a significant impact on the environmental efficiency of Iranian rapeseed growers.

In this regard, the government and citizens should focus on solutions such as reducing pollution, saving domestic water consumption and transforming the industrial structure. In addition, managers should consider the spatial effects of these factors when designing government policies.

Provincial current and infrastructural budgets are the most important economic tools for public sector and can help to reduce regional inequalities and imbalances in Iran. despite the government's expanded role in Iran's economy, but for various reasons, such as access to oil revenues, certain principles of government in society and so on, the importance of the budget as one of the most important economic and social policy instruments are not known. In other words, due to the privileged position of planning and importance of budget in preparation and implementation of medium-term development programs, Budgeting is ineffective in Iran. Therefore, the process of preparation and implementation of the budget management has become a difficult and complex issue in public sector in the last half-century that imposes to the government. So, budgeting pattern is important for presenting provincial capital assets budgeting in that format.
Method and materials: considering that the way of allocation of funds to various sectors of the country, is related to a spatial relationship between regions, a strategy with the ability to measure local heterogeneity should have been applied. Therefore, in this study, the spatial econometrics method spatial Durbin model with the panel data has been employed. The geographic scope of this study includes all provinces and time scope contains 10 years (2005-2014). In this study, variables of provincial revenues, the share of service, industry, agriculture, and oil in GDP, intermediate consumption in economic activity, inflation rate, unemployment rate, gross domestic product per capita, population and province area as programming variables are used. Besides economic, demographic and geographic variables, political variables such as participation in the presidential election and the percentage of votes to elected president in each province have been added to the budget allocation pattern.
The unit root test results showed that all variable is stationary. Two methods are available for estimate the panel data. The first method is fixed effect model and the second method is random effect model. Results of Hausman test confirm that fixed effect model is better than random effect model. Results indicated that the variables of a share of service, industry, agriculture and oil sectors in GDP and gross domestic product per capita have statistically significant effect on an associated budget in provinces. This results illustrated that government approach in budget allocation is economic and according to the positive effect of these variables on attracting budget (except the share of service sector in GDP) can be stated that government in order to expand the production and greater use of the economic potential of provinces invest in areas where investment will lead to more production and economic development. These findings confirm that provinces with advance agriculture and industry sectors attract more budget in comparison with other provinces. The effects of provincial revenues approved in the law on the budget allocated for infrastructure in the region is significant and positive. The results showed a significant negative effect of inflation rate on the budget allocation. This finding is consistent with economic theory because with an increase in inflation rate or the consumer price index will be reduced economic growth of provinces. In fact, increase in inflation rate has a negative effect on the economic efficiency of each province and this leads to less budget allocated to provinces that have a high inflation rate. Variable of unemployment rate has no significant effect on the budget allocated to the provinces. Budget allocation regardless of the unemployment rate in the region indicates that the process of granting budget is based on efficiency criteria. Because the poor and less developed regions with higher the unemployment rates, less credit is given.
In general, the results indicated that government's approach for allocation of budgets in provinces is economic and based on programs. It is necessary to mention that government's approach to allocation of budgets in provinces is not merely a based program and policy-driven approach also had an impact on the budget allocations to the provinces, but these effects are not for province with a high percentage of votes to elected president. In fact, policy-driven approach to creating political-regional integration is used in the acquisition more votes. In other words, if taking into account indirect effects, it can be concluded that government is used application-driven approach to target provinces and policy-driven approach to neighboring provinces in the allocation of budget.

The groundwater resources in Hamedan-Bahar plain are threated by uncontrolled exploitation and overmining. So the underground water levels are depletion. The aim of this study is to analyze the welfare of farmers affected by excessive exploitation of these resources. Information collected in the field, through interviews and questionnaires completed by farmers in 2015. For this purpose, the estimation welfare function, measured the effect of reducing the groundwater level on the welfare of farmers. In this study, the effects of land adjacent to the welfare of farmers, estimated through spatial econometric approach. The correlation coefficient of the estimate showed that the use of spatial regression superior to the classical regression model. The results show that the annual welfare loss per meter groundwater level is for each farmer in wheat and potato 18754300 and 35672800 Rials, respectively. Thus, the losses to farmers, 5632235 Rials, and in the study area is 52 billion rials. Thus, decreased 2.6 percent of the per capita income of farmers. Therefore, considerable reduction in welfare and a continuation of this situation in the long term lead to reduced water availability and reducing the welfare of farmers. Therefore Recommended investment by governments at least reduced welfare, preservation and groundwater recharge. Also be customized to farmers who participate in watershed management projects designed by the government.

In this study the impact of climate variables such as precipitation and temperature fluctuations and seed، urea and phosphate fertilizers on the yield of maize was studied in three different climate zones of Iran. For this purpose، Ricardian and spatial econometric models were used. The results showed the severity of climate change fluctuations، in all three climates، has been enough to identify as systematical risk factors. The results showed that، the extreme heat in the growing season of September، and lack of precipitation during the growing season (October) in warm climate zone were the main factors which caused decline in maize yield. In moderate climate، overheating during growing season (August) and harvest (October) considered as systematical risk factors. Also in the cold climate، heat in growing and flowering seasons (June and August) and harvest season (November) had negative effect on crop yield.

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.