جستجوی مقالات مرتبط با کلیدواژه « اقتصادسنجی فضایی » در نشریات گروه « اقتصاد کشاورزی »

Iran is as one of the largest producers and exporters of pistachio in world markets. Considering that the export of this commodity is one of the main sources of foreign exchange earnings and has an important role in reducing the government's general budget dependence on oil revenues, identifying the factors affecting on pistachio exports to world markets is essential and it can lead to the improvement of the country's position in the global pistachio market. Institutional conditions are the factors affecting on the export of goods, including pistachio from Iran to world markets.

This paper examines the effect of institutions on Iranian pistachio exports to Asian blocs using the spatial econometric method and Mixed Regressive-Spatial Autoregressive Model. The research pattern is a regression model with panel data during the time period 2000-2015 from Iranian trade with Asian blocs.

The results of model estimation are shown International Country Risk Guide (ICRG) variable as an indicator of institutions has a positive and significant effect on Iranian pistachio exports to Asian blocs.

The International Country Risk Guide index has three types of political, financial and economic risk of the country, according to the findings of the article as one of the most important obstacles to the expansion of investment and pistachio trade in Iran. Reducing this risk brings political, financial and economic stability will increase Iranian pistachio exports.

This study aimed at exploring the spatial effects of agricultural sustainability on food security of urban households in Iran over the period of 2005-15. For this purpose, first, the overall level of agricultural sustainability was calculated using a combination of agricultural sustainability and weighting indicators based on Analytic Hierarchy Process (AHP) method. Then, the household food security index (AHFSI) was used to determine the food security of households in urban areas. Finally, the effectiveness of agricultural sustainability on food security of urban households while other effective factors in place was examined using the mixed Spatial Autoregressive (SAR) model. The results of the model indicated a positive and significant effect of agricultural sustainability on food security in urban households, and the significance of the dependent spatial interruption coefficient confirmed the existence of spatial effects. So, the results of calculating the direct and indirect effects of agricultural sustainability index on the food security of each province and neighboring provinces were positive and significant. These results indicated the intra- and inter-provincial overflows. Therefore, it is imperative for policymakers of the agricultural sector to invest in production infrastructure such as seeds, fertilizers and agricultural practices with a focus on enhancing sustainable production as a prerequisite for the establishment of sustainable food security.

Agriculture and natural resources have a mutual relationship with each other. The purpose of this study was to evaluate prior and posterior relationship between natural resources and agricultural development. We studied the relationship between the consumption of water and agricultural value added per capita income in order to obtain the prior relationship, and assessed the relationship between carbon dioxide emissions and per capita income of the Iran’s agricultural sector in order to obtain posterior relationship. To test these relationships, the Kuznets theory is used. Results showed that there was an inverted U relationship between per capita income and water consumption and carbon dioxide emissions. Also, spatial estimation showed that both water consumption and CO2 emissions in agricultural sector had a direct relationship with the value of these two variables in the neighboring areas. Since the environmental Kuznets curve can be applied to both water consumption and CO2 emissions in agricultural sector, development and growth of agriculture in the country can lead to controlled CO2 emissions and water consumption in this sector. Overall, in order to sustain this growth, the continued investment in increasing productivity of energy and water inputs in agricultural sector is recommended.

This study aims to determine the most effective estimate of hedonic model for pricing agricultural land in Sanandaj Central Township. The necessary data obtained through completing 124 questionnaires and applying a classified random sampling method. The results showed that the estimation made by spatial econometric method in terms of R square and percentage of significant coefficients was more accurate. Furthermore، the effect of spatial dependent variable on land price was positive and significant. Finally، it is recommended to utilize spatial econometric model for hedonic valuation of agricultural land.

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.