Rural Development
Shadali Tohidloo; gholamreza mojarradi
Abstract
Life expectancy shows having a better and more appropriate standard of living. As a result, Awareness of the above index in rural areas helps government officials and rural planners in decision making. The aim of this secondary data analysis research was to estimate and zoning of life expectancy in rural ...
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Life expectancy shows having a better and more appropriate standard of living. As a result, Awareness of the above index in rural areas helps government officials and rural planners in decision making. The aim of this secondary data analysis research was to estimate and zoning of life expectancy in rural areas of Iran in 2016. In the research method, based on the official secondary data of the country, the life expectancy table was created and life expectancy were calculated for the rural areas of the provinces of the country, then these areas were zoned using Arc GIS. Based on the results, Tehran province in terms of villagers’ life expectancy has the best location among all of provinces. The amount of this index in Tehran province was different from 74.60 for all of rural people to 74.71 for rural women and 74.50 years for rural men. The worst situation of villagers’ life expectancy in Iran was related to Sistan and Blochestan province, because, the amount of this index was for all villagers’ people 67.26 and for women 67.76 and finally for men 66.76 years. The highest life expectancy between all groups and provinces, related to Tehran province rural women’s with 74.71 years and the lowest was related to the rural men of Sistan and Baluchestan with 66.76 years. Women had more life expectancy than men in all provinces. Finally, the rural people of different provinces placed in three areas of good, moderate and weak in terms of life expectancy index. Planners and policymakers can take over the elimination of deficiencies and deficits in weak areas and improve life expectancy in other areas of the appropriate actions.
Rural Development
Ebrahim ghaed; Mohammadtaher Ahmadi Shadmehri; Habib Shirafkan lamso; Haniye Hossainzadeh
Abstract
The rural areas of Iran are known as the most important hubs for the production of agricultural products. Considering that income distribution has an effect on the level of poverty and economic well-being of rural people, knowing the factors affecting how income is distributed in the rural areas of the ...
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The rural areas of Iran are known as the most important hubs for the production of agricultural products. Considering that income distribution has an effect on the level of poverty and economic well-being of rural people, knowing the factors affecting how income is distributed in the rural areas of the country will be necessary to develop poverty alleviation policies. Identifying these factors will pave the way for appropriate measures in the first place to improve the pattern of rural income distribution and in the second place to reduce rural poverty in Iran. The purpose of this research is to investigate the effect of trade liberalization and the quality of human resources on the Gini coefficient in rural areas of Iran for the period of 1971-2020. For this analysis, Vector Autoregressive Model, Johansson-Juselius method Engel-Granger method and Vector Error Correction Model are used. The findings of the research based on The coefficient of the error correction method indicates that about 0.61 of the short-term imbalance is adjusted in each period to achieve the long-term equilibrium, and it can be said that in the long-term, a one percent increase in the variables. The quality of human resources (literacy rate of farmers) and the relative income of agriculture causes a decrease of 2.78 and 2.03 percent in the inequality of income distribution, respectively, and a one percent increase in the economic growth variables of the agricultural sector, the government's construction expenditures for agriculture, the index The degree of commercial openness and the ratio of agricultural investment cause an increase of 68%, 0.51%, 2.85% and 1.18% respectively in the inequality of income distribution, and among the types of variables mentioned, the effect of the index of the degree of commercial openness on the inequality of distribution income is more compared to other variables.
Geography and plan
Fatemeh Eshaghi Milasi; Beytollah Mahmoudi
Abstract
In achieving sustainable livelihoods in rural areas, the need for accurate and complete identification of factors affecting the process of formation and development of rural areas is necessary. In this regard, identification and evaluation of criteria and indicators of sustainable rural livelihoods can ...
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In achieving sustainable livelihoods in rural areas, the need for accurate and complete identification of factors affecting the process of formation and development of rural areas is necessary. In this regard, identification and evaluation of criteria and indicators of sustainable rural livelihoods can be promising. In this study, it has been tried to identify and evaluate the criteria and indicators of rural sustainable livelihood in the country through a comprehensive review of the library resources and existing records. For this purpose, factors influencing rural sustainable livelihood were formulated in the form of a group of criteria, and indicators for each criterion. In the next step by using the Delphi method and using normalized importance coefficient, the indices were screened. Based on the results, the economic criterion group with the highest Normalized Importance coefficient (0.338) was identified as the most important criterion group. Two income and cost and water resources criteria with normalized importance coefficient 0.720 and 0.070 are more important than the other criteria, and then the employment and health of the society criteria are at the next levels. Among the indicators of sustainable livelihoods, household income index is ranked first with the normalized importance coefficient 0.0084. And two indicators of assets and household expenses are ranked second with the same importance coefficient (0.0081).
