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Agriculture, climate change and sustainability in Iran: Application of numerical taxonomy method and Panel-VAR | ||
Caspian Journal of Environmental Sciences | ||
دوره 20، شماره 1، فروردین 2022، صفحه 61-75 اصل مقاله (1.07 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22124/cjes.2022.5393 | ||
نویسندگان | ||
Seyed Mehdi Hosseini؛ Seyed Nematollah Moosavi* ؛ Bahaoddin Najafi | ||
Department of Economics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran. | ||
چکیده | ||
The purpose of the paper is twofold. Firstly, through the Taxonomic Method, we construct a composite indicator, called the Index of Sustainable (IS), and analyze the provinces of Iran from 2011 to 2018, according to 9 variables. Secondly, the Granger-causality test for panel data is implemented in order to verify the causal relationship among the IS, climate change and agricultural production. In other words, we test which of the three analyzed variables turns out to be the causetive variable and which, instead, turns out to be the effect variable. This analysis provides a wide overview on how the provinces rank according to the IS and its three crucial pillars, i.e. environmental, economic and social. Moreover, important causality relationships among the IS, climate changes (approximated by mean annual temperature and mean annual precipitation) and agricultural production (approximated by wheat and barley production) are identified. The results showed that Khuzestan, Isfahan and Fars provinces have the highest average sustainability index during 2011-2018. Generally, the provinces which are in a better position in terms of agricultural and industrial production, are also in a more favorable position in terms of sustainability than other provinces. The results also showed that there is a significant causal relationship between agricultural productions, climatic variables of temperature, precipitation and stability index among the studied provinces. | ||
کلیدواژهها | ||
Sustainability, Agriculture, Climate change؛ Taxonomic method؛ Panel VAR | ||
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