Artikel

Agricultural energy demand modeling in Iran: Approaching to a more sustainable situation

Energy has been heavily subsidized in Iranian economy for decades. Due to low oil prices, and, thus, budget limit, fossil fuel prices are under gradual liberalization. This will result in higher cost of production in all fuel consuming activities including agriculture. So it seems that farmers will plan to substitute fossil fuels by non-fossil alternatives. This study aims at modeling and prediction of energy demand (as a key factor of production) in Iranian agriculture. Box-Jenkins methodology is applied to model agricultural consumption of four major sources of energy including: gasoline, kerosene, gasoil and electricity for the period spanning from 1988 to 2014. Also same data are predicted for 2015-2026 in order to check model adequacy and provide information regarding status of energy demand in Iranian agriculture in the future. Main results indicate a downward trend in consumption of four energy types except electricity which is predicted to go up. This implies that, as far as energy consumption is concerned, Iranian agriculture is approaching to a more sustainable situation. Rearrangement of fuel price support policy from nonrenewable to renewable sources and provision of more governmental support for switching to lower-carbon and environment-friendly energy sources is recommended.

Sprache
Englisch

Erschienen in
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 4 ; Year: 2018 ; Pages: 260-265 ; Amsterdam: Elsevier

Klassifikation
Wirtschaft
Thema
Agriculture
BJ methodology
Energy consumption
Iran
Modeling

Ereignis
Geistige Schöpfung
(wer)
Farajian, Leila
Moghaddasi, Reza
Hosseini, Safdar
Ereignis
Veröffentlichung
(wer)
Elsevier
(wo)
Amsterdam
(wann)
2018

DOI
doi:10.1016/j.egyr.2018.03.002
Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Farajian, Leila
  • Moghaddasi, Reza
  • Hosseini, Safdar
  • Elsevier

Entstanden

  • 2018

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