Forecasting Natural Gas: A Literature Survey

Jean Gaston Tamba, Salom Ndjakomo Essiane, Emmanuel Flavian Sapnken, Francis Djanna Koffi, Jean Luc Nsouand L, Bozidar Soldo and Donatien Njomo
Additional contact information
Jean Gaston Tamba: Department of Thermal and Energy Engineering, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon
Salom Ndjakomo Essiane: Laboratory of Technologies and Applied Science, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,
Emmanuel Flavian Sapnken: Laboratory of Technologies and Applied Science, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,
Francis Djanna Koffi: Department of Thermal and Energy Engineering, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,
Jean Luc Nsouand L: Department of Renewable Energy, Higher Institute of the Sahel, University of Maroua, PO Box 46, Maroua, Cameroon
Bozidar Soldo: HEP-Plin Ltd., Cara Hadrijana 7, HR-31000 Osijek, Croatia,
Donatien Njomo: Environmental Energy Technologies Laboratory, University of Yaound I, PO Box 812, Yaound , Cameroon.

International Journal of Energy Economics and Policy, 2018, vol. 8, issue 3, 216-249

Abstract: This work presents a state-of-the-art survey of published papers that forecast natural gas production, consumption or demand, prices and income elasticity, market volatility and hike in prices. New models and techniques that have recently been applied in the field of natural gas forecasting have discussed with highlights on various methodologies, their specifics, data type, data size, data source, results and conclusions. Moreover, we undertook the difficult task of classifying existing models that have been applied in this field by giving their performance for instance. Our objective is to provide a synthesis of published papers in the field of natural gas forecasting, insights on modeling issues to achieve usable results, and the future research directions. This work will help future researchers in the area of forecasting no matter the methodological approach and nature of energy source used.

Keywords: Forecasting natural gas; Existing forecasting models; Models categorization. (search for similar items in EconPapers)
JEL-codes: C53 Q4 Q47 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2018-03-28

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