An Estimation of Natural Gas Demand in Household Sector of Iran; the Structural Time Series Approach
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Sun, Mei & Wang, Xiaofang & Chen, Ying & Tian, Lixin, 2011. "Energy resources demand-supply system analysis and empirical research based on non-linear approach," Energy, Elsevier, vol. 36(9), pages 5460-5465.
- Majid Ahmadian & Mona Chitnis & Lester C. Hunt, 2007. "Gasoline demand, pricing policy and social welfare in the Islamic Republic of Iran," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 31(2), pages 105-124, June.
- Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
- Dongfeng Chang & Apostolos Serletis, 2014.
"The Demand For Gasoline: Evidence From Household Survey Data,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 291-313, March.
- Dongfeng (Karen) Chang & Apostolos Serletis, "undated". "The Demand for Gasoline: Evidence from Household Survey Data," Working Papers 2012-10, Department of Economics, University of Calgary.
- Azadeh, A. & Asadzadeh, S.M. & Ghanbari, A., 2010. "An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments," Energy Policy, Elsevier, vol. 38(3), pages 1529-1536, March.
- Sun, Mei & Zhang, Pei-Pei & Shan, Tian-Hua & Fang, Cui-Cui & Wang, Xiao-Fang & Tian, Li-Xin, 2012. "Research on the evolution model of an energy supply–demand network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(19), pages 4506-4516.
- Yoo, Seung-Hoon & Lim, Hea-Jin & Kwak, Seung-Jun, 2009. "Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias," Applied Energy, Elsevier, vol. 86(4), pages 460-465, April.
- Athukorala, P.P.A Wasantha & Wilson, Clevo, 2010. "Estimating short and long-term residential demand for electricity: New evidence from Sri Lanka," Energy Economics, Elsevier, vol. 32(Supplemen), pages 34-40, September.
- Payne, James E. & Loomis, David G. & Wilson, Renardo, 2011. "Residential Natural Gas Demand in Illinois: Evidence from the ARDL Bounds Testing Approach," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 41(2), pages 1-10.
- repec:ags:jrapmc:133220 is not listed on IDEAS
- Majid Ahmadian & Mona Chitnis & Lester C Hunt, 2007. "Gasoline Demand, Pricing Policy and Social Welfare in Iran," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 117, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
- Murata, Akinobu & Kondou, Yasuhiko & Hailin, Mu & Weisheng, Zhou, 2008. "Electricity demand in the Chinese urban household-sector," Applied Energy, Elsevier, vol. 85(12), pages 1113-1125, December.
- Aydinalp-Koksal, Merih & Ugursal, V. Ismet, 2008. "Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector," Applied Energy, Elsevier, vol. 85(4), pages 271-296, April.
- Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2009. "Energy demand models for policy formulation : a comparative study of energy demand models," Policy Research Working Paper Series 4866, The World Bank.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Potočnik, Primož & Soldo, Božidar & Šimunović, Goran & Šarić, Tomislav & Jeromen, Andrej & Govekar, Edvard, 2014. "Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia," Applied Energy, Elsevier, vol. 129(C), pages 94-103.
- Jean Gaston Tamba & Salom Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouand l & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
- Sen, Doruk & Günay, M. Erdem & Tunç, K.M. Murat, 2019. "Forecasting annual natural gas consumption using socio-economic indicators for making future policies," Energy, Elsevier, vol. 173(C), pages 1106-1118.
- Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
- Khan, Muhammad Arshad, 2015. "Modelling and forecasting the demand for natural gas in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1145-1159.
- Burke, Paul J. & Yang, Hewen, 2016.
"The price and income elasticities of natural gas demand: International evidence,"
Energy Economics, Elsevier, vol. 59(C), pages 466-474.
- Paul J Burke & Hewen Yang, 2016. "The price and income elasticities of natural gas demand: International evidence," Departmental Working Papers 2016-14, The Australian National University, Arndt-Corden Department of Economics.
- Raghoo, Pravesh & Surroop, Dinesh, 2020. "Price and income elasticities of oil demand in Mauritius: An empirical analysis using cointegration method," Energy Policy, Elsevier, vol. 140(C).
- Wadud, Zia & Dey, Himadri S. & Kabir, Md. Ashfanoor & Khan, Shahidul I., 2011. "Modeling and forecasting natural gas demand in Bangladesh," Energy Policy, Elsevier, vol. 39(11), pages 7372-7380.
- Azadeh, A. & Babazadeh, R. & Asadzadeh, S.M., 2013. "Optimum estimation and forecasting of renewable energy consumption by artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 605-612.
- Aldubyan, Mohammad & Gasim, Anwar, 2021.
"Energy price reform in Saudi Arabia: Modeling the economic and environmental impacts and understanding the demand response,"
Energy Policy, Elsevier, vol. 148(PB).
- Mohammad Al Dubyan & Anwar Gasim, 2020. "Energy Price Reform in Saudi Arabia: Modeling the Economic and Environmental Impact and Understanding the Demand Response," Discussion Papers ks--2020-dp12, King Abdullah Petroleum Studies and Research Center.
- Jumah Ahmad Alzyadat, 2022. "The Price and Income Elasticity of Demand for Natural Gas Consumption in Saudi Arabia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 357-363, November.
- Di Leo, Senatro & Caramuta, Pietro & Curci, Paola & Cosmi, Carmelina, 2020. "Regression analysis for energy demand projection: An application to TIMES-Basilicata and TIMES-Italy energy models," Energy, Elsevier, vol. 196(C).
- Azadeh, A. & Asadzadeh, S.M. & Mirseraji, G.H. & Saberi, M., 2015. "An emotional learning-neuro-fuzzy inference approach for optimum training and forecasting of gas consumption estimation models with cognitive data," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 47-63.
- Athukorala, Wasantha & Wilson, Clevo & Managi, Shunsuke & Karunarathna, Muditha, 2019. "Household demand for electricity: The role of market distortions and prices in competition policy," Energy Policy, Elsevier, vol. 134(C).
- Atalla, Tarek N. & Gasim, Anwar A. & Hunt, Lester C., 2018. "Gasoline demand, pricing policy, and social welfare in Saudi Arabia: A quantitative analysis," Energy Policy, Elsevier, vol. 114(C), pages 123-133.
- Aliyu Barde Abdullahi, 2014. "Modeling Petroleum Product Demand in Nigeria Using Structural Time Series Model (STSM) Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 427-441.
- Halim Tatli, 2019. "Factors affecting industrial coal demand in Turkey," Energy & Environment, , vol. 30(6), pages 1027-1048, September.
- Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
- Ju-Hee Kim & Byoung-Soh Hwang & Seung-Hoon Yoo, 2022. "Estimating the Demand Function for Residential City Gas in South Korea: Findings from a Price Sensitivity Measurement Experiment," Sustainability, MDPI, vol. 14(12), pages 1-13, June.
- Misconel, S. & Zimmermann, F. & Mikurda, J. & Möst, D. & Kunze, R. & Gnann, T. & Kühnbach, M. & Speth, D. & Pelka, S. & Yu, S., 2024. "Model coupling and comparison on optimal load shifting of battery electric vehicles and heat pumps focusing on generation adequacy," Energy, Elsevier, vol. 305(C).
More about this item
Keywords
Gas Demand; Household Sector; Structural Time Series; Kalman Filter;All these keywords.
JEL classification:
- Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
- D19 - Microeconomics - - Household Behavior - - - Other
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CWA-2015-10-10 (Central and Western Asia)
- NEP-ENE-2015-10-10 (Energy Economics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sek:iacpro:2804383. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klara Cermakova (email available below). General contact details of provider: https://iises.net/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.