IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v31y2010i4p111-136.html

Stochastic Trends and Technical Change: The Case of Energy Consumption in the British Industrial and Domestic Sectors

Author

Listed:
  • Paolo Agnolucci

Abstract

This paper estimates energy demand in the British domestic and industrial sectors and analyzes the extent to which energy-saving technological change is exogenous, or induced by the energy price. The paper implements models with a linear trend, models making use of the price decomposition of Dargay and Gately (1995a) and the Structural Time Series Models (STSMs) of Harvey (1989). Stochastic trends have been found to be rather important while in neither of the sectors assessed in this study could the hypothesis of symmetric price effects be rejected. Following Hunt and Judge (2005), stochastic trend and asymmetric price effects are found to be substitutes in the industrial sector. In particular we conclude that asymmetric price effects can substitute for the slope in the stochastic trend. Finally, energy consumption in the industrial sector is strongly influenced by price while the effect of price in the domestic sector is markedly smaller.

Suggested Citation

  • Paolo Agnolucci, 2010. "Stochastic Trends and Technical Change: The Case of Energy Consumption in the British Industrial and Domestic Sectors," The Energy Journal, , vol. 31(4), pages 111-136, October.
    • Handle: RePEc:sae:enejou:v:31:y:2010:i:4:p:111-136
    DOI: 10.5547/ISSN0195-6574-EJ-Vol31-No4-5
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/ISSN0195-6574-EJ-Vol31-No4-5
    Download Restriction: no
    File URL: https://libkey.io/10.5547/ISSN0195-6574-EJ-Vol31-No4-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    2. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
    3. repec:aen:journl:2005v26-02-a01 is not listed on IDEAS
    4. repec:aen:journl:1992v13-04-a10 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    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.
    1. Adom, Philip Kofi & Bekoe, William, 2012. "Conditional dynamic forecast of electrical energy consumption requirements in Ghana by 2020: A comparison of ARDL and PAM," Energy, Elsevier, vol. 44(1), pages 367-380.
    2. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    3. Brainerd, Elizabeth & Siegler, Mark V, 2003. "The Economic Effects of the 1918 Influenza Epidemic," CEPR Discussion Papers 3791, Centre for Economic Policy Research.
    4. R Burger & S du Plessis, 2011. "Examining the Robustness of Competing Explanations of Slow Growth in African Countries," Studies in Economics and Econometrics, Taylor & Francis Journals, vol. 35(3), pages 21-47, December.
    5. Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.
    6. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    7. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    8. Zhang, Lin, 2017. "Correcting the uneven burden sharing of emission reduction across provinces in China," Energy Economics, Elsevier, vol. 64(C), pages 335-345.
    9. David F. Hendry & Grayham E. Mizon, 2016. "Improving the teaching of econometrics," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170096-117, December.
    10. Parigi, Giuseppe & Golinelli, Roberto, 2005. "Short-Run Italian GDP Forecasting and Real-Time Data," CEPR Discussion Papers 5302, Centre for Economic Policy Research.
    11. George Kapetanios, 2005. "Variable Selection using Non-Standard Optimisation of Information Criteria," Working Papers 533, Queen Mary University of London, School of Economics and Finance.
    12. Bianchi, Robert J. & Drew, Michael E. & Fan, John Hua, 2016. "Commodities momentum: A behavioral perspective," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 133-150.
    13. Zamanipour, Behzad & Ghadaksaz, Hesam & Keppo, Ilkka & Saboohi, Yadollah, 2023. "Electricity supply and demand dynamics in Iran considering climate change-induced stresses," Energy, Elsevier, vol. 263(PE).
    14. Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting the French index of industrial production: A comparison from bridge and factor models," Economic Modelling, Elsevier, vol. 29(6), pages 2174-2182.
    15. Cáceres, Neila & Malone, Samuel W., 2015. "Optimal Weather Conditions, Economic Growth, and Political Transitions," World Development, Elsevier, vol. 66(C), pages 16-30.
    16. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    17. Ishmael Ackah, 2014. "Determinants of natural gas demand in Ghana," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(3), pages 272-295, September.
    18. Becker William & Paruolo Paolo & Saltelli Andrea, 2021. "Variable Selection in Regression Models Using Global Sensitivity Analysis," Journal of Time Series Econometrics, De Gruyter, vol. 13(2), pages 187-233, July.
    19. Joanne Evans & Massimo Filippini & Lester C Hunt, 2011. "Measuring energy efficiency and its contribution towards meeting CO2 targets: estimates for 29 OECD countries," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 135, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    20. Benjamin Wirth & Andreas Mense, 2014. "Flat Prices, Cell Phone Base Stations, and Network Structure," ERSA conference papers ersa14p1552, European Regional Science Association.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    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:sae:enejou:v:31:y:2010:i:4:p:111-136. 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: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.