IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v48y2015icp168-177.html
   My bibliography  Save this article

Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing

Author

Listed:
  • Hung, Ming-Feng
  • Huang, Tai-Hsin

Abstract

This paper studies the dynamic demand for residential electricity in Taiwan employing a monthly panel data set, composed of 19 counties and spanning the period from 2007:01 to 2013:12. The partial adjustment model used addresses the endogeneity of the electricity price that results from the increasing-block pricing. The estimated results show that there is a significant seasonal difference in the demand for electricity between the summer and non-summer periods. Both the adjustment speed and own price elasticity during the summer months are found to be lower than those in the non-summer months due to the hot weather in summer. It is easier for consumers to adjust their electricity consumption in response to the changes in electricity pricing during the non-summer time. The estimated inelastic short-run and long-run income effects show that electricity is a necessity for consumers. Moreover, the controversial electricity-conservation policies are found to be ineffective measures for reducing electricity consumption in Taiwan.

Suggested Citation

  • Hung, Ming-Feng & Huang, Tai-Hsin, 2015. "Dynamic demand for residential electricity in Taiwan under seasonality and increasing-block pricing," Energy Economics, Elsevier, vol. 48(C), pages 168-177.
  • Handle: RePEc:eee:eneeco:v:48:y:2015:i:c:p:168-177
    DOI: 10.1016/j.eneco.2015.01.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988315000249
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2015.01.010?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Loayza, Norman V. & Ranciere, Romain, 2006. "Financial Development, Financial Fragility, and Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 1051-1076, June.
    2. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    3. Dinusha Dharmaratna & Edwyna Harris, 2012. "Estimating Residential Water Demand Using the Stone-Geary Functional Form: The Case of Sri Lanka," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2283-2299, June.
    4. Flannery, Mark J. & Hankins, Kristine Watson, 2013. "Estimating dynamic panel models in corporate finance," Journal of Corporate Finance, Elsevier, vol. 19(C), pages 1-19.
    5. R. Bruce Billings, 1982. "Specification of Block Rate Price Variables in Demand Models," Land Economics, University of Wisconsin Press, vol. 58(3), pages 386-394.
    6. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential consumption of gas and electricity in the U.S.: The role of prices and income," Energy Economics, Elsevier, vol. 33(5), pages 870-881, September.
    7. Jung, Tae Yong, 1993. "Ordered logit model for residential electricity demand in Korea," Energy Economics, Elsevier, vol. 15(3), pages 205-209, July.
    8. Roberto Martinez-Espineira & Celine Nauges, 2004. "Is all domestic water consumption sensitive to price control?," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1697-1703.
    9. Paul, Anthony & Myers, Erica & Palmer, Karen, 2009. "A Partial Adjustment Model of U.S. Electricity Demand by Region, Season, and Sector," RFF Working Paper Series dp-08-50, Resources for the Future.
    10. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    11. Nakajima, Tadahiro & Hamori, Shigeyuki, 2010. "Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States," Energy Policy, Elsevier, vol. 38(5), pages 2470-2476, May.
    12. Ziramba, Emmanuel, 2008. "The demand for residential electricity in South Africa," Energy Policy, Elsevier, vol. 36(9), pages 3460-3466, September.
    13. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    14. Sa'ad, Suleiman, 2009. "Electricity demand for South Korean residential sector," Energy Policy, Elsevier, vol. 37(12), pages 5469-5474, December.
    15. Kamerschen, David R. & Porter, David V., 2004. "The demand for residential, industrial and total electricity, 1973-1998," Energy Economics, Elsevier, vol. 26(1), pages 87-100, January.
    16. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    17. Nakajima, Tadahiro, 2010. "The residential demand for electricity in Japan: An examination using empirical panel analysis techniques," Journal of Asian Economics, Elsevier, vol. 21(4), pages 412-420, August.
    18. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    19. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
    20. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    21. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential Consumption of Gas and Electricity in the U.S.: The Role of Prices and Income," Sustainable Development Papers 99637, Fondazione Eni Enrico Mattei (FEEM).
    22. Michael Parti & Cynthia Parti, 1980. "The Total and Appliance-Specific Conditional Demand for Electricity in the Household Sector," Bell Journal of Economics, The RAND Corporation, vol. 11(1), pages 309-321, Spring.
    23. Edward F. Blackburne III & Mark W. Frank, 2007. "Estimation of nonstationary heterogeneous panels," Stata Journal, StataCorp LP, vol. 7(2), pages 197-208, June.
    24. Julie A. Hewitt & W. Michael Hanemann, 1995. "A Discrete/Continuous Choice Approach to Residential Water Demand under Block Rate Pricing," Land Economics, University of Wisconsin Press, vol. 71(2), pages 173-192.
    25. Yoo, Seung-Hoon & Lee, Joo Suk & Kwak, Seung-Jun, 2007. "Estimation of residential electricity demand function in Seoul by correction for sample selection bias," Energy Policy, Elsevier, vol. 35(11), pages 5702-5707, November.
    26. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    27. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    28. Hondroyiannis, George, 2004. "Estimating residential demand for electricity in Greece," Energy Economics, Elsevier, vol. 26(3), pages 319-334, May.
    29. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    30. Murray, Michael P, et al, 1978. "The Demand for Electricity in Virginia," The Review of Economics and Statistics, MIT Press, vol. 60(4), pages 585-600, November.
    31. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    32. Bose, Ranjan Kumar & Shukla, Megha, 1999. "Elasticities of electricity demand in India," Energy Policy, Elsevier, vol. 27(3), pages 137-146, March.
    33. Filippini, Massimo & Pachauri, Shonali, 2004. "Elasticities of electricity demand in urban Indian households," Energy Policy, Elsevier, vol. 32(3), pages 429-436, February.
    34. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    35. Giovanni S. F. Bruno, 2005. "Estimation and inference in dynamic unbalanced panel-data models with a small number of individuals," Stata Journal, StataCorp LP, vol. 5(4), pages 473-500, December.
    36. Michael L. Nieswiadomy & David J. Molina, 1989. "Comparing Residential Water Demand Estimates under Decreasing and Increasing Block Rates Using Household Data," Land Economics, University of Wisconsin Press, vol. 65(3), pages 280-289.
    37. Bernard, Jean-Thomas & Bolduc, Denis & Yameogo, Nadège-Désirée, 2011. "A pseudo-panel data model of household electricity demand," Resource and Energy Economics, Elsevier, vol. 33(1), pages 315-325, January.
    38. Narayan, Paresh Kumar & Smyth, Russell, 2005. "The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 33(4), pages 467-474, March.
    39. Burtless, Gary & Hausman, Jerry A, 1978. "The Effect of Taxation on Labor Supply: Evaluating the Gary Negative Income Tax Experiments," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 1103-1130, December.
    40. Holtedahl, Pernille & Joutz, Frederick L., 2004. "Residential electricity demand in Taiwan," Energy Economics, Elsevier, vol. 26(2), pages 201-224, March.
    41. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
    42. Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February.
    43. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    44. John A. Nordin, 1976. "A Proposed Modification of Taylor's Demand Analysis: Comment," Bell Journal of Economics, The RAND Corporation, vol. 7(2), pages 719-721, Autumn.
    45. Lester D. Taylor, 1975. "The Demand for Electricity: A Survey," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 74-110, Spring.
    46. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    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. Jia, Jun-Jun & Guo, Jin & Wei, Chu, 2021. "Elasticities of residential electricity demand in China under increasing-block pricing constraint: New estimation using household survey data," Energy Policy, Elsevier, vol. 156(C).
    2. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    3. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    4. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    5. Alberini, Anna & Gans, Will & Velez-Lopez, Daniel, 2011. "Residential consumption of gas and electricity in the U.S.: The role of prices and income," Energy Economics, Elsevier, vol. 33(5), pages 870-881, September.
    6. Blazquez Leticia & Nina Boogen & Massimo Filippini, 2012. "Residential electricity demand for Spain: new empirical evidence using aggregated data," CEPE Working paper series 12-82, CEPE Center for Energy Policy and Economics, ETH Zurich.
    7. Alberini, Anna & Filippini, Massimo, 2011. "Response of residential electricity demand to price: The effect of measurement error," Energy Economics, Elsevier, vol. 33(5), pages 889-895, September.
    8. Akihiro Otsuka, 2019. "Natural disasters and electricity consumption behavior: a case study of the 2011 Great East Japan Earthquake," Asia-Pacific Journal of Regional Science, Springer, vol. 3(3), pages 887-910, October.
    9. Cialani, Catia & Mortazavi, Reza, 2018. "Household and industrial electricity demand in Europe," Energy Policy, Elsevier, vol. 122(C), pages 592-600.
    10. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    11. Okajima, Shigeharu & Okajima, Hiroko, 2013. "Estimation of Japanese price elasticities of residential electricity demand, 1990–2007," Energy Economics, Elsevier, vol. 40(C), pages 433-440.
    12. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    13. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    14. Salari, Mahmoud & Javid, Roxana J., 2016. "Residential energy demand in the United States: Analysis using static and dynamic approaches," Energy Policy, Elsevier, vol. 98(C), pages 637-649.
    15. Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan, 2019. "Heterogeneity in the price response of residential electricity demand: A dynamic approach for Germany," Resource and Energy Economics, Elsevier, vol. 57(C), pages 119-134.
    16. Dorothée CHARLIER & Mouez FODHA & Djamel KIRAT, 2021. "CO2 Emissions from the Residential Sector in Europe: Some Insights form a Country-Level Assessment," LEO Working Papers / DR LEO 2849, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    17. Kostakis, Ioannis & Lolos, Sarantis & Sardianou, Eleni, 2021. "Residential natural gas demand: Assessing the evidence from Greece using pseudo-panels, 2012–2019," Energy Economics, Elsevier, vol. 99(C).
    18. Martins, Luís Oscar Silva & Amorim, Inara Rosa & Mendes, Vinícius de Araújo & Silva, Marcelo Santana & Freires, Francisco Gaudêncio Mendonça & Teles, Eduardo Oliveira & Torres, Ednildo Andrade, 2021. "Price and income elasticities of residential electricity demand in Brazil and policy implications," Utilities Policy, Elsevier, vol. 71(C).
    19. Kiran B Krishnamurthy, Chandra & Kriström, Bengt, 2013. "A cross-country analysis of residential electricity demand in 11 OECD-countries," CERE Working Papers 2013:5, CERE - the Center for Environmental and Resource Economics, revised 30 Jun 2014.
    20. Gautam, Tej K. & Paudel, Krishna P., 2018. "Estimating sectoral demands for electricity using the pooled mean group method," Applied Energy, Elsevier, vol. 231(C), pages 54-67.

    More about this item

    Keywords

    Residential electricity demand; Increasing-block pricing; Seasonality; Partial adjustment model; Price elasticity; Income effects;
    All these keywords.

    JEL classification:

    • D - Microeconomics
    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

    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:eee:eneeco:v:48:y:2015:i:c:p:168-177. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.