IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/116122.html

Estimating Short and Long-Run Demand Elasticities: A Primer with Energy-Sector Applications

Author

Listed:
  • Cuddington, John
  • Dagher, Leila

Abstract

Many empirical exercises estimating demand functions, whether in energy economics or other fields, are concerned with estimating dynamic effects of price and income changes over time. This paper first reviews a number of commonly used dynamic demand specifications to highlight the implausible a priori restrictions that they place on short and long-run elasticities. Such problems are easily avoided by adopting a general-to-specific modeling methodology. Second, it discusses functional forms and estimation issues for getting point estimates and associated standard errors for both short and long-run elasticities – key information that is missing from many published studies. Third, our proposed approach is illustrated using a dataset on Minnesota residential electricity demand.

Suggested Citation

  • Cuddington, John & Dagher, Leila, 2013. "Estimating Short and Long-Run Demand Elasticities: A Primer with Energy-Sector Applications," MPRA Paper 116122, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:116122
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/116122/1/MPRA_paper_116122.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-174, Summer.
    2. Urbain, Jean-Pierre, 1992. "On Weak Exogeneity in Error Correction Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(2), pages 187-207, May.
    3. Dagher, Leila, 2012. "Natural gas demand at the utility level: An application of dynamic elasticities," Energy Economics, Elsevier, vol. 34(4), pages 961-969.
    4. Huntington, Hillard G., 2007. "Industrial natural gas consumption in the United States: An empirical model for evaluating future trends," Energy Economics, Elsevier, vol. 29(4), pages 743-759, July.
    5. Garcia-Cerrutti, L. Miguel, 2000. "Estimating elasticities of residential energy demand from panel county data using dynamic random variables models with heteroskedastic and correlated error terms," Resource and Energy Economics, Elsevier, vol. 22(4), pages 355-366, October.
    6. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    7. Andrew C. Harvey, 1990. "The Econometric Analysis of Time Series, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026208189x, December.
    8. Pei, Fanyu & Tilton, John E., 1999. "Consumer preferences, technological change, and the short-run income elasticity of metal demand," Resources Policy, Elsevier, vol. 25(2), pages 87-109, June.
    9. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, , vol. 22(1), pages 75-120, January.
    10. Mizon, Grayham E., 1995. "A simple message for autocorrelation correctors: Don't," Journal of Econometrics, Elsevier, vol. 69(1), pages 267-288, September.
    11. West, Kenneth D, 1988. "Asymptotic Normality, When Regressors Have a Unit Root," Econometrica, Econometric Society, vol. 56(6), pages 1397-1417, November.
    12. Juselius, Katarina, 2006. "The Cointegrated VAR Model: Methodology and Applications," OUP Catalogue, Oxford University Press, number 9780199285679.
    13. Stock, James H, 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors," Econometrica, Econometric Society, vol. 55(5), pages 1035-1056, September.
    14. Wojciech W. Charemza & Derek F. Deadman, 1997. "New Directions In Econometric Practice, Second Edition," Books, Edward Elgar Publishing, number 1139.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Franz Wirl, 2024. "Dynamic demand and noncompetitive intertemporal output adjustments: correction and extension," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(2), pages 483-505, June.
    3. Thierry Brunelle & Gérard de la Paix Bayiha, 2025. "Economic drivers of pesticide use in Cameroon [Déterminants économiques de l’utilisation des pesticides au Cameroun]," Post-Print hal-05332527, HAL.
    4. Gao, Liping & Kinnucan, Henry W. & Zhang, Yaoqi & Qiao, Guanghua, 2016. "The effects of a subsidy for grassland protection on livestock numbers, grazing intensity, and herders’ income in inner Mongolia," Land Use Policy, Elsevier, vol. 54(C), pages 302-312.
    5. Germán Coloma, 2025. "Market definition through demand-and-supply estimations, with an application to the Argentine dishwashing detergent industry," CEMA Working Papers: Serie Documentos de Trabajo. 913, Universidad del CEMA.

    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. repec:aen:journl:ej36-1-07 is not listed on IDEAS
    2. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    3. Mr. Alejandro D Guerson, 2015. "Inflation Dynamics and Monetary Policy in Bolivia," IMF Working Papers 2015/266, International Monetary Fund.
    4. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    5. Myers, Robert J., 1994. "Time Series Econometrics and Commodity Price Analysis: A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 62(02), pages 1-15, August.
    6. Bardsen, Gunnar, "undated". "Dynamic Modelling And The Demand For Narrow Money In Norway," Economic Research Papers 268479, University of Warwick - Department of Economics.
    7. Catherine Bruneau & Eric Jondeau, 1999. "Long‐run Causality, with an Application to International Links Between Long‐term Interest Rates," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 545-568, November.
    8. Shahriyar Aliyev & Evžen Kočenda, 2023. "ECB monetary policy and commodity prices," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 274-304, February.
    9. Bahram Adrangi & Arjun Chatrath, 2022. "Dynamic Responses of Major Pacific Rim Emerging Equity Markets to the US Crude Oil Fear Index (OVX)," Bulletin of Applied Economics, Risk Market Journals, vol. 9(1), pages 51-84.
    10. James H. Stock & Mark W. Watson, 1989. "A Simple MLE of Cointegrating Vectors in Higher Order Integrated Systems," NBER Technical Working Papers 0083, National Bureau of Economic Research, Inc.
    11. Bahram Adrangi & Arjun Chatrath & Joseph Macri & Kambiz Raffiee, 2018. "U.S. Diesel Fuel Price Responses To The Global Crude Oil Supply And Demand," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 1-25, December.
    12. Alejandro Rodriguez Arana, 2021. "La expansion de Covid-19 en Mexico en 2020: un enfoque desde la econometria de series de tiempo," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 1(3), pages 34-66.
    13. Bahram Adrangi & Arjun Chatrath & Joseph Macri & Kambiz Raffiee, 2019. "Dynamic Responses of Major Equity Markets to the US Fear Index," JRFM, MDPI, vol. 12(4), pages 1-23, September.
    14. Shabtai Donnenfeld & Alfred A. Haug, 2008. "Currency invoicing of US imports," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 13(2), pages 184-198.
    15. Herrera, Santiago, 2000. "Determinantes y composición del endeudamiento público en Colombia," IDB Publications (Working Papers) 2110, Inter-American Development Bank.
    16. 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.).
    17. Dutrénit, Gabriela & Natera, José Miguel & Puchet Anyul, Martín & Vera-Cruz, Alexandre O., 2019. "Development profiles and accumulation of technological capabilities in Latin America," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 396-412.
    18. Martin D. Evans & Karen K. Lewis, 1992. "Peso Problems and Heterogeneous Trading: Evidence from Excess Returns in Foreign Exchange and Euromarkets," Working Papers 92-13, New York University, Leonard N. Stern School of Business, Department of Economics.
    19. 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.
    20. Hildegart Ahumada & Magdalena Cornejo, 2015. "Explaining commodity prices by a cointegrated time series-cross section model," Empirical Economics, Springer, vol. 48(4), pages 1667-1690, June.
    21. Harm Bandholz & Jorg Clostermann & Franz Seitz, 2009. "Explaining the US bond yield conundrum," Applied Financial Economics, Taylor & Francis Journals, vol. 19(7), pages 539-550.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    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:pra:mprapa:116122. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.