IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v67y2014icp30-46.html
   My bibliography  Save this article

Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area

Author

Listed:
  • Melo, Patricia C.
  • Ramli, Ahmad Razi

Abstract

This paper estimates fuel demand models for the Lisbon Metropolitan Area (AML) and uses the demand elasticities obtained to predict future levels of road transport CO2 greenhouse gas emissions. Data for the municipalities constituting the AML and the period 1993–2010 are analysed using static and dynamic panel data models to measure the relative importance of fuel price, income, vehicle stock, the price of public transport, and the availability of urban and suburban rail networks on fuel demand. To the best of our knowledge, this is the first study in the Portuguese context to produce fuel demand elasticities for a specific metropolitan area, as opposed to the estimation of country-level aggregate elasticities. Our findings indicate that the elasticity of fuel demand with respect to fuel price ranges between −0.48 and −0.72 in the short run and between −1.19 and −1.82 in the long run. Income elasticities are found to range between 0.51 and 0.54 in the short run and between 1.26 and 1.37 in the long run. The elasticity of fuel demand with respect to vehicle stock (keeping population constant) is 0.57 in the short run and 1.43 in the long run. There is only weak evidence of a reduction in fuel demand as a result of a decrease in the price of public transport, and no effect of greater availability of rail networks. Based on the elasticities estimated, we predict road transport CO2 emissions for the AML according to different macroeconomic scenarios. The results indicate that the emissions target is only achieved in the scenario of poor economic performance. In the presence of medium and strong economic growth, fuel prices would need to increase by about 7% and 11% per year respectively in order to meet the emissions target.

Suggested Citation

  • Melo, Patricia C. & Ramli, Ahmad Razi, 2014. "Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 30-46.
    • Handle: RePEc:eee:transa:v:67:y:2014:i:c:p:30-46
    DOI: 10.1016/j.tra.2014.06.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856414001414
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2014.06.001?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. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2003. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," Empirical Economics, Springer, vol. 28(4), pages 795-811, November.
    5. A. Bhargava & L. Franzini & W. Narendranathan, 2006. "Serial Correlation and the Fixed Effects Model," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 4, pages 61-77, World Scientific Publishing Co. Pte. Ltd..
    6. Daniel J. Graham & Stephen Glaister, 2002. "The Demand for Automobile Fuel: A Survey of Elasticities," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 1-25, January.
    7. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    8. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    9. 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.
    10. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    11. Liddle, Brantley, 2009. "Long-Run Relationship among Transport Demand, Income, and Gasoline Price for the US," MPRA Paper 52080, University Library of Munich, Germany.
    12. Polemis, Michael L., 2006. "Empirical assessment of the determinants of road energy demand in Greece," Energy Economics, Elsevier, vol. 28(3), pages 385-403, May.
    13. Jonathan E. Hughes & Christopher R. Knittel & Daniel Sperling, 2008. "Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand," The Energy Journal, International Association for Energy Economics, vol. 29(1), pages 113-134.
    14. Brons, Martijn & Nijkamp, Peter & Pels, Eric & Rietveld, Piet, 2008. "A meta-analysis of the price elasticity of gasoline demand. A SUR approach," Energy Economics, Elsevier, vol. 30(5), pages 2105-2122, September.
    15. Crôtte, Amado & Noland, Robert B. & Graham, Daniel J., 2010. "An analysis of gasoline demand elasticities at the national and local levels in Mexico," Energy Policy, Elsevier, vol. 38(8), pages 4445-4456, August.
    16. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    17. Al-faris, Abdul-razak F., 1997. "Demand for oil products in the GCC countries," Energy Policy, Elsevier, vol. 25(1), pages 55-61, January.
    18. Dahl, Carol A., 2012. "Measuring global gasoline and diesel price and income elasticities," Energy Policy, Elsevier, vol. 41(C), pages 2-13.
    19. Virley, Simon, 1993. "The effect of fuel price increases on road transport CO2 emissions," Transport Policy, Elsevier, vol. 1(1), pages 43-48, October.
    20. Li, Zheng & Rose, John M. & Hensher, David A., 2010. "Forecasting automobile petrol demand in Australia: An evaluation of empirical models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(1), pages 16-38, January.
    21. Samimi, Rodney, 1995. "Road transport energy demand in Australia: A cointegration approach," Energy Economics, Elsevier, vol. 17(4), pages 329-339, October.
    22. Joyce Dargay & Dermot Gately & Martin Sommer, 2007. "Vehicle Ownership and Income Growth, Worldwide: 1960-2030," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 143-170.
    23. 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.
    24. 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.
    25. Pock, Markus, 2010. "Gasoline demand in Europe: New insights," Energy Economics, Elsevier, vol. 32(1), pages 54-62, January.
    26. Park, Sung Y. & Zhao, Guochang, 2010. "An estimation of U.S. gasoline demand: A smooth time-varying cointegration approach," Energy Economics, Elsevier, vol. 32(1), pages 110-120, January.
    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. Patrícia C. Melo, 2022. "Will COVID‐19 hinder or aid the transition to sustainable urban mobility? Spotlight on Portugal's largest urban agglomeration," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 80-106, November.
    2. Zimmer, Anne & Koch, Nicolas, 2017. "Fuel consumption dynamics in Europe: Tax reform implications for air pollution and carbon emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 22-50.
    3. Cheng, Yung-Hsiang & Chang, Yu-Hern & Lu, I.J., 2015. "Urban transportation energy and carbon dioxide emission reduction strategies," Applied Energy, Elsevier, vol. 157(C), pages 953-973.
    4. Bigerna, S. & Bollino, C.A. & Micheli, S. & Polinori, P., 2017. "Revealed and stated preferences for CO2 emissions reduction: The missing link," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1213-1221.

    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. Bakhat, Mohcine & Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "Elasticities of transport fuels at times of economic crisis: An empirical analysis for Spain," Energy Economics, Elsevier, vol. 68(S1), pages 66-80.
    2. Mohcine Bakhat & José M. Labeaga & Xavier Labandeira & Xiral Lñpez, 2013. "Economic Crisis and Elasticities of Car Fuels: Evidence for Spain," Working Papers fa15-2013, Economics for Energy.
    3. Scott, K. Rebecca, 2015. "Demand and price uncertainty: Rational habits in international gasoline demand," Energy, Elsevier, vol. 79(C), pages 40-49.
    4. Zimmer, Anne & Koch, Nicolas, 2017. "Fuel consumption dynamics in Europe: Tax reform implications for air pollution and carbon emissions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 22-50.
    5. Scott, K. Rebecca, 2011. "Demand and Price Volatility: Rational Habits in International Gasoline Demand," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2q87432b, Department of Agricultural & Resource Economics, UC Berkeley.
    6. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    7. Ghoddusi, Hamed & Morovati, Mohammad & Rafizadeh, Nima, 2019. "Foreign Exchange Shocks and Gasoline Consumption," Energy Economics, Elsevier, vol. 84(C).
    8. Pock, Markus, 2010. "Gasoline demand in Europe: New insights," Energy Economics, Elsevier, vol. 32(1), pages 54-62, January.
    9. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
    10. Shaw, Charles, 2020. "Econometric Analysis of Demand for Petrol in India, 1966-2019," MPRA Paper 104797, University Library of Munich, Germany.
    11. Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    12. Rosa M. González-Marrero & Rosa M. Lorenzo-Alegría & Gustavo A. Marrero, 2011. "Gasoline and Diesel Consumption for Road Transport in Spain: a Dynamic Panel Data Approach," Economic Reports 04-2011, FEDEA.
    13. Liddle, Brantley & Parker, Steven, 2022. "One more for the road: Reconsidering whether OECD gasoline income and price elasticities have changed over time," Energy Economics, Elsevier, vol. 114(C).
    14. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    15. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    16. Antonio Ruiz Porras, 2016. "La investigación econométrica mediante paneles de datos:historia, modelos y usos en México," Archivos Revista Economía y Política., Facultad de Ciencias Económicas y Administrativas, Universidad de Cuenca., vol. 24, pages 11-32, Julio.
    17. Johanna Vogel, 2012. "Agglomeration and Growth: Evidence from the Regions of Central and Eastern Europe," ERSA conference papers ersa12p1089, European Regional Science Association.
    18. Burke, Paul J. & Nishitateno, Shuhei, 2013. "Gasoline prices, gasoline consumption, and new-vehicle fuel economy: Evidence for a large sample of countries," Energy Economics, Elsevier, vol. 36(C), pages 363-370.
    19. Pock, Markus, 2007. "Gasoline and Diesel Demand in Europe: New Insights," Economics Series 202, Institute for Advanced Studies.
    20. Osvaldo Lagares, 2016. "Capital, Economic Growth and Relative Income Differences in Latin America," Discussion Papers 16/03, Department of Economics, University of York.

    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:transa:v:67:y:2014:i:c:p:30-46. 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/wps/find/journaldescription.cws_home/547/description#description .

    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.