IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v65y2014icp92-102.html
   My bibliography  Save this article

The asymmetric effects of income and fuel price on air transport demand

Author

Listed:
  • Wadud, Zia

Abstract

Forecasts of passenger demand are an important parameter for aviation planners. Air transport demand models typically assume a perfectly reversible impact of the demand drivers. However, there are reasons to believe that the impacts of some of the demand drivers such as fuel price or income on air transport demand may not be perfectly reversible. Two types of imperfect reversibility, namely asymmetry and hysteresis, are possible. Asymmetry refers to the differences in the demand impacts of a rising price or income from that of a falling price or income. Hysteresis refers to the dependence of the impacts of changing price or income on previous history, especially on previous maximum price or income. We use US time series data and decompose each of fuel price and income into three component series to develop an econometric model for air transport demand that is capable of capturing the potential imperfectly reversible relationships and test for the presence or absence of reversibility. We find statistical evidence of asymmetry and hysteresis – for both, prices and income – in air transport demand. Implications for policy and practice are then discussed.

Suggested Citation

  • Wadud, Zia, 2014. "The asymmetric effects of income and fuel price on air transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 92-102.
    • Handle: RePEc:eee:transa:v:65:y:2014:i:c:p:92-102
    DOI: 10.1016/j.tra.2014.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856414000822
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2014.04.001?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. Dargay, Joyce & Gately, Dermot, 1997. "The demand for transportation fuels: Imperfect price-reversibility?," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 71-82, February.
    2. Bidwell, Miles O, Jr & Wang, Bruce X & Zona, J Douglas, 1995. "An Analysis of Asymmetric Demand Response to Price Changes: The Case of Local Telephone Calls," Journal of Regulatory Economics, Springer, vol. 8(3), pages 285-298, November.
    3. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    4. Peter C. B. Phillips & Mico Loretan, 1991. "Estimating Long-run Economic Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 407-436.
    5. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
    6. Tsekeris, Theodore, 2009. "Dynamic analysis of air travel demand in competitive island markets," Journal of Air Transport Management, Elsevier, vol. 15(6), pages 267-273.
    7. Hendry, David F, 1986. "Econometric Modelling with Cointegrated Variables: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 201-212, August.
    8. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-277, August.
    9. Rudolf Wolffram, 1971. "Positivistic Measures of Aggregate Supply Elasticities: Some New Approaches—Some Critical Notes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(2), pages 356-359.
    10. Adeyemi, Olutomi I. & Hunt, Lester C., 2007. "Modelling OECD industrial energy demand: Asymmetric price responses and energy-saving technical change," Energy Economics, Elsevier, vol. 29(4), pages 693-709, July.
    11. Diego Escobari, 2013. "Asymmetric Price Adjustments in Airlines," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 34(2), pages 74-85, March.
    12. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    13. Ryan, David L. & Plourde, Andre, 2002. "Smaller and smaller? The price responsiveness of nontransport oil demand," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(2), pages 285-317.
    14. P.B. Goodwin, 1977. "Habit and Hysteresis in Mode Choice," Urban Studies, Urban Studies Journal Limited, vol. 14(1), pages 95-98, February.
    15. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    16. Dermot Gately & Hiliard G. Huntington, 2002. "The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-55.
    17. Dargay, Joyce M, 2001. "The effect of income on car ownership: evidence of asymmetry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(9), pages 807-821, November.
    18. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    19. Profillidis, V.A, 2000. "Econometric and fuzzy models for the forecast of demand in the airport of Rhodes," Journal of Air Transport Management, Elsevier, vol. 6(2), pages 95-100.
    20. Bacon, Robert W., 1991. "Rockets and feathers: the asymmetric speed of adjustment of UK retail gasoline prices to cost changes," Energy Economics, Elsevier, vol. 13(3), pages 211-218, July.
    21. Durbin, J, 1970. "Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables," Econometrica, Econometric Society, vol. 38(3), pages 410-421, May.
    22. Godfrey, Leslie G, 1978. "Testing against General Autoregressive and Moving Average Error Models When the Regressors Include Lagged Dependent Variables," Econometrica, Econometric Society, vol. 46(6), pages 1293-1301, November.
    23. Ito, Harumi & Lee, Darin, 2005. "Assessing the impact of the September 11 terrorist attacks on U.S. airline demand," Journal of Economics and Business, Elsevier, vol. 57(1), pages 75-95.
    24. Sentenac-Chemin, Elodie, 2012. "Is the price effect on fuel consumption symmetric? Some evidence from an empirical study," Energy Policy, Elsevier, vol. 41(C), pages 59-65.
    25. Dermot Gately, 1992. "Imperfect Price-Reversibility of U.S. Gasoline Demand: Asymmetric Responses to Price Increases and Declines," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 179-208.
    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. Francesco Cerigioni, 2021. "Dual Decision Processes: Retrieving Preferences When Some Choices Are Automatic," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1667-1704.
    2. Chen, Jieh-Haur & Wei, Hsi-Hsien & Chen, Chih-Lin & Wei, Hsin-Yi & Chen, Yi-Ping & Ye, Zhongnan, 2020. "A practical approach to determining critical macroeconomic factors in air-traffic volume based on K-means clustering and decision-tree classification," Journal of Air Transport Management, Elsevier, vol. 82(C).
    3. Pal, Debdatta & Mitra, Subrata K., 2022. "Do airfares respond asymmetrically to fuel price changes? A multiple threshold nonlinear ARDL model," Energy Economics, Elsevier, vol. 111(C).
    4. Chi, Junwook, 2018. "Imperfect reversibility of fuel demand for road transport: Asymmetric and hysteretic effects of income and price changes in Korea," Transport Policy, Elsevier, vol. 71(C), pages 116-125.
    5. Sotirios Thanos & Maria Kamargianni & Andreas Schäfer, 2018. "Car Travel Demand: Spillovers and Asymmetric Price Effects in a Spatial Setting," Transportation Science, INFORMS, vol. 52(3), pages 621-636, June.
    6. Akinyemi, Yingigba Chioma, 2023. "Air cargo demand in Africa: Application of cointegration and error correction modelling techniques," Journal of Air Transport Management, Elsevier, vol. 109(C).
    7. Lo, Winnie Wai Ling & Wan, Yulai & Zhang, Anming, 2015. "Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 309-324.
    8. Wadud, Zia, 2015. "Imperfect reversibility of air transport demand: Effects of air fare, fuel prices and price transmission," Transportation Research Part A: Policy and Practice, Elsevier, vol. 72(C), pages 16-26.
    9. Wang, Yue & Wong, Collin Wai Hung & Cheung, Tommy King-Yin & Wu, Edmund Yangming, 2021. "How influential factors affect aviation networks: A Bayesian network analysis," Journal of Air Transport Management, Elsevier, vol. 91(C).
    10. Kamyabi, Najmeh & Chidmi, Benaissa, 2022. "Gasoline demand in the United States: An asymmetric economic analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    11. Egon Smeral, 2019. "Seasonal forecasting performance considering varying income elasticities in tourism demand," Tourism Economics, , vol. 25(3), pages 355-374, May.
    12. Wang, Sen & Gao, Yi, 2021. "A literature review and citation analyses of air travel demand studies published between 2010 and 2020," Journal of Air Transport Management, Elsevier, vol. 97(C).
    13. Adedoyin, Festus Fatai & Bekun, Festus Victor & Driha, Oana M. & Balsalobre-Lorente, Daniel, 2020. "The effects of air transportation, energy, ICT and FDI on economic growth in the industry 4.0 era: Evidence from the United States," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    14. Wadud, Zia, 2015. "Decomposing the drivers of aviation fuel demand using simultaneous equation models," Energy, Elsevier, vol. 83(C), pages 551-559.

    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. Wadud, Zia, 2015. "Imperfect reversibility of air transport demand: Effects of air fare, fuel prices and price transmission," Transportation Research Part A: Policy and Practice, Elsevier, vol. 72(C), pages 16-26.
    2. Fedoseeva, Svetlana & Zeidan, Rodrigo, 2018. "How (a)symmetric is the response of import demand to changes in its determinants? Evidence from European energy imports," Energy Economics, Elsevier, vol. 69(C), pages 379-394.
    3. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    4. Frondel, Manuel & Vance, Colin, 2013. "Re-Identifying the Rebound: What About Asymmetry?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 34(4), pages 42-54.
    5. Reza Darisavi Bahmanshir & Ali Akbar Naji Meidani & Mahdi Khodaparast Mashhadi & Narges Salehnia, 2018. "Reversibility Test of Oil Demand Function of OECD Countries Importing Oil from Iran with an Emphasis on Technological and Environmental Considerations: Symmetric and Asymmetric Models," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 132-139.
    6. Adofo, Yaw Osei & Evans, Joanne & Hunt, Lester Charles, 2013. "How sensitive to time period sampling is the asymmetric price response specification in energy demand modelling?," Energy Economics, Elsevier, vol. 40(C), pages 90-109.
    7. Bardsen, Gunnar, 1990. "Dynamic Modelling And The Demand For Narrow Money In Norway," Economic Research Papers 268479, University of Warwick - Department of Economics.
    8. Roberto Martínez-Espiñeira, 2007. "An Estimation of Residential Water Demand Using Co-Integration and Error Correction Techniques," Journal of Applied Economics, Taylor & Francis Journals, vol. 10(1), pages 161-184, May.
    9. McAvinchey, Ian D., 2003. "Modelling and forecasting in an energy demand system with high and low frequency information," Economic Modelling, Elsevier, vol. 20(1), pages 207-226, January.
    10. Liddle, Brantley & Sadorsky, Perry, 2020. "How much do asymmetric changes in income and energy prices affect energy demand?," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    11. Sharimakin, Akinsehinwa, 2021. "Modelling asymmetric price responses of industrial energy demand with a dynamic hierarchical model," Energy Economics, Elsevier, vol. 98(C).
    12. Mizon, Grayham E., 1995. "A simple message for autocorrelation correctors: Don't," Journal of Econometrics, Elsevier, vol. 69(1), pages 267-288, September.
    13. Gerdesmeier, Dieter, 1996. "The role of wealth in money demand," Discussion Paper Series 1: Economic Studies 1996,05e, Deutsche Bundesbank.
    14. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    15. Dilaver, Zafer & Hunt, Lester C., 2021. "Modelling U.S. gasoline demand: A structural time series analysis with asymmetric price responses," Energy Policy, Elsevier, vol. 156(C).
    16. repec:wyi:journl:002087 is not listed on IDEAS
    17. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    18. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    19. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    20. Erdogdu, Erkan, 2007. "Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey," Energy Policy, Elsevier, vol. 35(2), pages 1129-1146, February.
    21. Erdogdu, Erkan, 2010. "Natural gas demand in Turkey," Applied Energy, Elsevier, vol. 87(1), pages 211-219, January.

    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:65:y:2014:i:c:p:92-102. 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.