A time series analysis of the pricing behaviour of directly competitive 'low-cost' airlines

International Journal of Transport Economics

Volumn 32, Issue 1, 2005, Pages 15-38

  Pitfield, D E ^a  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AIR TRANSPORTATION; AIRLINE INDUSTRY; COMPETITION (ECONOMICS); TIME SERIES ANALYSIS; TRANSPORTATION ECONOMICS;

EASTERN HEMISPHERE; EURASIA; EUROPE; WORLD;

EID: 15044352929     PISSN: 03918440     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (26)

1. A more recent attempt to examine competition is found in Pels and Rietveld, where services between a pair of cities, but not the same airports, is examined (in press) and Alderighi et al. (2004).
2. Indeed, there is some evidence that traditional carriers have adopted a similar pricing strategy. See The Sunday Times, 22 February 2004, London.
3. easyJet achieved a 77% load factor in 2003. Reported in The Times, February 7, 2004, London.
4. Buzz was sold to Ryanair in 2003.
5. The series should be akin to the representative perambulatory progress of an inebriated individual. The best forecast for a random walk is the previous observation.
6. Gottman (1981) suggests a rule of thumb for determining stationarity. This is that the square of the ACF will go to zero very rapidly as the number of lags increase and although this isn't a strict criterion, it may be adequate for most practical applications. Another route, but not one followed here, as the data series are not long enough, is to examine the mean, variance and ACF for separate chunks of the observed series.
7. This may be achieved simply by differencing if the resultant Box-Ljung Q statistic indicates white noise.
8. See any text on ARIMA models, for example, Wei (1994) or Gottman (1981).
9. On occasion, a constant term might be included in a model to ensure white noise residuals and this can be interpreted as a trend term. However such recourse was not needed and besides, the interpretation of a constant term on differenced data that is stationary seems problematic.
10. An ARIMA model was calibrated on the basis of non-differenced data, but the standard errors etc. were higher than the model reported here.
11. t statistics in brackets.
12. Where there was poor guidance as to the appropriate model, all the relatively parsimonious models described in equations (1) to (10) were tried and the best chosen according to the goodness of fit indicators.
13. It seems the yield management procedure of easyJet is working on its Scottish destinations in unison.
14. The Sunday Times, 15 February 2004, London.
15. The Times, 5th May 2004, London.
16. Nottingham Evening Post, 15th May 2004.
17. Alderighi, M., Cento, A., Nijkamp, P. and Rietveld, P. (2004) The Entry of Low Cost Airlines: Price Competition in the European Airline Market. Work in progress, available from authors.
18. Calder, S. (2002), No Frills: The truth behind the low-cost revolution in the skies, Virgin Books, London.
19. Doganis, R. (1991), Flying Off Course: The economics of international airlines, Routledge, London.
20. Doganis, R. (2001), The airline business in the 21st century. Routledge, London.
21. Gottman, J. M. (1981), Time Series Analysis: A comprehensive introduction for social scientists, Cambridge University Press. Cambridge.
22. Internet Travel Directory website listing low cost airlines at www.itravelnet.com/transport/air/lowcostairlines.html.
23. Pels, E. and Rietveld, P. (in press), Airline pricing behaviour in the London-Paris market, Journal of Air Transport Management.
24. Pitfield, D. E. (1993), Predicting air-transport demand, Environment and Planning A, 25, 459-466.
25. Wei, W. W. S. (1994), Time Series Analysis: Univariate and Multivariate Methods, Addison-Wesley, Redwood City, CA.
26. Williams, G. (2001), Will Europe's Charter Carriers be replaced by 'No-Frills' Scheduled Airlines? Journal of Air Transport Management 35, 14-25.