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Productivity? of US Airlines After Deregulation


  • R. Färe
  • S. Grosskopf
  • R. C. Sickles


We analyse a sample of airline firms most recently examined by Alam and Sickles (2000) and extended by Good, Sickles and Weiher (2005) to include an index of circuity as one of our measures of service quality of airline travel. An additional measure of quality of airline travel is timeliness and is measured by FAA data on the percentage of flights that arrived on time. The two traditional outputs are scheduled and non-scheduled revenue passenger miles. We find that accounting for characteristics such as circuity and percentage of flights arriving on time does affect productivity. Our findings confirm anecdotal accounts of a decline in airline service quality since deregulation, yielding in general lower rates of productivity growth in our sample when quality variables such as indirect routeing and delays are explicitly introduced into the technology. Our findings also point out the power of index number techniques to account for service quality changes and could serve a similar function in analysing post-deregulatory dynamics in other industries such as telecommunications, electric power, distribution and financial services. © 2007 LSE and the University of Bath

Suggested Citation

  • R. Färe & S. Grosskopf & R. C. Sickles, 2007. "Productivity? of US Airlines After Deregulation," Journal of Transport Economics and Policy, University of Bath, vol. 41(1), pages 93-112, January.
  • Handle: RePEc:tpe:jtecpo:v:41:y:2007:i:1:p:93-112

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    Cited by:

    1. Zou, Bo & Elke, Matthew & Hansen, Mark & Kafle, Nabin, 2014. "Evaluating air carrier fuel efficiency in the US airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 306-330.
    2. Aguirregabiria, Victor & Ho, Chun-Yu, 2012. "A dynamic oligopoly game of the US airline industry: Estimation and policy experiments," Journal of Econometrics, Elsevier, vol. 168(1), pages 156-173.
    3. Duygun, Meryem & Kutlu, Levent & Sickles, Robin C., 2014. "Measuring Productivity and Efficiency: A Kalman," Working Papers 15-010, Rice University, Department of Economics.
    4. Gayle, Philip G. & Yimga, Jules O., 2018. "How much do consumers really value air travel on-time performance, and to what extent are airlines motivated to improve their on-time performance?," Economics of Transportation, Elsevier, vol. 14(C), pages 31-41.
    5. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    6. Chen, Yongmin & Gayle, Philip G., 2019. "Mergers and product quality: Evidence from the airline industry," International Journal of Industrial Organization, Elsevier, vol. 62(C), pages 96-135.
    7. Lee, Chia-Yen & Johnson, Andrew L., 2012. "Two-dimensional efficiency decomposition to measure the demand effect in productivity analysis," European Journal of Operational Research, Elsevier, vol. 216(3), pages 584-593.
    8. Yimga, Jules, 2017. "Airline on-time performance and its effects on consumer choice behavior," Research in Transportation Economics, Elsevier, vol. 66(C), pages 12-25.
    9. Yu, Ming-Miin & Chang, Yu-Chun & Chen, Li-Hsueh, 2016. "Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 186-198.
    10. Yu, Ming-Miin & Chen, Li-Hsueh & Chiang, Hui, 2017. "The effects of alliances and size on airlines’ dynamic operational performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 197-214.
    11. Barbot, Cristina & Costa, Ã lvaro & Sochirca, Elena, 2008. "Airlines performance in the new market context: A comparative productivity and efficiency analysis," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 270-274.

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