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Time Series Analysis of Deregulatory Dynamics and Technical Efficiency: The Case of the U.S. Airline Industry

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  • Alam, Ila M Semenick
  • Sickles, Robin C

Abstract

As markets worldwide become less regulated, it becomes increasingly possible and timely to establish the presence of an empirical relationship between technical efficiency and market forces compelling agents to economize. This article, taking an innovative approach to test the hypothesis that competitive pressure enhances efficiency, constructs a methodology to examine time series of technical efficiency indices for cointegration and convergence. A panel of U.S. airlines, observed quarterly between 1970 and 1990, is used as a case study. Cointegration results are suggestive of long-run relationships between carriers; furthermore, convergence tests document less dispersion in firm performance over time. Copyright 2000 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Alam, Ila M Semenick & Sickles, Robin C, 2000. "Time Series Analysis of Deregulatory Dynamics and Technical Efficiency: The Case of the U.S. Airline Industry," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(1), pages 203-218, February.
  • Handle: RePEc:ier:iecrev:v:41:y:2000:i:1:p:203-18
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    Cited by:

    1. Jamasb, Tooraj & Pollitt, Michael & Triebs, Thomas, 2008. "Productivity and efficiency of US gas transmission companies: A European regulatory perspective," Energy Policy, Elsevier, vol. 36(9), pages 3398-3412, September.
    2. repec:eee:transe:v:104:y:2017:i:c:p:52-68 is not listed on IDEAS
    3. Walter Briec & Kristiaan Kerstens, 2006. "Input, output and graph technical efficiency measures on non-convex FDH models with various scaling laws: An integrated approach based upon implicit enumeration algorithms," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 135-166, June.
    4. Duygun, Meryem & Prior, Diego & Shaban, Mohamed & Tortosa-Ausina, Emili, 2016. "Disentangling the European airlines efficiency puzzle: A network data envelopment analysis approach," Omega, Elsevier, vol. 60(C), pages 2-14.
    5. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    6. Robin C. Sickles & Jiaqi Hao & Chenjun Shang, 2014. "Panel data and productivity measurement: an analysis of Asian productivity trends," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 12(3), pages 211-231, August.
    7. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2015. "Evaluating airline efficiency: An application of Virtual Frontier Network SBM," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 1-17.
    8. Jaap W. B. Bos & Bertrand Candelon & Claire Economidou, 2016. "Does knowledge spill over across borders and technology regimes?," Journal of Productivity Analysis, Springer, vol. 46(1), pages 63-82, August.
    9. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    10. 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.
    11. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2016. "Has airline efficiency affected by the inclusion of aviation into European Union Emission Trading Scheme? Evidences from 22 airlines during 2008–2012," Energy, Elsevier, vol. 96(C), pages 8-22.
    12. Lee, Boon L. & Worthington, Andrew C., 2014. "Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 15-20.
    13. 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.
    14. Mallikarjun, Sreekanth, 2015. "Efficiency of US airlines: A strategic operating model," Journal of Air Transport Management, Elsevier, vol. 43(C), pages 46-56.
    15. Michaelides, Panayotis G. & Belegri-Roboli, Athena & Marinos, Theocharis, 2008. "Technical Efficiency in International Air Transport," MPRA Paper 74490, University Library of Munich, Germany.
    16. repec:use:tkiwps:3232 is not listed on IDEAS
    17. repec:eee:transa:v:106:y:2017:i:c:p:197-214 is not listed on IDEAS
    18. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2007. "Semiparametric efficient estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 136(1), pages 281-301, January.
    19. Alam, Ila M Semenick & Morrison, Andrew R, 2000. "Trade Reform Dynamics and Technical Efficiency: The Peruvian Experience," World Bank Economic Review, World Bank Group, vol. 14(2), pages 309-330, May.
    20. Nguyen Khac Minh & Nguyen Viet Hung & Pham Van Khanh & Ha Quynh Hoa, 2014. "Do Direct Foreign Investments Increase Efficiency Convergence at Firm Level? The Case of Vietnam, 2000-2011," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 4(7), pages 109-119, July.
    21. 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.
    22. repec:eee:transa:v:100:y:2017:i:c:p:121-134 is not listed on IDEAS
    23. repec:eee:transa:v:106:y:2017:i:c:p:130-143 is not listed on IDEAS

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