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How scale and institutional setting explain the costs of small airports? -An application of spatial regression analysis

Author

Listed:
  • Tolga Ülkü

    (University of Berlin)

  • Vahidin Jeleskovic

    (University of Kassel)

  • Jürgen Müller

    (University of Berlin)

Abstract

One of the main pillars of efficient airport operations is cost-minimization. Unit costs of operation with respect to the level of passengers served are a possible proxy to measure the cost efficiency of an airport. Due to compound production framework and sophisticated political-economic environment of airports, estimation of airport costs requires detailed specifications. Airport cost functions should be able to explain the total costs with the main inputs labor, material and capital as well as by taking the airport specific characteristics into account. In this paper, we apply such an approach and focus on airport specific characteristics. We use a spatial regression methodology to explain how these drive the unit costs and analyze the spatial relationship among the dependent variables. Two separate data samples from Norwegian and French airports are used in this research to test various hypotheses. Because a large number of regional airports in both countries cannot reach financial break-even, our first research question deals with the effects of subsidies, which often follow regional and political considerations. One must therefore find an efficient way to maintain these airports without any distortions on the incentives. When evaluating the relationship between subsidies and unit costs, we find negative effect of subsidies on airport cost efficiency. Second, we evaluate the importance of economies of scale by focusing on the relationship between airport size and unit costs. Finally, the results of spatial regression show that a denser spatial distribution of airports results in higher unit costs as a consequence of lower capacity utilization, indicating the negative effect of spatial competition on airport unit costs within an airport network.

Suggested Citation

  • Tolga Ülkü & Vahidin Jeleskovic & Jürgen Müller, 2014. "How scale and institutional setting explain the costs of small airports? -An application of spatial regression analysis," MAGKS Papers on Economics 201435, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:201435
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    as
    1. Low, Joyce M.W. & Tang, Loon Ching, 2006. "Factor substitution and complementarity in the Asia airport industry," Journal of Air Transport Management, Elsevier, vol. 12(5), pages 261-266.
    2. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    3. Volodymyr Bilotkach & Joseph Clougherty & Juergen Mueller & Anming Zhang, 2012. "Regulation, privatization, and airport charges: panel data evidence from European airports," Journal of Regulatory Economics, Springer, vol. 42(1), pages 73-94, August.
    4. Pavlyuk, Dmitry, 2012. "Airport Benchmarking and Spatial Competition: a Critical Review," MPRA Paper 43391, University Library of Munich, Germany.
    5. Luc Anselin, 2001. "Spatial Effects in Econometric Practice in Environmental and Resource Economics," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 705-710.
    6. Paolo Malighetti & Gianmaria Martini & Stefano Paleari & Renato Redondi, 2008. "The Efficiency of European Airports: Do the Importance in the EU Network and the Intensity of Competition Matter?," Working Papers 0804, Department of Management, Information and Production Engineering, University of Bergamo.
    7. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis," Environment and Planning A, , vol. 30(11), pages 1905-1927, November.
    8. Voltes-Dorta, Augusto & Pagliari, Romano, 2012. "The impact of recession on airports' cost efficiency," Transport Policy, Elsevier, vol. 24(C), pages 211-222.
    9. J. F. Nolan & P. C. Ritchie & J. R. Rowcroft, 2001. "Measuring efficiency in the public sector using nonparametric frontier estimators: a study of transit agencies in the USA," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 913-922.
    10. Lian, Jon Inge, 2010. "Network dependency and airline competition – Consequences for remote areas in Norway," Journal of Air Transport Management, Elsevier, vol. 16(3), pages 137-143.
    11. Chi-Lok, Andrew Yuen & Zhang, Anming, 2009. "Effects of competition and policy changes on Chinese airport productivity: An empirical investigation," Journal of Air Transport Management, Elsevier, vol. 15(4), pages 166-174.
    12. Fröhlich, Karsten & Niemeier, Hans-Martin, 2011. "The importance of spatial economics for assessing airport competition," Journal of Air Transport Management, Elsevier, vol. 17(1), pages 44-48.
    13. Martín, Juan Carlos & Román, Concepción & Voltes-Dorta, Augusto, 2011. "Scale economies and marginal costs in Spanish airports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 238-248, March.
    14. Hans-Friedrich Eckey & Reinhold Kosfeld & Matthias Türck, 2007. "Regional Convergence in Germany: a Geographically Weighted Regression Approach," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(1), pages 45-64.
    15. Barros, Carlos Pestana, 2011. "Cost efficiency of African airports using a finite mixture model," Transport Policy, Elsevier, vol. 18(6), pages 807-813, November.
    16. Oum, Tae H. & Yan, Jia & Yu, Chunyan, 2008. "Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports," Journal of Urban Economics, Elsevier, vol. 64(2), pages 422-435, September.
    17. Huber, Hans, 2009. "Comparing spatial concentration and assessing relative market structure in air traffic," Journal of Air Transport Management, Elsevier, vol. 15(4), pages 184-194.
    18. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    19. Vahidin Jeleskovic & Benjamin Schwanebeck, 2012. "Assessment of a spatial panel model for the efficiency analysis of the heterogonous healthcare systems in the world," MAGKS Papers on Economics 201248, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    20. Pita, João P. & Adler, Nicole & Antunes, António P., 2014. "Socially-oriented flight scheduling and fleet assignment model with an application to Norway," Transportation Research Part B: Methodological, Elsevier, vol. 61(C), pages 17-32.
    21. David Starkie & George Yarrow, 2013. "Why airports can face price-elastic demands: margins, lumpiness and leveraged passenger losses," International Transport Forum Discussion Papers 2013/23, OECD Publishing.
    22. Adler, Nicole & Ülkü, Tolga & Yazhemsky, Ekaterina, 2013. "Small regional airport sustainability: Lessons from benchmarking," Journal of Air Transport Management, Elsevier, vol. 33(C), pages 22-31.
    23. Pels, Eric & Njegovan, Nenad & Behrens, Christiaan, 2009. "Low-cost airlines and airport competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(2), pages 335-344, March.
    24. Link, Heike & Götze, Wolfgang & Himanen, Veli, 2009. "Estimating the marginal costs of airport operation using multivariate time series models with correlated error terms," Journal of Air Transport Management, Elsevier, vol. 15(1), pages 41-46.
    25. Carlsson, Fredrik, 2002. "Airport Marginal Cost Pricing: Discussion and an Application to Swedish Airports," Working Papers in Economics 85, University of Gothenburg, Department of Economics.
    26. Barros, Carlos Pestana, 2008. "Technical efficiency of UK airports," Journal of Air Transport Management, Elsevier, vol. 14(4), pages 175-178.
    27. Assaf, A., 2010. "The cost efficiency of Australian airports post privatisation: A Bayesian methodology," Tourism Management, Elsevier, vol. 31(2), pages 267-273.
    28. Martín, Juan Carlos & Voltes-Dorta, Augusto, 2011. "The dilemma between capacity expansions and multi-airport systems: Empirical evidence from the industry's cost function," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(3), pages 382-389, May.
    29. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    30. Karlaftis, Matt G. & McCarthy, Patrick, 1998. "Operating subsidies and performance in public transit: an empirical study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(5), pages 359-375, September.
    31. Pels, Eric & Nijkamp, Peter & Rietveld, Piet, 2003. "Inefficiencies and scale economies of European airport operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(5), pages 341-361, September.
    32. Jonathan Cowie, 2009. "The British Passenger Rail Privatisation: Conclusions on Subsidy and Efficiency from the First Round of Franchises," Journal of Transport Economics and Policy, University of Bath, vol. 43(1), pages 85-104, January.
    33. Barrett, Sean D, 2000. "Airport competition in the deregulated European aviation market," Journal of Air Transport Management, Elsevier, vol. 6(1), pages 13-27.
    34. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    35. Martín, Juan Carlos & Voltes-Dorta, Augusto, 2011. "The econometric estimation of airports' cost function," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 112-127, January.
    36. David Starkie, 2008. "The Airport Industry in a Competitive Environment: A United Kingdom Perspective," OECD/ITF Joint Transport Research Centre Discussion Papers 2008/15, OECD Publishing.
    37. Carlin, Alan & Park, Rolla Edward, 1970. "Marginal Cost Pricing of Airport Runway Capacity," American Economic Review, American Economic Association, vol. 60(3), pages 310-319, June.
    38. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
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    Cited by:

    1. Pavlyuk, Dmitry, 2016. "Implication of spatial heterogeneity for airports' efficiency estimation," Research in Transportation Economics, Elsevier, vol. 56(C), pages 15-24.

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    More about this item

    Keywords

    Airport costs; airport subsidies; spatial regression; scale economies;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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