Financial performance and ownership structure of european airports
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Financial performance and ownership structure of European Airports. Mikhail Zolotko. Outline. Motivation Description of analysis techniques Data description Empirical results Conclusions. Why study financial performance of the airports?.

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Financial performance and ownership structure of european airports l.jpg
Financial performance and ownership structure of European Airports

Mikhail Zolotko


Outline l.jpg
Outline

  • Motivation

  • Description of analysis techniques

  • Data description

  • Empirical results

  • Conclusions


Why study financial performance of the airports l.jpg
Why study financial performance of the airports?

  • Components of overall airports performance (according to e.g. Graham, 2005):

    • Service quality performance

    • Operational performance

    • Financial performance

  • Financial performance is of interest to investors


Structure of the analysis l.jpg
Structure of the analysis

  • Compare financial performance indicators of the airports

    • that didn’t experience the change in ownership structure

    • that did experience it

  • Apply Data Envelopment Analysis to the financial data and explain efficiency scores through a number of variables including ownership structure


Data description l.jpg
Data description

  • Unbalanced panel of selected entries of balance sheets, income statements and cash flow statements.

  • Time span: 1990-2006

  • Over 50 airports with constant ownership structure

  • 17 airports that experienced the change in the ownership structure.


Mean ratios private partially privatised and public airports l.jpg
Mean ratiosPrivate, partially privatised and public airports

To test significance of differences between ratios across airports t-test and non-parametric Mann-Witney test were used


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…after accounting for other factors

Signs of coefficients corresponding to ownership dummies (as compared to public airports) in an ANOVA model

Stars denote the level of significance


Mean ratios airports before vs after privatisation l.jpg
Mean ratiosAirports before vs after privatisation

To test significance of differences between ratios across airports t-test and non-parametric Mann-Witney test were used


Again taking into account other factors l.jpg
…again, taking into account other factors

Signs of coefficients corresponding to ownership dummies (as compared to (partially) privatised airports) in an ANOVA model

Stars denote the level of significance


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DEA scores. First specification

  • Inputs: log assets, operating expenditure except depreciation

  • Outputs: aviation revenue, non-aviation revenue

    (in contrast to Vogel’s one-input, one-output analysis)


Dea scores second specification l.jpg
DEA scores. Second specification

  • Inputs: log assets, total personnel expenditure

  • Outputs: aviation revenue, non-aviation revenue

    The number of specifications is limited due to data limitations

    Though specifications are almost identical, the results are totally different.


Dea scores explanation l.jpg
DEA scores explanation

  • According to Simar and Wilson (2007), only application of truncated regression leads to consistent estimates.

    (compared to Tobit regression and OLS that were used in literature previously)

  • Regressors used:

    • Ownership and country dummies

    • Leverage (debt/assets)

    • Airport size proxy (logarithm of assets to reduce the variation – a technical condition to ensure convergence)


Dea scores explained under constant returns to scale 1st specification l.jpg
DEA scores explained (under constant returns to scale). 1st specification

Negative signs denote increasing effiency given increase in variable

Stars denote significance level: *** 0.001, ** 0.01, *0.05, ^0.1


Dea scores explained under variable returns to scale 1st specification l.jpg
DEA scores explained (under variable returns to scale). 1st specification

Negative signs denote increasing effiency given increase in variable


Dea scores explained under constant returns to scale 2nd specification l.jpg
DEA scores explained (under constant returns to scale). 2nd specification

Negative signs denote increasing effiency given increase in variable


Dea scores explained under variable returns to scale 2nd specification l.jpg
DEA scores explained (under variable returns to scale). 2nd specification

Negative signs denote increasing effiency given increase in variable


Conslusions l.jpg
Conslusions specification

  • Private airports beat both partially privatised and publicly owned airports in terms of profitability but are worse at interest coverage and asset turnover

  • After privatisation airports tend to increase profitability, non-aviation revenue share and to worsen interest coverage and asset turnover.

    (where decrease in interest coverageratio may be an evidence of higher interest rates for private companies compared to )


Conslusions18 l.jpg
Conslusions specification

  • On the „overall” financial performance level private and partially privatised airports outperformpublic airports which is however evidenced only by one of two specifications.

  • „Overall” financial performance can also be explained by country differences, airports size and leverage. However, these effects often have different signs under different specifications.



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