1. Financial performance and ownership structure of European Airports Mikhail Zolotko

2. Outline 1. Motivation 2. Description of analysis techniques 3. Data description 4. Empirical results 5. Conclusions

3. 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

4. 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

5. 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.

6. Mean ratios Private, partially privatised and public airports RatioPrivatePartially privatised Public EBIT/Equity0.110.010.04 EBIT/Assets0.070.030.04 Capex/Depreciation0.83NA0.09 Non-aviation revenue share0.470.200.39 Leverage=Debt/Assets0.300.310.34 EBIT Margin0.240.090.07 Interest coverage ratio10.6817.6510.22 Assets Turnover0.290.650.40 To test significance of differences between ratios across airports t-test and non-parametric Mann-Witney test were used

7. …after accounting for other factors Ratio (dependent variable)PrivatePartially privatised EBIT/Equity+- EBIT/Assets++. Capex/Depreciation ratio- NA Non-aviation revenue share+**-*** Leverage=Debt/Assets-*+ EBIT Margin+*** (>)+* Interest coverage ratio-*(>)- Assets Turnover-+** Signs of coefficients corresponding to ownership dummies (as compared to public airports) in an ANOVA model Stars denote the level of significance

8. Mean ratios Airports before vs after privatisation To test significance of differences between ratios across airports t-test and non-parametric Mann-Witney test were used Public(Partially) privatised EBIT/Equity0.11 EBIT/Assets0.010.08 Non-aviation revenue share0.320.36 Leverage=Debt/Assets0.580.57 EBIT Margin0.180.25 EBITDA Margin0.320.38 Interest coverage ratio18.329.52 Assets Turnover0.640.36

9. …again, taking into account other factors Ratio (dependent variable)Public EBIT/Equity- EBIT/Assets+ * Non-aviation revenue share- Leverage=Debt/Assets- EBIT Margin-* EBITDA Margin-* Interest coverage ratio+ Assets Turnover+*** Signs of coefficients corresponding to ownership dummies (as compared to (partially) privatised airports) in an ANOVA model Stars denote the level of significance

10. 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)

11. 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.

12. 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)

13. 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 Explanatory variableTruncated regression coefficients Log assets-0.0462 UK-1.0455* Italy1.4078* Leverage-0.2047 Private0.2067 Partially privatised-1.652**

14. DEA scores explained (under variable returns to scale). 1st specification Negative signs denote increasing effiency given increase in variable Explanatory variableTruncated regression coefficients Log assets-0.10*** UK-0.39** Italy-0.73* Leverage0.22 Private0.26* Partially privatised-0.70**

15. DEA scores explained (under constant returns to scale). 2nd specification Negative signs denote increasing effiency given increase in variable Explanatory variableTruncated regression coefficients Log assets1.73*** UK0.12 Italy5.97** Leverage-14.47*** Private-2.74* Partially privatised-0.51

16. DEA scores explained (under variable returns to scale). 2nd specification Negative signs denote increasing effiency given increase in variable Explanatory variableTruncated regression coefficients Log assets0.02 UK0.14 Italy-1.17^ Leverage-1.45* Private-0.27 Partially privatised-0.57*

17. Conslusions  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 coverage ratio may be an evidence of higher interest rates for private companies compared to )

18. Conslusions  On the „overall” financial performance level private and partially privatised airports outperform public 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.

19. Thank you for you attention!