Privatisation and Financial Performance of European

Airports

Dr. Hans-Arthur Vogel

Content

• Financial performance of 35 European commercial airports (1990 – 2000)

• Evaluation of partial factor productivity (PFP), financial ratio (FRA) and data envelopment analysis (DEA)

• Comparison between public owned, privatised and partially privatised airports

Definitions of Ownership Structure

• Public Ownership: No involvement of private parties

• Partially Privatised: Requires a minimum private share >= 20% with regard to total equity or a lease or concession agreement with a similar risk profile

• Fully Privatised: Long-term private risk investment in terms of a substantial equity stake >= 75%, long-term lease or concession agreement, or a BOT franchise

Sample Airports

Methodology

• Financial metrics emphasises profitability or return rates

• Productivity measures relationship between inputs and outputs

• An independent and a related t-test significance of results

Defintions of Performance Indicators and Financial Ratios

Results of Independent t-Test

• Statistically significant or highly significant differences (95% and 99% confidence level respectively) between publicly owned and privatised airports for 20 out of 28 ratios

• No statistically significant difference: non-aeronautical share of total revenue, return on capital employed, EBITDA margin, return on equity, etc.

Results of Independent Means t-Test

Results of Dependent t-Test

• Partially privatised: ADR, BRS, CPH, HAJ, NAP and VIE

• Fully privatised: BFS, CWL and EMA

• Assess financial performance before and after privatisation

• Statistically significant (95% confidence level) for 12 out of 28 ratios

Results of Dependent t-Test

Data Envelopment Analysis

• DEA scores are overall indices of (in)efficiency of the individual sample airports relative to each other

• Financial efficiency model was used• Consistent findings of the two t-tests are

confirmed by the results of total factor productivity in terms of DEA

• Indicates econmies of scale < 4 mill terminal passengers per annum

• Diseconomies of scale > 4 mill

Data Envelopment Analysis

• VRS: small and medium-sized sample airports operate under increasing returns to scale (IRS)

• VRS: airports and airport systems with traffic volumes in excess of > 3-4 mill terminal passengers operate under either constant (CRS) or decreasing returns to scale (DRS)

Mean Annual DEA Scores

Data Envelopment Analysis

• Scale efficiency value of 1 no effect of scale size on productivity

• The lower the value of scale efficieny under 1, the more adverse the impact of scale size

• Airport sample trend of decreasing scale efficiency in parallel to increasing traffic volume

Mean Annual DEA Scores per Ownership Group (VRS)

DEA Scores (Results)

• Higher efficiency in terms of DEA for partially and fully privatised airports

Value Driver Scorecard of Sample Airports

The Roots of Key Value Drivers and their Effect on Returns

Balance Sheet Structure of Sample Airports 1990 – 1999 (Mean Values)

Conclusion

• DEA scores based on financial variables provide airport management with a useful tool to identify their relative position within the airport sector

• PFP and FRA useful for investor provide indications of the relative attractiveness of an airport as an potential investment

• Economically meaningful and statiscally significant differences between publicly owned and privatised airports for the vast majority of tested measures