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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)

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Presentation Transcript
content
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
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
methodology
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
results of independent t test
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 dependent 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
data envelopment analysis
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 analysis1
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)
data envelopment analysis2
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
dea scores results
DEA Scores (Results)
  • Higher efficiency in terms of DEA for partially and fully privatised airports
conclusion
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