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Benchmarking Airports:A Case Study on Alternative Valuation Approaches

5th Conference on Applied Infrastructure ResearchBerlin

7 October 2006

Dr. Hans-Arthur Vogel

Hans-ArthurVogel@t-online.de

TUBerlin University of Technology

WIP / CNI

2

Conventional Benchmarking TechniquesThe Principles of Company ValueTraditional Valuation Measures I & IIAn Airport Business ModelThe Roots of Key Value DriversFrame of Reference: The Airport Value TreeThe three Drivers of ReturnA Driver-Based Valuation Approach: Framework for Return ProfilesCase Study: The Sample; Performance Profiles, B/S StructuresThe Driver-Based Valuation Approach: Framework & Drivers RevisitedPositioning of Sample Airports per Ownership CriteriaReturn Profiles of Sample Airports I - IIIPositioning of Airports Before and After Partial or Full PrivatisationManaging the Value of AirportsConclusions

Outline

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Analysis of Partial Factor Productivity, PFP

Financial Ratio Analysis, FRA

Assessment of Total Factor Productivity, TFP

Data Envelopment Analysis, DEA

Conventional Benchmarking Techniques

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As with any other business, an airport is valued on the basisof its current and expected revenues, earnings and cash flow.

Illustration derived from Elton & Gruber, 1995; Pike & Neale, 1996

Supply Demand

Dividends

Assets Realizable Value

Price = NPV offuture dividends

Cash Flow

Earnings

Firm Value = NPVat cost of capital

Price = Multiplesreflecting growth

Liquidation

Going Concern

Accounting

Distribution

Supply Demand

Dividends

Assets Realizable Value

Price = NPV offuture dividends

Cash Flow

Earnings

Firm Value = NPVat cost of capital

Price = Multiplesreflecting growth

Liquidation

Going Concern

Accounting

Distribution

The Principles of Company Value

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Traditional Valuation Measures I

Share price performance, relative to local market

Price / earnings (P/E) ratio

Earnings per share (EPS)

Price / cash flow ratio (P/CF)

Price / cash earnings (P/CEPS)

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Traditional Valuation Measures IIADP as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend(EUR) 11/08/06 outst. (m) (in €m) EBITDA (x) Margin EBITDA (x) Yield 47.18 Dec 05A 99 4,671 - 3.6 30% 11.8 25.9 1.4% Mkt cap Dec 06E 99 4,671 3.0 3.4 33% 11.2 26.8 1.9% 4,671(m) Dec 07E 99 4,671 - 3.2 33% 10.4 24.8 2.0% BAA * as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend (GBP/p) 08/06 outst. (m) (€m) EBITDA (x) Margin EBITDA (x) Yield 933 Mar 06A 1,076 14,682 - 6.8 46% 12.9 19.7 2.4 Mkt cap Mar 07E 1,076 14,682 5.5 7.1 45% 15.7 21.0 2.6 10,038(m) Mar 08E 1,076 14,682 - 6.7 46% 14.5 18.8 2.6 CPH as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend(DKK) 11/08/06 outst. (m) (€m) EBITDA (x) Margin EBITDA (x) Yield 1,830 Dec 05A 8 1,962 - 6.7 53% 13.7 22.3 4.7% Mkt cap Dec 06E 8 1,962 2.5 6.5 52% 12.6 20.4 3.6% 14,640(m) Dec 07E 8 1,962 - 6.4 55% 12.1 18.8 2.7% FRA as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend(EUR) 11/08/06 outst. (m) (€m) EBITDA (x) Margin EBITDA (x) Yield 57.10 Dec 05A 91 5,196 - 2.5 25% 9.9 31.4 1.6% Mkt cap Dec 06E 91 5,196 0.8 2.4 26% 9.3 26.9 1.9% 5,196(m) Dec 07E 91 5,196 - 2.3 26% 8.7 24.0 2.1% VIE as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend(EUR) 11/08/06 outst. (m) (€m) EBITDA (x) Margin EBITDA (x) Yield 61.38 Dec 05A 21 1,289 - 3.2 36% 8.7 17.3 3.3% Mkt cap Dec 06E 21 1,289 0.5 3.1 38% 7.9 17.2 3.3% 1,289(m) Dec 07E 21 1,289 - 2.9 39% 7.5 17.1 3.4% ZRH as of shares Mkt cap Net Debt/ EV/Sales EBITDA EV/ P/E Dividend(CHF) 11/08/06 outst. (m) (€m) EBITDA (x) Margin EBITDA (x) Yield 280 Dec 05A 6 1,055 - 5.0 52% 9.6 23.3 0.4% Mkt cap Dec 06E 6 1,055 3.7 4.8 52% 9.2 19.7 1.1% 1,680(m) Dec 07E 6 1,055 - 4.8 53% 9.8 15.2 1.1%

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A business model is essentially the method of doingbusiness by which a company can sustain itself – that is,generate revenue.

Selling the provision of infrastructure (massive capex) andsupport services (opex) in the (regulated) marketplace.

AirportInfrastructure

&Services

CapitalStructure

GDP / TrafficDemand

Regulation /Yield, Profit

Return /Share-holderValue

Asset Utilization /Investment

OperatingEfficiency

AirportInfrastructure

&Services

CapitalStructure

GDP / TrafficDemand

Regulation /Yield, Profit

Return /Share-holderValue

Asset Utilization /Investment

OperatingEfficiency

An Airport Business Model

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The Roots of Key Value Drivers

• Operating Efficiency, i.e.: → ROS - Infl.-Adj. Total Revenue/WLU

- EBITDA Margin - Cash Flow/Total Revenue • Asset Utilization, i.e.: → Asset Turnover - WLU/Total Assets

- Capex/Total Revenue - Capex/Depreciation • Capital Structure, i.e.: → Financial Leverage - Net Assets/Total Assets

- Gearing (Debt/Equity Ratio) - Debt Ratio (Post-Tax)

ROE

ROA

X

X

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Frame of Reference: The Airport Value Tree

The airport value tree is rooted in traffic. It summarizes the relationshipsbetween investment, asset turnover, profit margin and financial leverage.

Illustra tion derived fro m the D u P ont chart and M organ S tanley D ean W itter, 2000

Air

Tra

ffic

Mov

emen

ts A irport C harges

P assengerC harges

C om m er-cia l

R evenue

A ssetTurnover

P rofitM arg in

F inancialL everage

R O A(R eturn

o n A ssets)before

T ax

Ta xE ffec t

A ero-nau ticalR evenue

O th erIn com e

Lan d ,B u ild ings

M ach inery,E qu ipm en t

W ork ingC ap ita l

P ro fit & Loss

E ffect

B a lanceSheetE ffect

Pass

enge

rV

olum

eLabour

E xternal Services,M ateria lsD eprecia-

tion

Fixed A ssets

C u rren t A ssets

R O E(R eturn

o n E qu ity )before

T a x

R O E(R eturn

on E quity )

afterT a x

O peratingC osts

T otal R evenu e

E B IT(E a rn ings

b efo reIn terest

and Tax)

T ota l A ssetsA

ir T

raff

ic M

ovem

ents A irport

C harges

P assengerC harges

C om m er-cia l

R evenue

A ssetTurnover

P rofitM arg in

F inancialL everage

R O A(R eturn

o n A ssets)before

T ax

Ta xE ffec t

A ero-nau ticalR evenue

O th erIn com e

Lan d ,B u ild ings

M ach inery,E qu ipm en t

W ork ingC ap ita l

P ro fit & Loss

E ffect

B a lanceSheetE ffect

Pass

enge

rV

olum

eLabour

E xternal Services,M ateria lsD eprecia-

tion

Fixed A ssets

C u rren t A ssets

R O E(R eturn

o n E qu ity )before

T a x

R O E(R eturn

on E quity )

afterT a x

O peratingC osts

T otal R evenu e

E B IT(E a rn ings

b efo reIn terest

and Tax)

T ota l A ssets

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The three Drivers of Return

Du Pont formula: ROA = Profit Margin x Total Asset Turnover

ROI (ROE) can be split into three components / drivers,

turnover of total assets, return on sales, financial leverage:

Net Income = Total Revenue x Net Income x Total AssetsShareh. Funds Total Assets Total Revenue Shareh. Funds

while asset turnover x return on sales (ROS) = return on assets (ROA),

hence

Enhanced Du Pont equation: ROE = ROA x FinancialLeverage

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ROS (Return on Sales) Net Income over Total Revenue Total Asset Turnover Total Revenue over Total Assets Financial Leverage Total Assets over Shareholders’ Funds The size of the bubble is determined by financial leverage.

The position of the bubble is determined by ROS and asset turnover. Illustration derived from MSDW, 2000

FinLever = 500%ROS = 17%AssetTurn = 0.32

FinLever = 200%ROS = 3% AssetTurn = 0.28

0%

5%

10%

15%

20%

0.280 0.290 0.300 0.310 0.320

Asset Turnover(times)

ROS Improving margins (unit cost fall/unit pricing rises)

Revenue growth lagging investment

Cost growth exceeds revenue growth

Improving asset utili-zation (revenue growth

exceeds investment)

FinancialLeverage

A Driver-Based Valuation Approach:Framework for Return Profiles

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31 individual airports,4 airport groups across Europe;different locations, sizes,regulatory regimes etc., anddifferent ownership structures

time series of ten yearsfor the period 1990-1999/´00

BER

RIA BAA

Case Study: Sample Airports

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Performance Profiles of Sample Airports

To ta l S a m pleA irpo rts

8%

31%

.468

32

314%

48%

ROS

EBITDAMargin

As s e tsTurno ver

WLU/To ta l As s e ts

Financia lLeverage

Net As s e ts /To ta l As s e ts

P ublic ly Owne d A irpo rts

40%

405%

36

.550

31%

6%ROS

EBITDAMargin

As s e tsTurno ver

WLU/To ta l As s e ts

Financia lLeverage

Net As s e ts /To ta l As s e ts

P a rt ia lly P riv a t is e dA irpo rts

15%

35%

.494

30

228%

51%

ROS

EBITDAMargin

As s e tsTurno ver

WLU/To ta l As s e ts

Financia lLeverage

Net As s e ts /To ta l As s e ts

F ully P riv a t is e dA irpo rts 11%

31%

.29125

172%

62%

ROS

EBITDAMargin

As s e tsTurno ver

WLU/To ta l As s e ts

Financia lLeverage

Net As s e ts /To ta l As s e ts

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Balance Sheet Structures of Sample Airports

Publicly owned airports assume more debt relative to their shareholders‘funds, resulting in higher gearing and financial leverage, compensatingfor the comparatively low ROA generated by the business.

Financial leverage is the use of fixed financing costs; it is acquired bychoice, used to increase the return to common shareholders.

Curr.A.19%

FixedAssets

81%

Shareh.Funds46%

Debt54%

Curr.A.23%

FixedAssets

77%

Shareh.Funds37%

Debt63%

Curr.A.23%

FixedAssets

77%

Shareh.Funds51%

Debt49%

C.A.9%

FixedAssets

91%

Shareh.Funds62%

Debt38%

Total Sample Publicly Owned Partially Privatised Fully Privatised

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ROS (Return on Sales) Net Income over Total Revenue Total Asset Turnover Total Revenue over Total Assets Financial Leverage Total Assets over Shareholders’ Funds The size of the bubble is determined by financial leverage.

The position of the bubble is determined by ROS and asset turnover. Illustration derived from MSDW, 2000

FinLever = 500%ROS = 17%AssetTurn = 0.32

FinLever = 200%ROS = 3% AssetTurn = 0.28

0%

5%

10%

15%

20%

0.280 0.290 0.300 0.310 0.320

Asset Turnover(times)

ROS

Improving margins (unit cost fall/unit pricing rises)

Revenue growth lagging investment

Cost growth exceeds revenue growth

Improving asset utili-zation (revenue growth

exceeds investment)

FinancialLeverage

The Driver-Based Valuation Approach:Framework & Drivers Revisited

The three drivers of return are: 1. operating efficiency ROS,2. Asset utilization/capital productivity total asset turnover and3. capital structure financial leverage.

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ROA and ROE of publicly owned, partially and fully privatisedairports are based on considerably different intensities of thesame key drivers.

-6%

0%

6%

12%

18%

24%

30%

0.250 0.320 0.390 0.460 0.530 0.600 0.670

AssetTurnover

(times)

RO S

Publicly Owned Partially Privatised Fully Privatised

Improving margins (unit cost fall/unit pricing rises)

Revenue growth lagging investment

Cost growth exceeds revenue growth

Improving asset utili-zation (revenue growth

exceeds investment)

Financial Leverage

Positioning of Sample Airportsper Ownership Criteria

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Return Profiles of Sample Airports I

Publicly owned airports are characterized by comparatively high assetutilization and financial leverage, and low operating efficiency.

Annual Growth Rates

-40%

-30%-20%

-10%0%

10%20%30%

1999 1998 1997 1996 1995 1994 1993 1992 1991

ROS Asset Turnover Financial Leverage

1990366%

1992434%

1998300%

1991439%

1999326%

1997316%

1995428%

1996397%

1993350%

1994606%3.5%

4.5%

5.5%

6.5%

7.5%

0.480 0.500 0.520 0.540 0.560 0.580 0.600 0.620

Asset Turnover

(times)

RO S

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Partially privatised airports are characterized by medium high assetutilization and financial leverage, as well as high operating efficiency.

Return Profiles of Sample Airports II

Annual Growth Rates

-60%

-30%

0%

30%

60%

90%

1999 1998 1997 1996 1995 1994 1993 1992 1991

ROS Asset Turnover Financial Leverage

1997275%

1999281%

1991140%

1990144%

1992170%

1998268%

1996168%

1995172%

1994185%

1993163%

0%

5%

10%

15%

20%

25%

30%

0.300 0.375 0.450 0.525 0.600 0.675

Asset Turnover(times)

ROS

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Fully privatised airports, in contrast, are characterized by comparativelylow asset utilization and financial leverage, and high operating efficiency.

Return Profiles of Sample Airports III

Annual Growth Rates

-300%

-200%

-100%

0%

100%

200%

1999 1998 1997 1996 1995 1994 1993 1992 1991

ROS Asset Turnover Financial Leverage

1990140%

1993195%

1999180%

1998171%

1996179%

1997176%

1995163%

1994165%

1992 = 184%1991 = 163%-10%

0%

10%

20%

30%

0.260 0.265 0.270 0.275 0.280 0.285 0.290 0.295 0.300 0.305 0.310 0.315

Asset Turnover(times)

ROS

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Positioning of Paired-Sample AirportsBefore and After Partial or Full Privatisation

The positioning of sample airports changes significantly with an increasein the degree of privatisation:

Capex grows faster than revenue decreased asset utilization /capital productivity and asset turnover.Operating margin and ~ efficiency increase on average increasedreturn on sales.Financial leverage decreases higher equity commitment !

After Privatisation226%

Before Privatisation409%

0%

5%

10%

15%

20%

25%

0.480 0.510 0.540 0.570

Assset Turnover (times)

RO S

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Managing the Value of Airports

Maximising capacity utilization appears to be the formula forsuccess in the airport business. This requires projectmanagement and financial skills for a thorough phasing ofcapex and optimisation of the use of debt facilities and equitysupply.

‘Sweating’ the assets includes efficient management oftraffic flows and optimal allocation of capital, finallymaximizing the effectiveness of investment spending, returnrates and shareholder value.

Criteria for (strategic) investments: growth and commercialpotential, potential for margin growth, existing capacity,appropriate regulatory framework and capital financestructure.

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Conclusions

Airport economics are dominated by the investment cycle; and although footed on the same business model, not allairport earnings are created equal.

Airports should not be valued with a single multiple but withmeasures recognising the key features of success of theirbusiness model and value tree.

It is useful to analyse the intensity and changes of the key drivers: return on sales, asset turnover and financialleverage.

Identifying the distinct differences in terms of operatingefficiency, capital productivity and capital structure is theadded value of this alternative, driver-based valuationapproach.

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Benchmarking Airports:A Case Study on Alternative Valuation Approaches

Thank you for your attention,please feel invited for questions !

The author has compiled this presentation in his personal capacity and viewsmentioned herein should not be attributed to his position within the Fraport group.

Hans-ArthurVogel@t-online.de

TUBerlin University of Technology

WIP / CNI