Benchmarking Airports: A Case Study on Alternative Valuation - - PowerPoint PPT Presentation

1

Benchmarking Airports: A Case Study on Alternative Valuation Approaches

5th Conference on Applied Infrastructure Research Berlin 7 October 2006

• Dr. Hans-Arthur Vogel

Hans-ArthurVogel@t-online.de

TU TU

Berlin University of Technology

WIP / CNI

2

Conventional Benchmarking Techniques The Principles of Company Value Traditional Valuation Measures I & II An Airport Business Model The Roots of Key Value Drivers Frame of Reference: The Airport Value Tree The three Drivers of Return A Driver-Based Valuation Approach: Framework for Return Profiles Case Study: The Sample; Performance Profiles, B/S Structures The Driver-Based Valuation Approach: Framework & Drivers Revisited Positioning of Sample Airports per Ownership Criteria Return Profiles of Sample Airports I - III Positioning of Airports Before and After Partial or Full Privatisation Managing the Value of Airports Conclusions

Outline

3

Analysis of Partial Factor Productivity, PFP Financial Ratio Analysis, FRA

Assessment of Total Factor Productivity, TFP

Data Envelopment Analysis, DEA Conventional Benchmarking Techniques

4

As with any other business, an airport is valued on the basis

• f 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 of future dividends Cash Flow Earnings Firm Value = NPV at cost of capital Price = Multiples reflecting growth Liquidation

Going Concern Accounting Distribution

Supply Demand

Dividends Assets Realizable Value Price = NPV of future dividends Cash Flow Earnings Firm Value = NPV at cost of capital Price = Multiples reflecting growth Liquidation

Going Concern Accounting Distribution

The Principles of Company Value

5

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)

6

Traditional Valuation Measures II

ADP 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

• utst. (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%

7

A business model is essentially the method of doing

business by which a company can sustain itself – that is, generate revenue.

Selling the provision of infrastructure (massive capex) and

support services (opex) in the (regulated) marketplace.

Airport Infrastructure & Services Capital Structure GDP / Traffic Demand Regulation / Yield, Profit Return / Share- holder Value Asset Utilization / Investment Operating Efficiency Airport Infrastructure & Services Capital Structure GDP / Traffic Demand Regulation / Yield, Profit Return / Share- holder Value Asset Utilization / Investment Operating Efficiency

An Airport Business Model

8

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

9

Frame of Reference: The Airport Value Tree

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

Illustration derived from the D u Pont chart and M organ Stanley D ean W itter, 2000

Air Traffic Movements Airport Charges Passenger Charges Com m er- cial R evenue A sset Turnover Profit M argin F inancial Leverage R O A (Return

• n

Assets) before T ax Tax Effect A ero- nautical R evenue O ther Incom e Land, Buildings M achinery, Equipm ent W orking C apital Profit & Loss Effect B alance Sheet Effect Passenger Volume Labour E xternal Services, M aterials D eprecia- tion Fixed Assets C urrent Assets R O E (Return

• n

E quity) before Tax R O E (R eturn

• n

E quity) after Tax O perating C osts Total R evenue EBIT (Earnings before Interest and Tax) Total A ssets Air Traffic Movements Airport Charges Passenger Charges Com m er- cial R evenue A sset Turnover Profit M argin F inancial Leverage R O A (Return

• n

Assets) before T ax Tax Effect A ero- nautical R evenue O ther Incom e Land, Buildings M achinery, Equipm ent W orking C apital Profit & Loss Effect B alance Sheet Effect Passenger Volume Labour E xternal Services, M aterials D eprecia- tion Fixed Assets C urrent Assets R O E (Return

• n

E quity) before Tax R O E (R eturn

• n

E quity) after Tax O perating C osts Total R evenue EBIT (Earnings before Interest and Tax) Total A ssets

10

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 Assets

• Shareh. 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

11

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) Financial Leverage

A Driver-Based Valuation Approach: Framework for Return Profiles

12

ABZ BFS BHX BRS CWL EDI EMA GLA AMS BRU ADR NAP ADP MRS CPH BSL GVA ZRH CGN DUS FRA HAJ HAM VIE LHR LBA LGW LPL LTN MAN NCL STN

31 individual airports, 4 airport groups across Europe; different locations, sizes, regulatory regimes etc., and different ownership structures time series of ten years for the period 1990-1999/´00

BER RIA BAA

Case Study: Sample Airports

13

Performance Profiles of Sample Airports

To ta l S a m ple A irpo rts 8% 31% .468 32 314% 48% ROS EBITDA Margin As s ets Turno ver WLU/To tal As s ets Financial Leverage Net As s ets / To tal As s ets P ublic ly Owne d A irpo rts 40% 405% 36 .550 31% 6% ROS EBITDA Margin As s ets Turno ver WLU/To tal As s ets Financial Leverage Net As s ets / To tal As s ets P a rtia lly P riv a tis e d A irpo rts 15% 35% .494 30 228% 51% ROS EBITDA Margin As s ets Turno ver WLU/To tal As s ets Financial Leverage Net As s ets / To tal As s ets F ully P riv a tis e d A irpo rts 11% 31% .291 25 172% 62% ROS EBITDA Margin As s ets Turno ver WLU/To tal As s ets Financial Leverage Net As s ets / To tal As s ets

14

Balance Sheet Structures of Sample Airports

Publicly owned airports assume more debt relative to their shareholders‘ funds, resulting in higher gearing and financial leverage, compensating for the comparatively low ROA generated by the business. Financial leverage is the use of fixed financing costs; it is acquired by choice, used to increase the return to common shareholders.

Curr.A. 19% Fixed Assets 81% Shareh. Funds 46% Debt 54% Curr.A. 23% Fixed Assets 77% Shareh. Funds 37% Debt 63% Curr.A. 23% Fixed Assets 77% Shareh. Funds 51% Debt 49% C.A.9% Fixed Assets 91% Shareh. Funds 62% Debt 38%

Total Sample Publicly Owned Partially Privatised Fully Privatised

15

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) Financial Leverage

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 and
• 3. capital structure financial leverage.

16

ROA and ROE of publicly owned, partially and fully privatised

airports are based on considerably different intensities of the same key drivers.

• 6%

0% 6% 12% 18% 24% 30% 0.250 0.320 0.390 0.460 0.530 0.600 0.670 Asset Turnover (times) ROS

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 Airports per Ownership Criteria

17

Return Profiles of Sample Airports I

Publicly owned airports are characterized by comparatively high asset utilization 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 1990 366% 1992 434% 1998 300% 1991 439% 1999 326% 1997 316% 1995 428% 1996 397% 1993 350% 1994 606% 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) ROS

18

Partially privatised airports are characterized by medium high asset utilization 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 1997 275% 1999 281% 1991 140% 1990 144% 1992 170% 1998 268% 1996 168% 1995 172% 1994 185% 1993 163% 0% 5% 10% 15% 20% 25% 30% 0.300 0.375 0.450 0.525 0.600 0.675 Asset Turnover (times) ROS

19

Fully privatised airports, in contrast, are characterized by comparatively low 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 1990 140% 1993 195% 1999 180% 1998 171% 1996 179% 1997 176% 1995 163% 1994 165% 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

20

Positioning of Paired-Sample Airports Before and After Partial or Full Privatisation

The positioning of sample airports changes significantly with an increase in the degree of privatisation: Capex grows faster than revenue decreased asset utilization / capital productivity and asset turnover. Operating margin and ~ efficiency increase on average increased return on sales. Financial leverage decreases higher equity commitment !

After Privatisation 226% Before Privatisation 409% 0% 5% 10% 15% 20% 25% 0.480 0.510 0.540 0.570 Assset Turnover (times) ROS

21

Managing the Value of Airports

Maximising capacity utilization appears to be the formula for

success in the airport business. This requires project management and financial skills for a thorough phasing of capex and optimisation of the use of debt facilities and equity supply. ‘Sweating’ the assets includes efficient management of traffic flows and optimal allocation of capital, finally maximizing the effectiveness of investment spending, return rates and shareholder value. Criteria for (strategic) investments: growth and commercial potential, potential for margin growth, existing capacity, appropriate regulatory framework and capital finance structure.

22

Conclusions

Airport economics are dominated by the investment cycle;

and although footed on the same business model, not all airport earnings are created equal. Airports should not be valued with a single multiple but with measures recognising the key features of success of their business model and value tree. It is useful to analyse the intensity and changes of the key drivers: return on sales, asset turnover and financial leverage. Identifying the distinct differences in terms of operating efficiency, capital productivity and capital structure is the added value of this alternative, driver-based valuation approach.

23

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 views mentioned herein should not be attributed to his position within the Fraport group.

Hans-ArthurVogel@t-online.de

TU TU

Berlin University of Technology

WIP / CNI