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Airport Cash Flows Soar Above the Clouds

In many European and Asian countries airports are operated by public companies under long-term concessions. Airports have two distinct businesses and three general regulatory models that drive the overall attractiveness of the concession. The core transportation business is driven by landing fees and ramp handling fees charged to airlines. Airports also have a commercial business driven by lease revenues from retailers located in the airport. The regulatory models reflect an allowed rate of return applying either to the transportation business (dual till), both businesses combined (single till) or a hybrid model.
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The core transportation business is driven by the scale of the airport and the quality of the airline tenants. A large international airport in a larger city centre will see higher passenger traffic and greater fee revenues. However, most countries have a dominant domestic airline and the economic health of that airline will also impact the level of fee revenue the airport can generate. The ideal airport will see high passenger traffic from business and leisure travellers who are visiting the city or connecting through the airport. The ideal airport will also have a diversified tenant roster of airlines with a dominant domestic carrier that is well-capitalized with an efficient fleet of airplanes and strong labour relations.
How the Baggage Handling System Works


Since starting commercial operations in 2019, the international terminal at Delhi airport has handled more than 89 million bags with only a 0.3% chance of a bag being lost in the system. What is the science behind these efficiency levels? Mint takes a look at how the baggage handling system (BHS), or the so-called mangle of steel at the Indira Gandhi International Airport Terminal 3, functions.
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Check in: A bar-coded sticker is generated when passengers check in with their baggage. The system can sort the baggage based on the information decoded from the 10-digit International Air Transport Association (IATA) license plate read into the system, and the bar code on bags, which contains the information on baggage origin, destination, passenger, flight and the airlines code.
If a bag is cleared after the first X-ray screening, it is diverted towards the sorting area. The system uses high-speed conveyance and automatically slows down where baggage has to be examined by automated X-ray systems.
Five-step scanning: If not cleared, the system diverts the bag to the second level of screening. If the level-two operator thinks there are suspicious objects in the bag, it is delivered by the operator for level-3 CTX screening machine, which slices the picture of the bag into multiple pieces. This system has the capability of accepting or rejecting the bag. If the bag is accepted, it goes to the destination carousel.
A sophisticated set-up of 35 fully automated detection systems, more than 50 remote operating stations with enhanced imagery and high-tech tomography X-rays for alarm resolution are used by trained security operators. If the bag is not cleared in level-three screening, it goes to an operator, who is trained to analyse the images. These operators accept or reject the bag. If they reject the luggage, it goes to level four, where level-three images are already available. If operators at this level feel there are suspicious objects in the luggage, they call the passengers, and examine the bag in front of them.
There are two levels of induction points to the sorting system. The gabs that come from the scanners go directly to the tray due to precision engineering and programming in the system.
A programme makes sure this tray automatically tilts, and the bag goes to the spiral shute, which leads it to the destination carousel.
Sorting: Four fully automated tilt tray sorting machines moving at a speed of 1.9 meters per second constantly receive and release bags to sort destinations. These machines then sort the mix of security-cleared baggage to 12 different destinations assigned for different flights.
An algorithm is fed into the system to see when to accept or reject a bag. There is a 270 degrees infrared sensor installed at a point on the baggage carousel where it reads the bag tag, and sends a signal to the processor, which takes a decision in micro seconds to send it to a certain destination baggage carousel.
At the backhouse, officials read the destination codes on the baggage with manual bar code readers. With the help of a baggage reconcilliation system, they load the bags on wheeled platforms, and then put them on trolleys that take the luggage to the plane.
Source: Delhi International Airport (P) LTD.
Airport concessions are generally awarded for 50 years or more. However, the economics of the concession are usually adjusted every 5 years. Airports are normally regulated under a model that permits them to earn an “allowed rate of return” on their Regulated Asset Base (“RAB”). The RAB is calculated based on the assets the firm owns that directly contribute to the regulated operations of the business. The allowed rate of return is driven by bond yields, equity risk premiums and the posture of the regulator. The ideal airport will grow its RAB by investing cash flow to drive revenue growth (additional runways, retail locations and gates) and cost savings (automated baggage handling, newer equipment, digitization). The ideal airport would also enjoy a favourable regulatory environment allowing the airport to earn higher allowed rates of return.
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There are three different models the regulator can apply to an airport. Single Till models mean that the transportation and commercial businesses are both captured in the allowed rat of return. This model does not provide much incentive for the airport operator to invest in the asset since the allowed rate of return caps the ability of the airport operator to recoup a return on their investment. Dual Till models mean that the transportation business is subject to the allowed rate of return while the  commercial business is unregulated. This model provides great incentive to the airport operator to invest in both businesses since it can earn a strong return on these investments. Many regulators apply a hybrid model where a specific portion of the commercial business’ returns are used to subsidize the transportation business. The ideal airport would operate under a Dual Till regulatory regime with a favourable regulator that provides the airport with incentives to invest in both the transportation and commercial businesses.

Regulated Asset Base Model

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Source: MAVCOM
Aena S.A. (“Aena”) is the holding company that operates the majority of Spain’s airports, the London-Luton airport (51% ownership) and airports in Mexico (12), Jamaica (2) and Colombia (2). The company has a portfolio of 46 airports and two heliports, which cumulatively handled 280M passengers in 2018, making it the largest airport operator globally. The Spanish airports are operated in perpetuity, with the heliports operated under concession. The airports have different characteristics, from hub to touristic to regional aviation assets and this leads to a varied mix of airline presence and demand seasonality across the portfolio.
In 2018 Aena enjoyed 5.7% passenger traffic growth which fueled 7.3% revenue growth and 7.0% dividend growth. The business generated a 61.5% EBITDA margin in 2018 but the commercial business EBITDA margin was 83.0%, demonstrating the attractiveness of the Dual Till regulatory model in Spain. Aena has consistently earned a return in excess of its allowed rate of return, reflecting strong passenger traffic and rising passenger spend at their airports. Continued capital investment should drive RAB growth and offset any slowing in traffic growth driven by Brexit.
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Certain statements in this document are forward-looking. Forward-looking statements (“FLS”) are statements that are predictive in nature, depend upon or refer to future events or conditions, or that include words such as “may,” “will,” “should,” “could,” “expect,” “anticipate,” “intend,” “plan,” “believe,” or “estimate,” or other similar expressions. Statements that look forward in time or include anything other than historical information are subject to risks and uncertainties, and actual results, actions or events could differ materially from those set forth in the FLS. FLS are not guarantees of future performance and are by their nature based on numerous assumptions. Although the FLS contained herein are based upon what Starlight Capital and the portfolio manager believe to be reasonable assumptions, neither Starlight Capital nor the portfolio manager can assure that actual results will be consistent with these FLS. The reader is cautioned to consider the FLS carefully and not to place undue reliance on FLS. Unless required by applicable law, it is not undertaken, and specifically disclaimed that there is any intention or obligation to update or revise FLS, whether as a result of new information, future events or otherwise.

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