# Authors: Alan Carlin and R.E. Park (1970) Presented by: Jared Hayden.

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Authors: Alan Carlin and R.E. Park (1970) Presented by: Jared Hayden

Leading up to 1970, quickly growing demand for airport runways began to exceed the amount of available capacity in some major cities Resulted in intolerably long delays and additional costs to airlines Most notably, LaGuardia airport in New York City Chicago and Washington experienced similar problems The study looks at pricing and administrative mechanisms to help alleviate the congestion at peak times

Paper written in 1970 using data from April 1967 through March 1968 (1 full year) Paper Examines New Yorks LaGuardia Airport Study divided into 2 sections 1. Develops a model for marginal delay (congestion costs) for La Guardia 2. Explores the use of congestion tolls and administrative controls to solve the short-term congestion problem Examines the possibilities of full marginal cost pricing, proportional cost pricing, administrative measures, and combinations of each

What are the congestion costs that an additional user would impose on others? Equivalently, what would the saving to others be if one fewer plane were to use LaGuardia? During a busy period, each user imposes some delay on following users until the end of the busy period Equivalently, an additional user shoves users behind him back one space in the queue until the queue dissipates Paper aims to model such airport activity

C i = delay costs imposed by a user of type i on other users at time t B(t) = remaining minutes in busy period i = specifies type of plane and whether its landing or taking off m = different types of use S i = absolute service times N i = number of operations from each type S i and N i are transformed to s i = S i /S 1 and n i = N i /N 1 Relative terms more feasible to estimate Four types of operations: i=1, air carrier landings i=2, air carrier takeoffs i=3, general aviation landings i=4, general aviation takeoffs Divide by S 1 N 1 *C i / B = marginal cost per minute of remaining busy period

To simplify estimation, many daily fluctuations are not taken into account by the data i.e. ns, ss and cs all vary throughout day Carlin and Park to not believe the added complexities would add significant precision to model Thus, the model aims to estimate all values as yearly averages The lone exception is B(t), which is estimated for each hour of the day.

Traffic proportions, n i : obtained from aggregate traffic statistics available for 1967 Corrected for usage of non-duty runways Relative service times, s i : derived from airport capacity manual prepared by Airborne Instruments Laboratory Cost of delay to airplane owners and passengers, c i : Estimate of costs are based on American Airlines figures for airplanes similar to those at LaGuardia Assumes \$6 per hour for air carrier passenger time value and \$12 per hour for more affluent general aviation passenger time value

Average remaining busy period, B(t) : American Airlines and United Airlines data used to relate delays experienced from individual flights Used to determine hourly busy periods of the day Determination of B(t) allows for marginal delay costs per minute of remaining busy period, C i /B(t), to be calculated Full marginal delay costs : Attained by multiplying the costs per minute of remaining busy period by the busy period estimates. Result : Shows average values of the delay costs imposed on other users by incremental operations at any time of the day

Air Carriers have heavier traffic and longer service times Landings more expensive than takeoffs Air carriers have much greater marginal cost of delays Marginal cost of delay per minute of remaining busy period shows the greater marginal cost of general aviation activity during peak periods

Column 1 shows B(t) Airport most congested between 1500-1600 Estimates suggests that one additional air carrier arrival between 1500- 1600 would impose a delay cost of greater than \$1000 on other users

Flight fees at LaGuardia based on airplane weight \$5 minimum for each take off and no charge for landing (general aviation usually minimum) Air carriers pay fees between \$50 and \$150, depending on weight Fee structure leads to two major inefficiencies Inefficiently large amount of general aviation traffic \$5 dollar fees could cause marginal congestion costs upwards of 200 times that amount Airline passenger loads are inefficiently low LaGuardia load factors averaged 59.4% in 1967

August 1, 1968: LaGuardia airport raised minimum fees to \$25 for flights between 0800 and 1000 (Monday-Friday) and between 1500 and 2000 every day Estimated that this measure reduced general aviation by 40% during such busy periods General aviation operations are of low value when compared to relative congestion cost they impose on others With present airfare, airlines can cover costs with low load factors Incentive to schedule more flights to improve service Less frequent service at higher load factors would be more efficient

Would be extremely difficult, if not impossible to find equilibrium prices Would have to charge an increasing percentage of full marginal cost pricing until target was hit Equilibrium marginal cost prices would result in very efficient runway use Exclude low value general aviation traffic Increase carrier load factors to a more efficient level

Does not appear practical at LaGuardia in short run Present fees determined by lease agreements between Port Authority and individual airlines Airlines could shutdown fee increases Long-run may yield benefits Reduced operating costs with less traffic and lower operating costs May take long adjustment period to yield benefits In reality, airline opposition would quickly dismiss the implementation of full marginal cost pricing

Limit total airline runway use payments to align with present lease agreements Change fees in such a way that fees are levied so that fees during any hour would be proportional to those that would prevail under full marginal cost pricing Hypothetical estimate collections with full marginal cost flight fees used to compute proportional cost fees computed (tables 2/3) Use percentages to allocate current level of runway prices proportionate to marginal cost pricing

Can observe much high runway fees during busy periods of the day Costs much higher for general aviation, who generally pay minimum fees (shown in far right columns)

Limit low value general aviation traffic during busy hours Fees as much as 5x higher during busy periods Pricing scheme would probably eliminate almost as much general aviation traffic as full marginal cost prices Little or no effect on inefficiently low load factors.

Airlines may pay more or less when compared to present fees The more airline with lower costs, the more likely pricing scheme accepted Local service carriers receive major cost increases Costs Partially offset by less delay fees Large airlines may be willing to subsidize local service carriers

Restrict both general aviation and air carriers to lower levels of operation Hard to design efficient administrative measure to determine respective levels of operation No guarantee that schedules will go to highest value user

Issue property rights in schedule slots for particular hours A free market approach to allocating slots would allocate them to highest-value user Feasible to implement to airlines All would share gains from efficiency In practice, a pricing scheme more likely effective in controlling nonscheduled users

Policy consisting of both proportional marginal cost pricing and administrative limits Proportional prices: exclude low value general aviation users Schedule limits: would increase airline load factors Most benefits of full marginal cost pricing, but more feasible to implement

Equilibrium marginal cost pricing does not appear to be a feasible alternative Proportional marginal cost pricing offers similar efficiency advantages sans lowered load factors without many of the headaches of implementation Combining proportional marginal cost pricing with administrative limits seems to be the most implementable measure that addresses both general aviation reduction during peak times and increases in load factors to more efficient levels

Questions?

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