... K @,O) 0.707 = x^0.25T0.25 (om Firm 1 L Consumer A xl Note: Copyright 1991, 19% by Joseph 1. ... more ... K @,O) 0.707 = x^0.25T0.25 (om Firm 1 L Consumer A xl Note: Copyright 1991, 19% by Joseph 1. Daniel. All rights reserved. Reprinted with permission of the author. Page 8. oo-Micro! consists of four main parts: MicroModels, MicroGruphs, Micro-Lessons, and MicroExercises. ...
Specification tests using stochastic bottleneck models of airport congestion investigate whether ... more Specification tests using stochastic bottleneck models of airport congestion investigate whether dominant airlines internalize or ignore self-imposed delays at twenty-seven major US airports. Data on flight times determine the airport's landing and takeoff delays for every minute of operation during peak travel days. Dynamic congestion functions based on stochastic-queuing theory separately identify delays that aircraft experience directly, impose internally on their airline's other aircraft, or impose externally on other airlines. Specification tests largely reject internalization and fail to reject non-internalization by dominant airlines. Optimal pricing should value all time using non-dominant aircraft time values and treat all delays as external.
We compare three empirical models of airport congestion pricing: a standard peak-load-pricing mod... more We compare three empirical models of airport congestion pricing: a standard peak-load-pricing model with econometrically estimated demand and delay functions (Morrison [7], Morrison and Winston [8]); a deterministic bottleneck model with traffic adjusting intertemporally to congestion prices (Vickrey [9], Arnott et al. [2]); and a bottleneck model with time-dependent stochastic queuing (Daniel [4]). When implemented using Daniel's airport traffic data, the models produce similar traffic patterns under weight-based pricing, but differ significantly under congestion pricing. We conclude that structural modeling of stochastic traffic, queues, and intertemporal substitution is necessary to produce realistic responses of traffic patterns to congestion pricing.
Imposition of airport congestion pricing redistributes welfare among commercial, regional, and ge... more Imposition of airport congestion pricing redistributes welfare among commercial, regional, and general aviation. This article extends Daniel's [Econometrica63, 327–370 (1995)] stochastic-bottleneck model with dynamically adjusting traffic rates, queuing delays, and congestion fees to include elastic demand, heterogeneous operating time preferences, and heterogeneous layover and queuing time values. Using parameters from Minneapolis-St. Paul airport, simulations of congestion pricing determine its effects on equilibrium traffic patterns, queuing delays, schedule delays, airport revenues, and social welfare. Gains by commercial aviation, common travelers, and airport authorities exceed losses by general and regional aviation. The article evaluates several price-and-rebate programs and proposes several that are self-financing and Pareto improving.
... K @,O) 0.707 = x^0.25T0.25 (om Firm 1 L Consumer A xl Note: Copyright 1991, 19% by Joseph 1. ... more ... K @,O) 0.707 = x^0.25T0.25 (om Firm 1 L Consumer A xl Note: Copyright 1991, 19% by Joseph 1. Daniel. All rights reserved. Reprinted with permission of the author. Page 8. oo-Micro! consists of four main parts: MicroModels, MicroGruphs, Micro-Lessons, and MicroExercises. ...
Specification tests using stochastic bottleneck models of airport congestion investigate whether ... more Specification tests using stochastic bottleneck models of airport congestion investigate whether dominant airlines internalize or ignore self-imposed delays at twenty-seven major US airports. Data on flight times determine the airport's landing and takeoff delays for every minute of operation during peak travel days. Dynamic congestion functions based on stochastic-queuing theory separately identify delays that aircraft experience directly, impose internally on their airline's other aircraft, or impose externally on other airlines. Specification tests largely reject internalization and fail to reject non-internalization by dominant airlines. Optimal pricing should value all time using non-dominant aircraft time values and treat all delays as external.
We compare three empirical models of airport congestion pricing: a standard peak-load-pricing mod... more We compare three empirical models of airport congestion pricing: a standard peak-load-pricing model with econometrically estimated demand and delay functions (Morrison [7], Morrison and Winston [8]); a deterministic bottleneck model with traffic adjusting intertemporally to congestion prices (Vickrey [9], Arnott et al. [2]); and a bottleneck model with time-dependent stochastic queuing (Daniel [4]). When implemented using Daniel's airport traffic data, the models produce similar traffic patterns under weight-based pricing, but differ significantly under congestion pricing. We conclude that structural modeling of stochastic traffic, queues, and intertemporal substitution is necessary to produce realistic responses of traffic patterns to congestion pricing.
Imposition of airport congestion pricing redistributes welfare among commercial, regional, and ge... more Imposition of airport congestion pricing redistributes welfare among commercial, regional, and general aviation. This article extends Daniel's [Econometrica63, 327–370 (1995)] stochastic-bottleneck model with dynamically adjusting traffic rates, queuing delays, and congestion fees to include elastic demand, heterogeneous operating time preferences, and heterogeneous layover and queuing time values. Using parameters from Minneapolis-St. Paul airport, simulations of congestion pricing determine its effects on equilibrium traffic patterns, queuing delays, schedule delays, airport revenues, and social welfare. Gains by commercial aviation, common travelers, and airport authorities exceed losses by general and regional aviation. The article evaluates several price-and-rebate programs and proposes several that are self-financing and Pareto improving.
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