Systematic peak-load pricing, congestion premia and demand diverting: Empirical evidence

Escobari, Diego

doi:10.1016/j.econlet.2009.01.019

Cited by 28 publications

(21 citation statements)

References 13 publications

(19 reference statements)

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“…This is also the departure date with the highest average fares ($279.85, see column 5, Table 2). Higher fares associated with more congestion known ex-ante is evidence of systematic peak-load pricing, as previously documented in Escobari (2009). It would be reasonable to observe that a more responsive demand is associated with more congestion, but the estimates in Table 5 show that there is little evidence that this is the case.…”

Section: Resultscontrasting

confidence: 39%

The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights

Escobari¹,

Mellado²

2014

Advances in Airline Economics

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This paper estimates the demand for flights in an international air travel market using a unique dataset with detailed information not only on flight choices but also on contemporaneous prices and characteristics of all the alternative non-booked flights.The estimation strategy employs a simple discrete choice random utility model that we use to analyze how choices and its response to prices depend on the departing airport, the identity of the carrier, and the departure date and time. The results show that a 10% increase in prices in a 100-seat aircraft throughout a 100-period selling season decreases quantity demanded by 7.7 seats. We also find that the quantity demanded is more responsive to prices for Delta and American, during morning and evening flights and that the response to prices changes significantly over different departure dates.

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Section: Resultscontrasting

confidence: 39%

The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights

Escobari¹,

Mellado²

2014

Advances in Airline Economics

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“…Using ex‐ante known demand intensities, Escobari [] estimates a congestion premia associated with systematic peak‐load pricing.…”

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confidence: 99%

Dynamic Pricing, Advance Sales and Aggregate Demand Learning in Airlines

Escobari¹

2012

The J Industrial Economics

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This paper uses a unique U.S. airlines panel data set to empirically study the dynamic pricing of inventories with uncertain demand over a finite horizon. I estimate a dynamic pricing equation and a dynamic demand equation that jointly characterize the adjustment process between prices and sales as the flight date nears. I find that the price increases as the inventory decreases, and decreases as there is less time to sell. Consistent with aggregate demand learning and price adjustment, demand shocks have a positive and much larger effect on prices than the positive effect of anticipated sales.

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“…Differences in fares across airports might be the results of the internalization of airport congestion costs (see, e.g., Brueckner, 2002;and Mayer and Sinai, 2003) or additional differences in costs or different consumer types across airports. From panel D, we observe that average fares are higher in the afternoon and in the evening, perhaps as a result of systematic peak-load pricing at the flight level (see, e.g., Escobari, 2009). …”

Section: Description and Discussion Of The Datamentioning

confidence: 93%

Airport, airline and departure time choice and substitution patterns: An empirical analysis

Escobari

2017

Transportation Research Part A: Policy and Practice

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This paper uses the random-coefficients logit methodology that controls for potential endogeneity of prices and allows for general substitution patterns to estimate various demand systems. The estimation takes advantage of an original ticket-level revealed preference data set on travels from the New York City area to Toronto that contains prices and characteristics of not only flight choices but also of all non-booked alternative flights. Consistent with having higher valuations, our results show that travelers buying closer to departure have a higher utility of flying. Moreover, consumers' heterogeneity decreases as the flight date nears. At the carrier level, we identify which carriers have more price-sensitive consumers and which carriers face greater competition. In addition, the results suggest that our multi-airport metropolitan area can be considered as a single market and that JFK and Newark are relatively closer substitutes. Overall, consumers are more willing to switch to alternative carriers than between airports or departure times.

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Systematic peak-load pricing, congestion premia and demand diverting: Empirical evidence

Cited by 28 publications

References 13 publications

The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights

The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights

Dynamic Pricing, Advance Sales and Aggregate Demand Learning in Airlines

Airport, airline and departure time choice and substitution patterns: An empirical analysis

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