This paper uses a unique daily time series data set to investigate the asymmetric response of airline prices to capacity costs driven by demand fluctuations. We use a Markov regime-switching model with time-varying transition probabilities to capture the time variation in the response. The...

This paper shows how an airline monopoly uses refundable and non-refundable tickets to screen consumers who are uncertain about their travel. Our theoretical model predicts that the difference between these two fares diminishes as individual demand uncertainty is resolved. Using an original data...

Prices for the same flight change substantially depending on the time of purchase. This paper uses a unique dataset with round-the-clock posted fares to document significant within-day price variation. Labeling time-variation as discriminatory is difficult because the cost of an unsold airline...

We use unique data sets with round-the-clock posted fares and a regression discontinuity design to identify price discrimination in advance-purchase discounts. Price discrimination increases fares by 14% between two and one week before departure, and by 7.6% between three and two weeks to...

Dynamic pricing and demand learning play an important role in airlines because (1) in low demand flights unsold tickets are of little value after departure, and (2) in high demand flights carriers may forgo important profits if the flight sells out and some relatively high willingness-to-pay...

We develop a model to derive an optimal price for a bundle of two goods when buyers are risk averse and uncertain about the valuation of each good. In theory, the optimal bundle price depends not only on the probability of a positive valuation of each good, but also on the correlation between...