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.
We show how a monopoly airline uses two ticket types, refundable and non-refundable, to screen consumers with different willingness to pay. Our theoretical model suggests that the difference between these two fares consists of refundability value and price discrimination, and the fare difference diminishes as risk-averse passengers learn about their individual demand uncertainty. Using an original dataset, we find that, after controlling for unobserved seat-and flight-specific characteristics, the empirical evidence from the U.S. airline industry supports our theory.
This paper investigates the role of virtual integration of financial markets on stock market return co-movements. In May of 2011 the Chilean, Colombian, and Peruvian stock markets virtually integrated their stock exchanges and central securities depositories to form the Latin American Integrated Market (MILA). We utilize the dynamic conditional correlation model propose by Engle (2002) to identify a statistically significant positive correlation between these markets.Moreover, we find strong evidence that the creation of the MILA increased the levels of dynamic correlation between stock returns. A higher correlation was also found during the dot-com bubble and the 2007 financial crises. Our results imply a decline in gains from international diversification by holding portfolios consisting of diverse stocks of these countries.
This paper tests the empirical importance of the price dispersion predictions of the Prescott-Eden-Dana (PED) models. Equilibrium price dispersion is derived in a setting with costly capacity and demand uncertainty where different fares can be explained by the different selling probabilities. The PED models predict that a lower selling probability leads to a higher price. Moreover, this effect is larger in more competitive markets. Despite its applications to several important market phenomena, there exists little empirical evidence supporting the PED models, mostly because of the difficulty of coming up with an appropriate measure of the selling probabilities. Using a unique panel of U.S. airline fares and seat inventories, we find evidence that strongly supports both predictions of the models. After controlling for the effect of aggregate demand uncertainty on fares, we also obtain evidence of second degree price discrimination in the form of advance-purchase discounts.
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