Studies of the Airline Industry
Paper Session
Saturday, Jan. 7, 2017 7:30 PM – 9:30 PM
Hyatt Regency Chicago, Field
- Chair: John Lazarev, New York University
The Value of Relational Adaptation in Outsourcing: Evidence from the 2008 Shock to the US Airline Industry
Abstract
In the airline industry, ex-post adaptation of flight schedules is necessary in the presenceof bad weather conditions. When major carriers contract with independent regionals,
conflicts over these adaptation decisions typically arise. Moreover, the celerity of needed
adjustments requires that adaptation be informal, and hence enforced relationally. In this
paper, we theoretically analyze, and empirically test for, the importance of relational
adaptation in the airline industry. Our model shows that for relational contracts to be selfenforcing,
the long-term value of the relationship between a major and a regional airline
must be at least as large as the regional’s cost of adapting flight schedules across joint
routes. Thus, when facing a shock that forces it to terminate some routes, the major is
more likely to preserve routes outsourced to regional airlines that have higher adaptation
costs, as the value of the major’s relationship with those regionals is larger. We analyze
the evolution of U.S. airline networks around the 2008 financial crisis, and we find that
consistent with our theoretical predictions, regional routes belonging to networks with
worse average weather, and hence higher adaptation costs, were more likely to survive
after the shock.
Dynamic Oligopoly With Financial Friction: The United States Airline Industry After the Deregulation
Abstract
In this paper, we study how financial friction has suppressed airline industry productivity through the aircraft misallocation after the deregulation. We develop an empirical model of dynamic oligopoly with financing de- cisions where endogenous default and the costs of bankruptcy, asset transaction, and equity issuance cause financial friction. The model allows us to jointly investigate firms’ financing and product market decisions. To identify the model, we merge airline financial statements with aircraft ownership, leasing and utilization data and complete aircraft transaction data. We first provide descriptive evidence that is consistent with the model prediction. We then estimate the model to quantify the effects of financial friction by counterfactual simulation. We find that eliminating financial friction increases airlines’ investment by 8% and output in final goods market by 0.5%, which results in an increase in the firm value by 12.9%.Price Discrimination With Stochastic Demand in International Airline Markets
Abstract
We estimate a structural model of dynamic airline pricing that incorporates two key features: (a) uncertain demand from the perspective of the airline, (b) different consumer types who arrive to the market at different times before the flight date. Both to of these features will lead the airline to engage in dynamic pricing. However, an airline’s pricing strategy is further complicated because it offers multiple classes of seats in order to screen consumers in each time period, and it can restrict the number of seats available at any given time period, leading to both static and inter-temporal price discrimination. We estimate the model in order to simultaneously study the welfare effects of stochastic demand and price discrimination. To estimate the model, we use novel data that contain rich information on both ticket and consumer characteristics. Importantly, we observe the price of a ticket, how long before the flight date the ticket was purchased, and whether the purpose of travel is business or leisure. We document that business travelers tend to arrive to the market later, and pay higher prices on average, than leisure consumers. We also find that dynamic pricing patterns differ substantially across markets with different levels of business passengers to leisure passengers. The rich information on consumer characteristics implies that we observe more than the firm in this setting, and allows us to identify the demand of different types of consumers separately from the effects of stochastic demand.JEL Classifications
- L0 - General