Organizational Structure and Pricing: Evidence from a Large U.S. Airline

We study how organizational boundaries affect pricing decisions using comprehensive data provided by a large U.S. airline. We show that contrary to prevailing theories of the firm, advanced pricing algorithms have multiple biases. To quantify the impacts of these biases, we estimate a structural demand model using sales and search data and recover the demand curves the firm believes it faces using forecasting data. In counterfactuals, we show that correcting biases introduced by organizational teams individually have little impact on market outcomes, but addressing all biases simultaneously leads to higher prices and increased dead-weight loss in the markets studied.