Firms often involve multiple departments for critical decisions that may result in coordination failures. Using data from a large U.S. airline, we document the presence of important pricing biases that differ significantly from dynamically optimal profit maximization. However, these biases can be rationalized as a “second-best” after accounting for department decision rights. We show that assuming prices are generated through profit maximization biases demand estimates and that second-best prices can persist, even under improvements to pricing algorithm inputs. Our results suggest caution in abstracting from organizational structure and drawing inferences from firms’ pricing decisions alone.
We study how organizational boundaries affect pricing decisions using comprehensive data from a large U.S. airline. We document that the firm’s advanced pricing algorithm, utilizing inputs from different organizational teams, is subject to multiple biases. To quantify the impacts of these biases, we estimate a structural demand model using sales and search data. We 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 coordinating organizational outcomes leads to higher prices/revenues and increased deadweight loss in the markets studied.
We examine the potential for exploiting retailer location choice in targeting health interventions. Using geospatial data, we quantify proximity to vaccines created by a U.S. federal program distributing COVID-19 vaccines to commercial retail pharmacies. We assess the distributional impacts of a proposal to provide vaccines at Dollar General, a low-priced general merchandise retailer. Adding Dollar General to the federal program would substantially decrease the distance to vaccine sites for low-income, rural, and minority U.S. households, groups for which COVID-19 vaccine take-up has been disproportionately slow.
We study reward-based crowdfunding, a new class of dynamic contribution games where a private good is produced only if the funding goal is reached by a deadline. Buyers face a problem of coordination rather than free-riding. A long-lived donor may alleviate this coordination risk, signaling his wealth through dynamic contributions. We characterize platform-, donor-, and buyer-optimal equilibrium outcomes, attained by Markov equilibria with simple donation strategies. We test the model’s predictions using high-frequency data collected from the largest crowdfunding platform, Kickstarter. The model fits the data well, especially for predictions concerning comparative statistics, donation dynamics, and properties of successful campaigns.
Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. We show that these data cover broad sections of the US population and exhibit movement patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We use these indices to document how pandemic-induced reductions in activity vary across people and places.
We study reward-based crowdfunding campaigns, a new class of dynamic contribution games where consumption is exclusive. Two types of backers participate: buyers want to consume the product while donors just want the campaign to succeed. The key tension is one of coordination between buyers, instead of free-riding. Donors can alleviate this coordination risk. We analyze a dynamic model of crowdfunding and demonstrate that its predictions are consistent with high-frequency data collected from Kickstarter. We compare the Kickstarter mechanism to alternative platform designs and evaluate the value of dynamically arriving information. We extend the model to incorporate social learning about quality.
This paper develops an oligopoly model in which firms first choose capacity and then compete in prices in a series of advance-purchase markets. We show the existence of multiple sales opportunities creates strong competitive forces that prevent firms from utilizing intertemporal price discrimination. We then show that intertemporal price discrimination is possible, but only when firms adopt inventory controls (sales limit restrictions) and demand becomes more inelastic over time. Therefore, in addition to being useful to manage demand uncertainty, we show that inventory controls are also a tool to soften price competition. We discuss model extensions, including product differentiation, aggregate demand uncertainty, and longer sales horizons.
This paper develops an oligopoly model in which firms first choose capacity and then compete in prices in a series of advance-purchase markets. We show the existence of multiple sales opportunities creates strong competitive forces that prevent firms from utilizing intertemporal price discrimination. We then show that intertemporal price discrimination is possible, but only when firms adopt inventory controls (sales limit restrictions) and demand becomes more inelastic over time. Therefore, in addition to being useful to manage demand uncertainty, inventory controls are also a tool to soften price competition. We also discuss model extensions, including product differentiation, aggregate demand uncertainty, and longer sales horizons.
Inventory controls, used most notably by airlines, are sales limits assigned to individual prices. While typically viewed as a tool to manage demand uncertainty, we argue that inventory controls also facilitate intertemporal price discrimination. In our model, competing firms first choose quantity and then choose prices in a series of advance-purchase markets. When demand becomes more inelastic over time, as in the airline and hotel markets, a monopolist can easily price discriminate; however, we show that oligopoly firms generally cannot. Inventory controls let firms set increasing prices regardless of whether or not demand is uncertain.
Airfares fluctuate over time due to both demand shocks and intertemporal variation in willingness to pay. I develop and estimate a model of dynamic airline pricing accounting for both forces with new flight-level data. With the model estimates, I disentangle key interactions between the arrival pattern of consumer types and scarcity of remaining capacity due to stochastic demand. I show that dynamic airline pricing expands output by lowering fares charged to early-arriving, price-sensitive customers. It also ensures seats for late-arriving travelers with the highest willingness to pay (e.g. business travelers) who are then charged high prices. I find that dynamic airline pricing increases total welfare relative to a more restrictive pricing regime. Finally, I show that abstracting from stochastic demand results in incorrect inferences regarding the extent to which airlines utilize intertemporal price discrimination.
Airfares fluctuate due to demand shocks and intertemporal variation in willingness to pay. I estimate a model of dynamic airline pricing accounting for both sources of price adjustments using flight-level data. I use the model estimates to evaluate the welfare effects of dynamic airline pricing. Relative to uniform pricing, dynamic pricing benefits early-arriving, leisure consumers at the expense of late-arriving, business travelers. Although dynamic pricing ensures seat availability for business travelers, these consumers are then charged higher prices. When aggregated over markets, welfare is higher under dynamic pricing than under uniform pricing. The direction of the welfare effect at the market level depends on whether dynamic price adjustments are mainly driven by demand shocks or by changes in the overall demand elasticity.
We quantify the welfare effects of zone pricing, or setting common prices across distinct markets, in retail oligopoly. Although monopolists can only increase profits by price discriminating, this need not be true when firms face competition. With novel data covering the retail home improvement industry, we find that Home Depot would benefit from finer pricing but that Lowe’s would prefer coarser pricing. Zone pricing softens competition in markets where firms compete, but it shields consumers from higher prices in rural markets, where firms might otherwise exercise market power. Overall, zone pricing produces higher consumer surplus than finer price discrimination does.
We quantify the welfare effects of zone pricing, or setting common prices across distinct markets, in retail oligopoly. Although monopolists can only increase profits by price discriminating, this need not be true when firms face competition. With novel data covering the retail home improvement industry, we find that Home Depot would benefit from finer pricing but that Lowe’s would prefer coarser pricing. Zone pricing softens competition in markets where firms compete, but it shields consumers from higher prices in markets where firms might otherwise exercise market power. Overall, zone pricing produces higher consumer surplus than finer pricing discrimination does.