Fundraising campaigns draw support from a wide pool of contributors. Some contributors are interested in private rewards offered in exchange for contributions (buyers), whereas others are publicly-minded and value success (donors). Buyers face a coordination problem because of the positive externalities of campaign success. A leadership donor who strategically times contributions can promote coordination by dynamically signaling his valuation. The ability to signal increases the probability of success and benefits all participants relative to the donor valuation being known. We validate our modeling assumptions and theoretical predictions using Kickstarter data.
We introduce a model of oligopoly dynamic pricing where firms with limited capacity face a sales deadline. We establish conditions under which the equilibrium is unique and converges to a system of differential equations. Using unique and comprehensive pricing and bookings data for competing U.S. airlines, we estimate our model and find that dynamic pricing results in higher output but lower welfare than under uniform pricing. Our theoretical and empirical findings run counter to standard results in single-firm settings due to the strategic role of competitor scarcity. Pricing heuristics commonly used by airlines increase welfare relative to estimated equilibrium predictions.
We propose an approach to modeling and estimating discrete choice demand that allows for a large number of zero sale observations, rich unobserved heterogeneity, and endogenous prices. We do so by modeling small market sizes through Poisson arrivals. Each of these arriving consumers then solves a standard discrete choice problem. We present a Bayesian IV estimation approach that addresses sampling error in product shares and scales well to rich data environments. The data requirements are traditional market-level data and measures of consumer search intensity. After presenting simulation studies, we consider an empirical application of air travel demand where product-level sales are sparse. We find considerable variation in demand over time. Periods of peak demand feature both larger market sizes and consumers with higher willingness to pay. This amplifies cyclicality. However, observed frequent price and capacity adjustments offset some of this compounding effect.
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.