Papers by Timothy Schwieg
We propose an approach to modeling and estimating discrete choice demand that allows for a large ... more 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. Ali Hortaçsu Kenn...
SSRN Electronic Journal, 2021
Although typically modeled as a centralized firm decision, pricing often involves multiple organi... more Although typically modeled as a centralized firm decision, pricing often involves multiple organizational teams that have decision rights over specific pricing inputs. We study team input decisions using comprehensive data from a large U.S. airline. We document that pricing at a sophisticated firm is subject to miscoordination across teams, uses persistently biased forecasts, and does not account for cross-price elasticities. With structural demand estimates derived from sales and search data, we find that addressing one team's biases in isolation has little impact on market outcomes. We show that teams do not optimally account for biases introduced by other teams. We estimate that corrected and coordinated inputs would lead to a significant reallocation of capacity. Leisure consumers would benefit from lower fares, and business customers would face significantly higher fares. Dead-weight loss would increase in the markets studied. Finally, we discuss likely mechanisms for the observed pricing biases.
We develop a simple analytical method to estimate the fraction of unreported infections in epidem... more We develop a simple analytical method to estimate the fraction of unreported infections in epidemics with a known epicenter and estimate the number of unreported COVID-19 infections in the US during the first half of March 2020. Our method utilizes the covariation in initial reported infections across US regions and the number of travelers to these regions from the epicenter, along with the results of a randomized testing study in Iceland. We estimate that 4-14% (1.5%-10%) of actual infections had been reported in US up to March 16, accounting for an assumed reporting lag of 8 (5) days.
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Papers by Timothy Schwieg