Effective treatment of Parkinson’s disease (PD) is a continual challenge for healthcare providers, and providers can benefit from leveraging emerging technologies to supplement traditional clinic…
In many applications of network analysis, it is important to distinguish between observed and unobserved factors affecting network structure. We show that a network model with discrete unobserved l…
Healthcare policy makers use wait-time metrics to encourage hospital managers to improve patient experience. In 2002, Massachusetts mandated that hospital managers develop processes to respond to b…
The COVID-19 pandemic has seen dramatic demand surges for hospital care that have placed a severe strain on health systems worldwide. As a result, policy makers are faced with the challenge of mana…
The multinomial probit model is often used to analyze choice behavior. However, estimation with existing Markov chain Monte Carlo (MCMC) methods is computationally costly, which limits its applicab…
Outpatient care providers usually allow patients to access service via scheduling appointments or direct walk-in. Patients choose strategically between these two access channels (and otherwise balk…
We revisit the generalized method of moments (GMM) estimation of the non-Gaussian structural vector autoregressive (SVAR) model. It is shown that in the n-dimensional SVAR model, global and local i…
We consider a platform facilitating trade between sellers and buyers with the objective of maximizing consumer surplus. Even though in many such marketplaces, prices are set by revenue-maximizing s…
We study the effects of counterfactual teacher-to-classroom assignments on average student achievement in U.S. elementary and middle schools. We use the Measures of Effective Teaching (MET) experim…
Historical data are typically limited. We study the following fundamental data-driven pricing problem. How can/should a decision maker price its product based on data at a single historical price? …