I exploit unsupervised machine learning and natural language processing techniques to elicit the risk factors that firms themselves identify in their annual reports. I quantify the firms’ exposure to each identified risk, design an econometric test to classify them as either systematic or idiosyncratic, and construct factor mimicking portfolios that proxy for each undiversifiable source of risk.…Read More
Secure messaging, or “e-visits,” between patients and providers has sharply increased in recent years, and many hope they will help improve healthcare quality, while increasing provider capacity. Using a panel data set from a large healthcare system in the United States, we find that e-visits trigger about 6% more office visits, with mixed results on phone visits and patient health.…Read More
Insight into the growth (or shrinkage) of “knowledge communities” of authors that build on each other’s work can be gained by studying the evolution over time of clusters of documents. We cluster documents based on the documents they cite in common using the Streemer clustering method, which finds cohesive foreground clusters (the knowledge communities) embedded in a diffuse background.…Read More
