Information aggregation mechanisms are designed explicitly for collecting and aggregating dispersed information. An excellent example of the use of this "wisdom of crowds" is a prediction market. The purpose of our Twitter-based prediction market is to suggest that carefully designed market...

Economically intuitive macroeconomic factors and borrower characteristics predict peer-to-peer loan defaults beyond what proprietary algorithms predict. Using county-level unemployment data, we find that loans originated in high unemployment areas are more likely to default. In addition, we...

The recovery rate on defaulted corporate bonds has a time-varying distribution. We propose machine learning approaches for intertemporal analysis of U.S. corporate bonds' recovery rates with a large number of predictors. The most informative macroeconomic variables are selected from a broad...

Innovations in statistical technology have sparked concerns about distributional impacts across categories such as race and gender. Theoretically, as statistical technology improves, distributional consequences depend on how changes in functional forms interact with cross-category distributions...

In this paper, to begin with, we define soft information as qualitative, subjective information produced by banks through the establishment of long-term lending relationships. We then highlight the importance of soft information for cooperative and social banks in the screening, pricing and...