We develop a model to analyze information aggregation and learning in housing markets. In the presence of pervasive informational frictions, housing prices serve as important signals to households and capital producers about the economic strength of a neighborhood. Our model provides a novel...

The success of the behavioral economics literature has led to a new challenge—a large number of behavioral biases offering observationally similar predictions for a targeted anomaly in financial markets. To tame the bias zoo, we propose a new approach of combining subjective survey responses...

By comparing uncollateralized business loans made by a big tech lending program with conventional bank loans, we find that big tech loans tend to be smaller and have higher interest rates and that borrowers of big tech loans tend to repay far before maturity and borrow more frequently. These...

We examine historical banking crises through the lens of bank equity declines, which cover a broad sample of episodes of banking distress both with and without banking panics. To do this, we construct a new dataset on bank equity returns and narrative information on banking panics for 46...

The widespread use of market-making algorithms in electronic over-the-counter markets may give rise to unexpected effects resulting from the autonomous learning dynamics of these algorithms. In particular the possibility of `tacit collusion' among market makers has increasingly received...