We develop a theoretical model of mortgage loss rates that evaluates their main underlying risk factors. Following the model, loss rates are positively influenced by the house price level, the loan-to-value of mortgages, interest rates, and the unemployment rate. They are negatively influenced by the growth of house prices and the income level. The calibration of the model for the US and Switzerland demonstrates that it is able to describe the overall development of actual mortgage loss rates. In addition, we show potential applications of the model for different macroprudential instruments: stress tests, countercyclical buffer, and setting risk weights for mortgages with different loan-to-value and loan-to-income ratios.

This paper examines the origins of herding behavior in asset markets and its potential to produce a price bubble. I present a model which explains the emergence and the development of herding behavior via asymmetric information and Baysian learning. A corresponding price bubble is explained through herding behavior without assuming any speculative incentives on the part of the investors.