The 2008 financial crisis has shown that financial busts can influence the real economy. However, there is less evidence to suggest that the same holds for financial booms. Using a Markov-Switching vector autoregressive model and euro area data, I show that financial booms tend to be less...

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870-2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...

We develop early warning models for financial crisis prediction using machine learning techniques on macrofinancial data for 17 countries over 1870–2016. Machine learning models mostly outperform logistic regression in out-of-sample predictions and forecasting. We identify economic drivers of...

The 2008 financial crisis has shown that financial busts can influence the real economy. However, there is less evidence to suggest that the same holds for financial booms. Using a Markov-Switching vector autoregressive model and euro area data, I show that financial booms tend to be less...

We study the implications of multi-period mortgage loans for monetary policy, considering several realistic modifications — fixed interest rate contracts, lower bound constraint on newly granted loans, and possibility for the collateral constraint to become slack — to an otherwise standard...

We develop a dynamic stochastic general equilibrium framework that can account for important macroeconomic and financial moments, given Epstein-Zin preferences, heterogeneous banking and third-order approximation methods that yield a time-varying term premium that feeds back to the real economy....

We study the implications of multiperiod mortgage loans for monetary policy, considering several realistic modifications—fixed interest rate contracts, a lower bound constraint on newly granted loans, and the possibility of the collateral constraint to become slack—to an otherwise standard...

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870–2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...