This paper predicts phases of the financial cycle by using a continuous financial stress measure in a Markov switching framework. The debt service ratio and property market variables signal a transition to a high financial stress regime, while economic sentiment indicators provide signals for a...

This paper introduces a new methodology to date systemic financial stress events in a transparent, objective and reproducible way. The financial cycle is captured by a monthly country-specific financial stress index. Based on a Markov-switching model, high financial stress regimes are...

We propose an early warning model for predicting the likelihood of a financial stress event for a given future time, and examine whether credit plays an important role in the model as a non-linear propagator of shocks. This propagation takes the form of a threshold regression in which a regime...

We incorporate quantile regressions into a structural vector autoregression model to empirically assess how monetary and fiscal policy influence risks around future GDP growth. Using a panel of six developed countries, we find that both policy instruments affect the location of the distribution...

We propose a novel framework to analyze how policy-makers can manage risks to the median projection and risks specific to the tail of gross domestic product (GDP) growth. By combining a quantile regression of GDP growth with a vector autoregression, we show that monetary and macroprudential...

We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on...

In the rapidly evolving landscape of digital asset markets, measuring cryptoasset knowledge alongside financial knowledge enhances our understanding of individuals' decisions to purchase cryptoassets. Using microdata from the Bank of Canada's Bitcoin Omnibus Survey, we measure familiarity with...

We develop a Canadian behavioral agent-based model (CANVAS) that utilizes Canadian micro- and macroeconomic data for forecasting and policy analysis. CANVAS represents a next-generation modelling effort, as it improves upon the previous generation of models in three dimensions: introducing...

This paper investigates the importance of U.S. macroeconomic news in driving low-frequency fluctuations in the term structure of interest rates in Canada, Sweden and the United Kingdom. We follow two complementary approaches: First, we apply a regression-based framework that aggregates the...

We propose and estimate a dynamic and individual model of expectations formation that links individual consumers' inflation expectations to their own lagged forecasts as well as proxies for the rational expectation forecasts. The model builds on the existing rational inattention literature and...