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We examine the effects of monetary policy shocks on the Canadian housing market. Using high-frequency surprises around fixed announcement dates as an instrument in a Bayesian VAR, we estimate the responses of house prices, housing starts, building permits, resales, inventories, and mortgage purchases to a contractionary monetary policy shock. An increase in the policy rate leads to a substantial and persistent decline in average house prices. Housing starts and building permits fall, but their implied effects on the future housing stock are both slow and modest. Interpreted through the lens of market equilibrium, these results are most consistent with a stronger response of housing demand than housing supply.

In this note we examine how monetary policy affects housing demand, supply and prices in Canada, and whether these effects vary with labour market conditions

Natural disasters can create important challenges for monetary policy in resource-rich small open economies. Using a DSGE model calibrated to Canada, we show that most disasters operate as adverse supply shocks, lowering output and raising inflation, thereby creating a trade-off for monetary policy.

This paper develops Monte Carlo likelihood-ratio tests for determining the number of regimes in Markov switching models. Unlike most existing procedures, which focus on testing one versus two regimes, the proposed methods allow testing an arbitrary number of regimes. They are valid in finite samples, robust to identification problems, and applicable to nonstationary, multivariate, and Markov switching GARCH models.

This paper examines how climate change affects income inequality across US states. Using a new climate-inequality VAR and a century of daily temperature data, it shows that shifts across the full temperature distribution—not just average warming—have diverse effects on within-state inequality.

Can monetary policy influence the neutral real interest rate (r-star)? Using a new statistical model, we show that interest rate hikes tend to lower r-star and long-run growth, but that monetary policy explains only a small share of the long-run decline in r-star.

This article examines what market conditions lead to extreme losses in global financial systems. Using a reverse stress testing approach, it introduces two measures of systemic risk by starting from the tail losses and working backward to identify the events most closely associated with them.

This paper studies how financial shocks shape the distribution of output growth by introducing a quantile-augmented vector autoregression (QAVAR), which integrates quantile regressions into a structural VAR framework. The QAVAR preserves standard shock identification while delivering flexible, nonparametric forecasts of conditional moments and tail risk measures for gross domestic product.

Trading flows affect Government of Canada bond prices. Our estimates suggest a sale of 1% of the available supply of bonds typically lowers bond prices by 0.2%. From 2000 to 2025, demand from institutional investors, such as Canadian pension funds and foreign investors, explains 69% of quarterly price variation, with the remainder explained by changes in the supply of bonds.

We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.