Inflation expectations are a key determinant of actual and future inflation and thus matter for the conduct of monetary policy. We study how firms form their inflation expectations using quarterly firm-level data from the Bank of Canada's Business Outlook Survey, spanning the 2001 to 2015...

We explore the macroeconomic effects of a compression in the long-term bond yield spread within the context of the Great Recession of 2007-2009 via a time-varying parameter structural VAR model. We identify a 'pure' spread shock defined as a shock that leaves the policy rate unchanged, which...

We propose a framework of optimal monetary policy where debt sustainability may, or may not, be a relevant constraint for the central bank. We show analytically that in each environment the optimal interest rate path consists of a Taylor rule augmented with forward guidance terms. These terms...

Inflation targeting (IT) had originally been introduced as a device to bring inflation down and stabilize it at low levels. Given the current environment of persistently weak inflation in many advanced economies, IT central banks must now bring inflation up to target. In this paper, the author...

A sequential Monte Carlo method for estimating GARCH models subject to an unknown number of structural breaks is proposed. Particle filtering techniques allow for fast and efficient updates of posterior quantities and forecasts in real time. The method conveniently deals with the path dependence...

Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. This...

Bayesian predictive synthesis is a flexible method of combining density predictions. The flexibility comes from the ability to choose an arbitrary synthesis function to combine predictions. I study the choice of synthesis function when combining large numbers of predictions-a common occurrence...

Bayesian predictive synthesis (BPS) is a method of combining predictive distributions based on agent opinion analysis theory, which encompasses many common approaches to combining density forecasts. The key ingredient in BPS is a synthesis function. This is typically specified parametrically as...

The macroeconomy is a complicated dynamic system with significant uncertainties that make modelling difficult. Consequently, decision-makers consider multiple models that provide different predictions and policy recommendations and then synthesize that information into a policy decision. We use...

We distinguish between the goods and services sectors in an otherwise standard unobserved components model of US inflation. Our main finding is that, while both sectors used to contribute to the overall variation in aggregate trend inflation, since the 1990s this variation has been driven almost...