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We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.

This monthly newsletter features the latest research publications by Bank of Canada economists including external publications and working papers published on the Bank of Canada’s website.

A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing.

We examine how changes in the Bank of Canada’s balance sheet impact the banking system. Quantitative easing contributed to an increase in the size of the banking system’s balance sheet and an improvement in bank liquidity coverage ratios. Quantitative tightening is expected to partially reverse these impacts. The banking system will have to adjust its liquidity management strategy in response.

When countries are hit by supply shocks, central banks often face the dilemma of either looking through such shocks or reacting to them to ensure that inflation expectations remain anchored. In this paper, we propose a tractable framework to capture this dilemma and then explore optimal policy under a range of assumptions about how expectations are formed.

This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models.

How do households respond when they receive unanticipated income, such as an inheritance or government stimulus cheque? This paper studies these windfall income shocks through a model of household behaviour that generates a realistic consumption response for households along the entire distribution of wealth.

Existing literature documents that house prices respond to monetary policy surprises with a significant delay, taking years to reach their peak response. We present new evidence of a much faster response.

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary.