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Over the past several years, the Bank for International Settlements has noted that Canada’s credit-to-GDP gap has widened and is above thresholds indicating future banking stress.

The substantial growth in wealth over the course of the second half of the 1990s generated the equivalent of a certain level of savings, while simultaneously causing household savings rates to fall significantly. The author seeks to explain this decline in savings, observed since 1995, using the methodology developed by King, Plosser, Stock, and Watson (1991).

This report reviews the use of quantitative tools to gauge market participants’ assessment of banking system resilience. These measures complement traditional balance-sheet metrics and suggest that markets consider large Canadian banks to be better placed to weather adverse shocks than banks in other advanced economies. Compared with regulatory capital ratios, however, the measures suggest less improvement in banking system resilience since the pre-crisis period.

This paper presents a dynamic general equilibrium model where asymmetric information about asset quality leads to asset illiquidity. Banking arises endogenously in this environment as banks can pool illiquid assets to average out their idiosyncratic qualities and issue liquid liabilities backed by pooled assets whose total quality is public information.

We analyze the interaction between committed monetary policy and discretionary fiscal policy in a model with public debt, endogenous government expenditures, distortive taxation and nominal rigidities.

Offline functionality is a key consideration for a potential CBDC. We describe the different types of offline functionality based on their duration outside of network connection—either intermittent (for short periods) or extended (for longer periods). We discuss the advantages and drawbacks of each and consider implications for end-user devices, system resilience and universal accessibility.

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 loan insurance—credit risk transfer upon origination—in a model in which lenders can screen, learn loan quality over time, and can sell loans. Some lenders with low screening ability insure, benefiting from higher market liquidity of insured loans while forgoing the option to exploit future information about loan quality.