Search

This paper studies, theoretically and empirically, the unintended consequences of mandatory retention rules in securitization. It proposes a novel model showing that while retention strengthens monitoring, it may also encourage banks to shift risk.

This paper measures how both geographical and cultural proximity of bank branches affect household credit choice and pricing. For credit products that require high levels of ex-ante screening, we find that both proximities can complement each other in reducing the cost of providing soft information, thereby increasing credit access.

The Bank of Canada is publishing a new set of indicators of financial vulnerabilities. This will allow households, the private sector, financial authorities and governments to better understand and monitor the evolution of two key vulnerabilities in the financial system: the elevated level of household indebtedness and high house prices.

We estimate the share of variable-rate mortgages with fixed payments that reached the so-called trigger rate—the interest rate at which mortgage payments no longer cover the principal. Amid rising interest rates, this share was close to 50% at the end of October 2022 and could potentially reach 65% in 2023.

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.

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.

The COVID-19 pandemic uncovered policy challenges related to the economic measures that were taken to support the economy. Two years later, we attempt to identify the broader impact of these measures and research that needs to follow.

We develop a principal-agent model of cyber-attacking with fee-paying clients who delegate security decisions to financial platforms. We derive testable implications about clients’ vulnerability to cyber attacks and about the fees charged.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.

This paper evaluates the effectiveness of macroprudential policies when regulations are uneven across mortgage lender types. We look at credit tightening that results from macroprudential regulations and examine how much of it is counteracted by credit shifting to unregulated lenders. We also study the impact of monetary policy tightening when some lenders are unregulated.