Browse research

How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy.

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.

This paper studies Canadians’ access to cash using the geographical distribution of automated banking machines (ABMs). During the pandemic, there have been no sustained adverse effects on cash accessibility.

We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models.

We summarize the theoretical model of central bank asset purchases developed in Cimon and Walton (2022). The model helps us understand how asset purchases ease pressures on investment dealers to restore market conditions in a crisis.

This paper introduces the Business Leaders’ Pulse, a new online survey conducted each month. It is designed to provide timely and flexible input into the Bank of Canada’s monetary policy decision making by asking firms about their sales and employment growth expectations, the risks to their business outlook, and topical questions that address specific information needs of the Bank.

This paper examines the cross-border spillovers from major economies’ quantitative easing (QE) policies to their trading partners. We concentrate on spillovers from the US to Canada during the zero lower bound period when QE policies were actively used.

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.

We assess whether more central clearing would enhance the resilience of Canadian fixed-income markets. Our analysis estimates the potential benefits of balance sheet netting under scenarios where central clearing is expanded to new participants.