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2098 Results

Should Central Banks Worry About Nonlinearities of their Large-Scale Macroeconomic Models?

Staff working paper 2017-21 Vadym Lepetyuk, Lilia Maliar, Serguei Maliar
How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions?

The impact of the Bank of Canada’s Government Bond Purchase Program

We assess the response of Government of Canada bond yields to the Bank of Canada’s initial announcement of the Government Bond Purchase Program (GBPP) as well as to the Bank’s later GBPP purchase operations.
March 9, 2010

An Uncertain Past: Data Revisions and Monetary Policy in Canada

Many important economic variables are subject to revision. This article explains how, when, and why such revisions occur; how revisions to Canadian gross domestic product (GDP) compare with GDP revisions in some other countries; which GDP components are subject to the largest revisions; and how data revisions can affect policy decisions. The author finds that revisions to Canadian GDP tend to be smaller, on average, than those of some other countries, and that among the GDP components, exports and imports are most heavily revised.

Nowcasting Canadian Economic Activity in an Uncertain Environment

Staff discussion paper 2018-9 Tony Chernis, Rodrigo Sekkel
This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.

Parallel Tempering for DSGE Estimation

Staff working paper 2024-13 Joshua Brault
I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.

The Determinants of Consumers’ Inflation Expectations: Evidence from the US and Canada

Staff working paper 2020-52 Charles Bellemare, Rolande Kpekou Tossou, Kevin Moran
We compare the determinants of consumer inflation expectations in the US and Canada by analyzing two current surveys. We find that Canadian consumers rely more on professional forecasts and the history of actual inflation when forming their expectations, while US consumers rely more on their own lagged expectations.

Are Temporary Oil Supply Shocks Real?

Staff working paper 2022-52 Johan Brannlund, Geoffrey R. Dunbar, Reinhard Ellwanger
Hurricanes disrupt oil production in the Gulf of Mexico because producers shut in oil platforms to safeguard lives and prevent damage. We examine the effects of these temporary oil supply shocks on real economic activity in the United States.

Calibrating the Magnitude of the Countercyclical Capital Buffer Using Market-Based Stress Tests

Staff working paper 2018-54 Maarten van Oordt
How much capital do banks need as a buffer to absorb severe shocks? By using historical stock market data, market-based stress tests help estimate the magnitude of capital buffers necessary to absorb severe but plausible shocks.

The Case of Serial Disappointment

Similar to those of other forecasters, the Bank of Canada’s forecasts of global GDP growth have shown persistent negative errors over the past five years. This is in contrast to the pre-crisis period, when errors were consistently positive as global GDP surprised to the upside. All major regions have contributed to the forecast errors observed since 2011, although the United States has been the most persistent source of notable errors.

Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems

Staff working paper 2024-15 Ajit Desai, Anneke Kosse, Jacob Sharples
Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.
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