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2182 Results

Macroeconomic Predictions Using Payments Data and Machine Learning

Staff working paper 2022-10 James Chapman, Ajit Desai
We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

The Heterogeneous Effects of COVID-19 on Canadian Household Consumption, Debt and Savings

Staff working paper 2020-51 James (Jim) C. MacGee, Thomas Michael Pugh, Kurt See
The impact of COVID-19 on Canadian households’ debt and unplanned savings varies by household income. Low-income and high-income households accrued unplanned savings, while middle-income households tended to accumulate more debt.

Machine learning for economics research: when, what and how

Staff analytical note 2023-16 Ajit Desai
This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.
August 4, 2010

Fellowship Award

Annual research grants and expense allowances for a term of up to five years.

Canadian Bitcoin Ownership in 2023: Key Takeaways

Staff discussion paper 2025-4 Daniela Balutel, Marie-Hélène Felt, Doina Rusu
The Bitcoin Omnibus Survey is an important tool for monitoring Canadians’ awareness and ownership of bitcoin and other cryptoassets over time. In this paper, we present data highlights from the 2023 survey.

The Trend Unemployment Rate in Canada: Searching for the Unobservable

In this paper, we assess several methods that have been used to measure the Canadian trend unemployment rate (TUR). We also consider improvements and extensions to some existing methods.

Improving the Efficiency of Payments Systems Using Quantum Computing

We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays.

Nowcasting Canadian GDP with Density Combinations

Staff discussion paper 2022-12 Tony Chernis, Taylor Webley
We present a tool for creating density nowcasts for Canadian real GDP growth. We demonstrate that the combined densities are a reliable and accurate tool for assessing the state of the economy and risks to the outlook.

High-Frequency Cross-Sectional Identification of Military News Shocks

Staff working paper 2025-27 Francesco Amodeo, Edoardo Briganti
We identify and quantify fiscal news shocks, compiling events (2001–2023) that altered the expected path of U.S. defense expenditure. For each event, we estimate market-implied shifts in expected spending. A shift-share analysis yields a two-year, metropolitan statistical area–level GDP multiplier of approximately 1 for U.S. military build-ups.
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