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60 Results

Prima: The Bank of Canada’s New Projection and Policy-Analysis Model—An Overview

Prima is the Bank of Canada’s new model for projection and policy analysis. It builds on the economic foundations of earlier Bank models, adding detail on how sectoral pressures affect production costs and their pass-through to consumer prices.

Sector-based producer price indexes: New measures of producer price pressures in Canada

Staff analytical paper 2026-46 Yena Joo, Ali Rouhghalandari, Vivian Chu, Xin Ha
Producer price indexes measure changes in the prices that producers receive for their outputs or that they pay for their inputs. Statistics Canada publishes a range of producer price indexes for specific products and industries. For the first time, these series have been combined into a small set of broad sectoral measures.

Liquidity Optimization in Gross Settlement Systems with Quantum Reordering: Application to TARGET2∗

Building on our earlier quantum algorithm, this paper shows that reordering queued payments can significantly reduce liquidity needs. The algorithm performs well on smaller payment batches, while traditional algorithms can process larger batches and deliver greater savings. Machine learning also helps identify which payment patterns offer the greatest potential for improvement.

Tracking Heterogeneous Spending Patterns with Credit Card Microdata

Staff analytical paper 2026-38 Jia Qi Xiao, Jackson Reid, Joey Daniels
We present a measure of account-level credit card spending constructed using credit bureau microdata, capturing monthly spending for approximately 80% of adults in Canada. Our measure offers higher frequency than other publicly available consumption metrics, and can be disaggregated by age, geographic location and credit history.

Integrating Non-traditional Data and AI into Central Banking: A Canadian Perspective

This paper reviews how central banks are integrating non traditional data and artificial intelligence (AI) into policy analysis and operations. Using the Bank of Canada’s experience, it examines emerging applications, governance challenges, and strategic choices for responsibly scaling AI to enhance insight, efficiency, and institutional resilience.

MSTest: An R-Package for Testing Markov Switching Models

Staff working paper 2026-7 Gabriel Rodriguez Rondon, Jean-Marie Dufour
We present the R package MSTest, which implements hypothesis testing procedures to determine the number of regimes in Markov switching models. The package provides several testing frameworks, including Monte Carlo likelihood ratio tests, moment-based tests, parameter stability tests, and classical likelihood ratio procedures.

I Am So Tired! I Don’t Know What to Do! Survey Fatigue and Financial Literacy: Results from a Randomized Experiment

Staff working paper 2026-5 Anna Chernesky, Kim Huynh, Marcel Voia
We use a randomization of question placement in surveys to estimate the causal effect on financial literacy results. We find that financial literacy questions placed at the end of a survey lead to a drop in financial literacy of 5%–15%. This research suggests a measure of financial literacy adapted for survey length.

Inflation Expectations in Action: Exploring Agents’ Behaviour in a Period of High Inflation

Staff discussion paper 2025-18 Naveen Rai, Hayley Touchburn, Matt West
Inflation expectations are important to monetary policy decision-makers. Using survey evidence, we examine how firms and consumers react to their inflation expectations during the post-pandemic period of high inflation.
Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C83, D, D8, D84, E, E3, E31 Research Theme(s): Monetary policy, Inflation dynamics and pressures

Do Firms’ Sales Expectations Hit the Mark? Evidence from the Business Leaders’ Pulse

Staff discussion paper 2025-15 Owen Gaboury, Farrukh Suvankulov, Mathieu Utting
We analyze Canadian data from the Bank of Canada’s Business Leaders’ Pulse, examining firms’ sales growth expectations. We find that expected growth predicts outcomes, uncertainty influences forecast errors and revisions, and firms with weak past performance anticipate and experience weaker future growth. These results highlight the survey’s value for understanding business expectations.

Correcting Selection Bias in a Non-Probability Two-Phase Payment Survey

Staff working paper 2025-17 Heng Chen, John Tsang
We develop statistical inferences for a non-probability two-phase survey sample when relevant auxiliary information is available from a probability survey sample. The proposed method is assessed by simulation studies and used to analyze a non-probability two phase payment survey.
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