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2120 Results

What COVID-19 revealed about the resilience of bond funds

Staff analytical note 2020-18 Guillaume Ouellet Leblanc, Ryan Shotlander
The liquidity management strategies of fund managers, supported by policy measures, have helped bond funds limit the increase in redemptions caused by COVID 19. This avoided further deterioration in liquidity in bond markets. Nevertheless, these funds were left with lower cash buffers, which could make them more vulnerable to additional large redemptions.

Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

Staff working paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez
Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

An Alternative Estimate of Canadian Potential Output: The Multivariate State-Space Framework

Staff discussion paper 2018-14 Lise Pichette, Maria Bernier, Marie-Noëlle Robitaille
In this paper, we extend the state-space methodology proposed by Blagrave et al. (2015) and decompose Canadian potential output into trend labour productivity and trend labour input. As in Blagrave et al. (2015), we include output growth and inflation expectations from consensus forecasts to help refine our estimates.

Detecting Scapegoat Effects in the Relationship Between Exchange Rates and Macroeconomic Fundamentals

Staff working paper 2017-22 Lorenzo Pozzi, Barbara Sadaba
This paper presents a new testing method for the scapegoat model of exchange rates that aims to tighten the link between the theory on scapegoats and its empirical implementation. This new testing method consists of a number of steps.

Partial Identification of Heteroskedastic Structural Vector Autoregressions: Theory and Bayesian Inference

Staff working paper 2025-14 Helmut Lütkepohl, Fei Shang, Luis Uzeda, Tomasz Woźniak
We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

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.

Identifying Nascent High-Growth Firms Using Machine Learning

Staff working paper 2023-53 Stéphanie Houle, Ryan Macdonald
Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data.

How Banks Create Gridlock to Save Liquidity in Canada's Large Value Payment System

Staff working paper 2023-26 Rodney J. Garratt, Zhentong Lu, Phoebe Tian
We show how participants in Canada’s new high-value payment system save liquidity by exploiting the new gridlock resolution arrangement. The findings have important implications for the design of these systems and shed light on financial institutions’ liquidity preference.

The Mutable Geography of Firms’ International Trade

Staff working paper 2025-11 Lu Han
Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks.
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