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2166 Results

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.

The Central Bank’s Dilemma: Look Through Supply Shocks or Control Inflation Expectations?

Staff working paper 2022-41 Paul Beaudry, Thomas J. Carter, Amartya Lahiri
When countries are hit by supply shocks, central banks often face the dilemma of either looking through such shocks or reacting to them to ensure that inflation expectations remain anchored. In this paper, we propose a tractable framework to capture this dilemma and then explore optimal policy under a range of assumptions about how expectations are formed.

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.

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.

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 Usage of Security Lending Facilities under Unconventional Monetary Policy: Evidence from Sweden

This paper examines the interaction between quantitative easing (QE) and the securities lending facility (SLF) using a detailed dataset on Riksbank QE purchases, Swedish DMO SLF transactions and OTC repo deals. A theoretical model further shows how excess demand for assets and search frictions shift the SLF from a backstop to a first-resort tool.

Is a Cashless Society Problematic?

Staff discussion paper 2018-12 Walter Engert, Ben Fung, Scott Hendry
The use of bank notes in Canada for payments has declined consistently for some time, and similar trends are evident in other countries. This has led some observers to predict a cashless society in the future.

Monetary Policy Transmission with Endogenous Central Bank Responses in TANK

Staff working paper 2025-21 Lilia Maliar, Chris Naubert
We study how the transmission of monetary policy innovations is affected by the endogenous response of the central bank to macroeconomic aggregates in a two-agent New Keynesian model. We focus on how the stance of monetary policy and the fraction of savers in the economy affect transmission.
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