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2172 Results

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.

Estimating Policy Functions in Payments Systems Using Reinforcement Learning

We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.

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.

Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge

Staff working paper 2024-31 Alberto Cavallo, Oleksiy Kryvtsov
We study how price variation within a store changes with inflation, and whether households exploit these changes to reduce the burden of inflation. We find that price changes from discounts mitigated the inflation burden while cheapflation exacerbated it.

On the Evolution of the United Kingdom Price Distributions

We propose a functional principal components method that accounts for stratified random sample weighting and time dependence in the observations to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK).

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.

Testing Collusion and Cooperation in Binary Choice Games

Staff working paper 2023-58 Erhao Xie
This paper studies the testable implication of players’ collusive or cooperative behaviour in a binary choice game with complete information. I illustrate the implementation of this test by revisiting the entry game between Walmart and Kmart.

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.

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.
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