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2139 Results

May 21, 2003

Conference Summary: Price Adjustment and Monetary Policy

The 2002 Bank of Canada Conference focused on price adjustment, a critically important issue for monetary policy. Given the acceptance throughout the 1990s and 2000s of the existence of price stickiness in goods or labour markets, or both, and of the important role that monetary policy can play in an economy, the time was right for a conference that would focus on current developments in this area of research, particularly within a Canadian context. Conference papers covering both theoretical and empirical studies explored such themes as sources of the persistence of inflation, forward-looking models of inflation, models of inflation in open economies, the macroeconomic effects of technology shocks, and models of the interaction between wages, prices, and real economic outcomes.

Should Central Banks Worry About Nonlinearities of their Large-Scale Macroeconomic Models?

Staff working paper 2017-21 Vadym Lepetyuk, Lilia Maliar, Serguei Maliar
How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions?

The impact of the Bank of Canada’s Government Bond Purchase Program

We assess the response of Government of Canada bond yields to the Bank of Canada’s initial announcement of the Government Bond Purchase Program (GBPP) as well as to the Bank’s later GBPP purchase operations.

Harnessing the benefit of state-contingent forward guidance

Staff analytical note 2022-13 Vivian Chu, Yang Zhang
A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

Trade and Diffusion of Embodied Technology: An Empirical Analysis

Using data from patents, citations, inter-sectoral sales and customs, we examine the international diffusion of technology through imports of sectoral knowledge and production inputs. We develop an instrumental variable strategy to identify the causal effects of technology embodied in imports on innovation and diffusion outcomes.
March 9, 2010

An Uncertain Past: Data Revisions and Monetary Policy in Canada

Many important economic variables are subject to revision. This article explains how, when, and why such revisions occur; how revisions to Canadian gross domestic product (GDP) compare with GDP revisions in some other countries; which GDP components are subject to the largest revisions; and how data revisions can affect policy decisions. The author finds that revisions to Canadian GDP tend to be smaller, on average, than those of some other countries, and that among the GDP components, exports and imports are most heavily revised.

Challenges in Implementing Worst-Case Analysis

Staff working paper 2018-47 Jon Danielsson, Lerby Ergun, Casper G. de Vries
Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

Calibrating the Magnitude of the Countercyclical Capital Buffer Using Market-Based Stress Tests

Staff working paper 2018-54 Maarten van Oordt
How much capital do banks need as a buffer to absorb severe shocks? By using historical stock market data, market-based stress tests help estimate the magnitude of capital buffers necessary to absorb severe but plausible shocks.

Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems

Staff working paper 2024-15 Ajit Desai, Anneke Kosse, Jacob Sharples
Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.
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