E1 - General Aggregative Models
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Should Banks Be Worried About Dividend Restrictions?
A regulator would want to restrict dividends to force banks to rebuild capital during a crisis. But such a policy is not time-consistent. A time-consistent policy would let banks gradually rebuild capital and pay dividends even when their equity remains below pre-crisis levels. -
Assessing global potential output growth and the US neutral rate: April 2023
We expect global potential output growth to increase from 2.5% in 2022 to 2.8% by 2026. Compared with the April 2022 staff assessment, global potential output growth is marginally slower. The current range for the US neutral rate is 2% to 3%, unchanged from the last annual assessment. -
Learning in a Complex World: Insights from an OLG Lab Experiment
This paper brings novel insights into group coordination and price dynamics in complex environments. We implement a chaotic overlapping-generation model in the lab and find that group coordination is always on the steady state or on the two-cycle and that behavior is non-monotonic. -
CANVAS: A Canadian Behavioral Agent-Based Model
The Bank of Canada’s current suite of models faces challenges in addressing network effects that integrate household and firm-level heterogeneity and their behaviours. We develop CANVAS, a Canadian behavioural agent-based model to contribute to the Bank’s next-generation modelling effort. CANVAS improves forecasting performance and expands capacity for model-based scenario analysis. -
The Central Bank’s Dilemma: Look Through Supply Shocks or Control Inflation Expectations?
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. -
Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning
Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo. -
Assessing global potential output growth and the US neutral rate: April 2022
We expect global potential output growth to increase from 2.7% in 2021 to 2.9% by 2024. Compared with the April 2021 assessment, global potential output growth is marginally slower. The current range for the US neutral rate is 2% to 3%, 0.25 percentage points higher than staff’s last assessment. -
ToTEM III: The Bank of Canada’s Main DSGE Model for Projection and Policy Analysis
ToTEM III is the most recent generation of the Bank of Canada’s main dynamic stochastic general equilibrium model for projection and policy analysis. The model helps Bank staff tell clear and coherent stories about the Canadian economy’s current state and future evolution. -
Can regulating bank capital help prevent and mitigate financial downturns?
Countercyclical capital buffers are regulatory measures developed in response to the global financial crisis of 2008–09. This note focuses on how time-varying capital buffers can improve financial stability in Canada