E1 - General Aggregative Models

• CANVAS: A Canadian Behavioral Agent-Based Model

  Staff Working Paper 2022-51 Cars Hommes, Mario He, Sebastian Poledna, Melissa Siqueira, Yang Zhang

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Central bank research, Econometric and statistical methods, Economic models, Firm dynamics, Inflation and prices JEL Code(s): C, D, D2, D22, D8, D83, E, E1, E17

• 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.

  Content Type(s): Staff research, Staff working papers Topic(s): Central bank research, Economic models, Inflation and prices, Monetary policy, Monetary policy and uncertainty, Monetary policy communications JEL Code(s): E, E1, E12, E2, E24, E3, E31, E5, E52, E58, E6, E65

• Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning

  Staff Working Paper 2022-29 Vladimir Skavysh, Sofia Priazhkina, Diego Guala, Thomas Bromley

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Central bank research, Econometric and statistical methods, Economic models, Financial stability JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21

• Assessing global potential output growth and the US neutral rate: April 2022

  Staff Analytical Note 2022-4 Kyle Boutilier, Thomas J. Carter, Xin Scott Chen, Eshini Ekanayake, Louis Poirier, Peter Shannon, Akash Uppal, Lin Xiang

  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.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Interest rates, Monetary policy, Potential output, Productivity JEL Code(s): E, E1, E2, E4, E5, F, F0, O, O4