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
May 13, 2014 Bank of Canada Review - Spring 2014 The five articles in this issue present research and analysis by Bank staff covering a variety of topics: the growth of Canadian-dollar-denominated assets in official foreign reserves; the emergence of platform-based digital currencies; methods of forecasting the real price of oil; measures of uncertainty in monetary policy; and the recent performance of the labour market in Canada and the United States. Content Type(s): Publications, Bank of Canada Review
Let’s Get Physical: Impacts of Climate Change Physical Risks on Provincial Employment Staff Working Paper 2024-32 Thibaut Duprey, Soojin Jo, Geneviève Vallée We analyze 40 years’ worth of natural disasters using a local projection framework to assess their impact on provincial labour markets in Canada. We find that disasters decrease hours worked within a week and lower wage growth in the medium run. Our study highlights that disasters affect vulnerable workers through the income channel. Content Type(s): Staff research, Staff working papers Topic(s): Climate change, Labour markets, Regional economic developments JEL Code(s): C, C3, C33, E, E2, E24, J, J3, Q, Q5, Q54