Parallel Tempering for DSGE Estimation Staff working paper 2024-13 Joshua Brault I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C15, E, E1, E10 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models
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 JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models
Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data Staff working paper 2018-28 Valéry Dongmo Jiongo, Pierre Nguimkeu This paper proposes a new bootstrap procedure for mean squared errors of robust small-area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite sample performance through Monte Carlo simulations. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C13, C15, C8, C83, E, E4, E41 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes
State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models Staff working paper 2018-14 Luis Uzeda Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C15, C5, C51, C53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Asymmetric Risks to the Economic Outlook Arising from Financial System Vulnerabilities Staff analytical note 2018-6 Thibaut Duprey When financial system vulnerabilities are elevated, they can give rise to asymmetric risks to the economic outlook. To illustrate this, I consider the economic outlook presented in the Bank of Canada’s October 2017 Monetary Policy Report in the context of two key financial system vulnerabilities: high levels of household indebtedness and housing market imbalances. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C0, C01, C1, C11, C15, E, E1, E17, E3, E32, E37, E4, E44, E47, E5, E58, E6, E66, G, G0, G01, G1, G18 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting