Differentiable, Filter Free Bayesian Estimation of DSGE Models Using Mixture Density Networks Staff Working Paper 2025-3 Chris Naubert I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values. Content Type(s): Staff research, Staff working papers Research Topic(s): Business fluctuations and cycles, Economic models JEL Code(s): C, C6, C61, C63, E, E3, E37, E4, E47
Digital Payments in Firm Networks: Theory of Adoption and Quantum Algorithm Staff Working Paper 2024-17 Sofia Priazhkina, Samuel Palmer, Pablo Martín-Ramiro, Román Orús, Samuel Mugel, Vladimir Skavysh We build a network formation game of firms with trade flows to study the adoption and usage of a new digital currency as an alternative to correspondent banking. Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Digital currencies and fintech, Digitalization, Economic models, Financial institutions, Payment clearing and settlement systems, Sectoral balance sheet JEL Code(s): C, C6, C7, C71, D, D4, D8, D85, G, L, L2, L22
January 15, 2024 Mapping out the implications of climate transition risk for the financial system Gabriel Bruneau, Javier Ojea Ferreiro, Andrew Plummer, Marie-Christine Tremblay, Aidan Witts We develop a new analytical framework to understand the system-wide implications of climate transition risk. When applying this framework to Canadian data, we find that interconnections within the financial sector could amplify the direct effects of climate transition risk on financial entities. Content Type(s): Publications, Financial System Hub articles Research Topic(s): Climate change, Economic models, Financial institutions, Financial markets, Financial stability JEL Code(s): C, C6, C63, G, G0, G01, G1, G10, G2, G20, Q, Q5, Q54
Understanding the Systemic Implications of Climate Transition Risk: Applying a Framework Using Canadian Financial System Data Staff Discussion Paper 2023-32 Gabriel Bruneau, Javier Ojea Ferreiro, Andrew Plummer, Marie-Christine Tremblay, Aidan Witts Our study aims to gain insight on financial stability and climate transition risk. We develop a methodological framework that captures the direct effects of a stressful climate transition shock as well as the indirect—or systemic—implications of these direct effects. We apply this framework using data from the Canadian financial system. Content Type(s): Staff research, Staff discussion papers Research Topic(s): Climate change, Economic models, Financial institutions, Financial markets, Financial stability JEL Code(s): C, C6, C63, G, G0, G01, G1, G10, G2, G20, Q, Q5, Q54
An Investigation into the Effects of Border Carbon Adjustments on the Canadian Economy Staff Working Paper 2023-27 Y.-H. Henry Chen, Hossein Hosseini Jebeli, Craig Johnston, Sergey Paltsev, Marie-Christine Tremblay We examine the economic implications of border carbon adjustments (BCAs) for Canada. We find that, BCAs, in the form of import tariffs, reduce Canada’s carbon leakage and improve its competitiveness when Canada is part of a broad coalition of BCA-implementing countries. Welfare also improves when tariff revenues are transferred to households. Content Type(s): Staff research, Staff working papers Research Topic(s): Climate change, International topics, Trade integration JEL Code(s): C, C6, C68, F, F1, H, H2, Q, Q3, Q37, Q5
Learning in a Complex World: Insights from an OLG Lab Experiment Staff Working Paper 2023-13 Cars Hommes, Stefanie J. Huber, Daria Minina, Isabelle Salle 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. Content Type(s): Staff research, Staff working papers Research Topic(s): Business fluctuations and cycles, Economic models JEL Code(s): C, C6, C62, C68, C9, C91, C92, E, E1, E13, E7, E70, G, G1, G12, G4, G41
Simulating Intraday Transactions in the Canadian Retail Batch System Staff Working Paper 2023-1 Nellie Zhang This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available. Content Type(s): Staff research, Staff working papers Research Topic(s): Financial markets, Payment clearing and settlement systems JEL Code(s): C, C6, C63, E, E4, E42, E5, E58
Improving the Efficiency of Payments Systems Using Quantum Computing Staff Working Paper 2022-53 Christopher McMahon, Donald McGillivray, Ajit Desai, Francisco Rivadeneyra, Jean-Paul Lam, Thomas Lo, Danica Marsden, Vladimir Skavysh We develop an algorithm and run it on a hybrid quantum annealing solver to find an ordering of payments that reduces the amount of system liquidity necessary without substantially increasing payment delays. Content Type(s): Staff research, Staff working papers Research Topic(s): Digital currencies and fintech, Financial institutions, Financial services, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): C, C6, C61, C63, D, D8, D83, E, E4, E42, E5, E58
Comparison of Bayesian and Sample Theory Parametric and Semiparametric Binary Response Models Staff Working Paper 2022-31 Xiangjin Shen, Iskander Karibzhanov, Hiroki Tsurumi, Shiliang Li We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models. Content Type(s): Staff research, Staff working papers Research Topic(s): Credit risk management, Econometric and statistical methods JEL Code(s): C, C1, C14, C3, C35, C5, C51, C6, C63, D, D1
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 Research 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