C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
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January 15, 2024
Mapping out the implications of climate transition risk for the financial system
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. -
Understanding the Systemic Implications of Climate Transition Risk: Applying a Framework Using Canadian Financial System Data
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. -
An Investigation into the Effects of Border Carbon Adjustments on the Canadian Economy
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. -
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. -
Simulating Intraday Transactions in the Canadian Retail Batch System
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. -
Improving the Efficiency of Payments Systems Using Quantum Computing
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. -
Comparison of Bayesian and Sample Theory Parametric and Semiparametric Binary Response Models
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. -
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. -
Transition Scenarios for Analyzing Climate-Related Financial Risk
Climate transition scenarios clarify climate-related risks to our economy and financial system. This paper summarizes key results of Canada-relevant scenarios developed in a pilot project on climate risk by the Bank of Canada and the Office of the Superintendent of Financial Institutions.