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Staff working papers

Estimating Policy Functions in Payments Systems Using Reinforcement Learning

We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff Working Paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

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