Econometric and statistical methods

• 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

• Cash in the Pocket, Cash in the Cloud: Cash Holdings of Bitcoin Owners

  Staff Working Paper 2022-26 Daniela Balutel, Christopher Henry, Kim Huynh, Marcel Voia

  We estimate the effect that owning Bitcoin has on the amount of cash held by Canadian consumers. Our results question the view that adopting certain new technologies, such as Bitcoin, leads to a decline in cash holdings.

  Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4, O, O3, O33, O5, O51