C1 - Econometric and Statistical Methods and Methodology: General
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Private Digital Cryptoassets as Investment? Bitcoin Ownership and Use in Canada, 2016-2021
We report on the dynamics of Bitcoin awareness and ownership from 2016 to 2021, using the Bank of Canada's Bitcoin Omnibus Surveys (BTCOS). Our analysis also helps understand Bitcoin owners who adopted during the COVID-19 and how they differ from long-term owners. -
October 12, 2022
Five things we learned about Canadian Bitcoin owners in 2021
We present key findings from the 2021 Bitcoin Omnibus Survey on Canadians’ awareness and ownership of Bitcoin. Most Canadians have heard of Bitcoin, which remains primarily used as an investment. Ownership jumped in 2021, reflecting increased savings during the pandemic and greater availability of user-friendly platforms to buy Bitcoin. -
Examining recent revisions to CPI-common
Unusually large revisions to CPI-common in recent months stem from increased common movements across consumer price index components amid broad inflationary pressures. With recent revisions, CPI-common is more closely aligned with the Bank of Canada’s other two preferred measures of core inflation. However, caution is necessary when interpreting real-time estimates of CPI-common in the current environment. -
Behavioral Learning Equilibria in New Keynesian Models
We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing. -
Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models. -
Cash, COVID-19 and the Prospects for a Canadian Digital Dollar
We provide an analysis of cash trends in Canada before and during the COVID-19 pandemic. We also consider the potential two scenarios for issuance of a central bank digital currency in Canada: the emergence of a cashless society or the widespread use of an alternative digital currency in Canada. Finally, we discuss the Canadian experience in maintaining cash as an efficient and accessible method of payment and store of value. -
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. -
Cash in the Pocket, Cash in the Cloud: Cash Holdings of Bitcoin Owners
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.