C1 - Econometric and Statistical Methods and Methodology: General
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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. -
Bitcoin Awareness, Ownership and Use: 2016–20
In this paper, we examine trends in Canadian ownership of Bitcoin and other cryptocurrencies from 2016 to 2020 using data from surveys conducted by the Bank of Canada. -
Cash and COVID-19: What happened in 2021
Using data from the Bank Note Distribution System and consumer surveys, we find that bank notes in circulation remained high through 2021. Canadians continued to rely on electronic methods of payment, but a significant share also continued using cash for payments. -
Covariates Hiding in the Tails
We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data.