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357 Results

Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models

Staff Discussion Paper 2022-19 James Younker
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.

Sectoral Uncertainty

Staff Working Paper 2022-38 Efrem Castelnuovo, Kerem Tuzcuoglu, Luis Uzeda
We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary.

Cash, COVID-19 and the Prospects for a Canadian Digital Dollar

Staff Discussion Paper 2022-17 Walter Engert, Kim Huynh
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

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.

Nonparametric Identification of Incomplete Information Discrete Games with Non-equilibrium Behaviors

Staff Working Paper 2022-22 Erhao Xie
This paper jointly relaxes two assumptions in the literature that estimates games. These two assumptions are the parametric restriction on the model primitives and the restriction of equilibrium behaviors. Without imposing the above two assumptions, this paper identifies the primitives of the game.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C57

Resilience of bank liquidity ratios in the presence of a central bank digital currency

Staff Analytical Note 2022-5 Alissa Gorelova, Bena Lands, Maria teNyenhuis
Could Canadian banks continue to meet their regulatory liquidity requirements after the introduction of a cash-like retail central bank digital currency (CBDC)? We conduct a hypothetical exercise to estimate how a CBDC could affect bank liquidity by increasing the run-off rates of transactional retail deposits under four increasingly severe scenarios.
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