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7 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.

Covariates Hiding in the Tails

Staff Working Paper 2021-45 Milian Bachem, Lerby Ergun, Casper G. de Vries
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.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C1, C14, C5, C58

Tail Index Estimation: Quantile-Driven Threshold Selection

The most extreme events, such as economic crises, are rare but often have a great impact. It is difficult to precisely determine the likelihood of such events because the sample is small.

Characterizing the Canadian Financial Cycle with Frequency Filtering Approaches

Staff Analytical Note 2018-34 Andrew Lee-Poy
In this note, I use two multivariate frequency filtering approaches to characterize the Canadian financial cycle by capturing fluctuations in the underlying variables with respect to a long-term trend. The first approach is a dynamically weighted composite, and the second is a stochastic cycle model.

Challenges in Implementing Worst-Case Analysis

Staff Working Paper 2018-47 Jon Danielsson, Lerby Ergun, Casper G. de Vries
Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.
Content Type(s): Staff research, Staff working papers Topic(s): Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58

Asymmetric Risks to the Economic Outlook Arising from Financial System Vulnerabilities

Staff Analytical Note 2018-6 Thibaut Duprey
When financial system vulnerabilities are elevated, they can give rise to asymmetric risks to the economic outlook. To illustrate this, I consider the economic outlook presented in the Bank of Canada’s October 2017 Monetary Policy Report in the context of two key financial system vulnerabilities: high levels of household indebtedness and housing market imbalances.

Financial Stress, Monetary Policy, and Economic Activity

Staff Working Paper 2010-12 Fuchun Li, Pierre St-Amant
This paper examines empirically the impact of financial stress on the transmission of monetary policy shocks in Canada. The model used is a threshold vector autoregression in which a regime change occurs if financial stress conditions cross a critical threshold.