C1 - Econometric and Statistical Methods and Methodology: General

• Extreme Downside Risk in Asset Returns

  Staff Working Paper 2019-46 Lerby Ergun

  Financial markets can experience sudden and extreme downward movements. Investors are highly concerned about the performance of their assets in such scenarios. Some assets perform badly in a downturn in the market; others have milder reactions.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Asset Pricing, Econometric and statistical methods JEL Code(s): C, C1, C14, G, G1, G11, G12

• 2018 Bitcoin Omnibus Survey: Awareness and Usage

  Staff Discussion Paper 2019-10 Christopher Henry, Kim Huynh, Gradon Nicholls, Mitchell Nicholson

  The Bank of Canada continues to use the Bitcoin Omnibus Survey (BTCOS) to monitor trends in Canadians’ awareness, ownership and use of Bitcoin. The most recent iteration was conducted in late 2018, following an 85 percent decline in the price of Bitcoin throughout the year.

  Content Type(s): Staff Research, Staff Discussion Papers Topic(s): Bank notes, Digital Currencies and Fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4, O, O5, O51

• Tail Index Estimation: Quantile-Driven Threshold Selection

  Staff Working Paper 2019-28 Jon Danielsson, Lerby Ergun, Laurens de Haan, Casper G. de Vries

  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.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C0, C01, C1, C14, C5, C58

• 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.

  Content Type(s): Staff Research, Staff Analytical Notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Monetary and financial indicators, Recent economic and financial developments JEL Code(s): C, C0, C01, C1, C13, C14, C18, C3, C32, C5, C51, C52, E, E3, E32, E6, E66, G, G0, G01, G1, G18

• Monetary Policy Uncertainty: A Tale of Two Tails

  Staff Working Paper 2018-50 Tatjana Dahlhaus, Tatevik Sekhposyan

  We document a strong asymmetry in the evolution of federal funds rate expectations and map this observed asymmetry into measures of monetary policy uncertainty. We show that periods of monetary policy tightening and easing are distinctly related to downside (policy rate is higher than expected) and upside (policy rate is lower than expected) uncertainty.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Monetary policy communications, Transmission of monetary policy, Uncertainty and monetary policy JEL Code(s): C, C1, C18, C3, C32, E, E0, E02, E4, E43, E5, E52

• 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

• A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint Distributions

  Staff Working Paper 2018-29 Marie-Hélène Felt

  This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure.

  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, C14, D, D1, D14, E, E4, E41

• Bitcoin Awareness and Usage in Canada: An Update

  Staff Analytical Note 2018-23 Christopher Henry, Kim Huynh, Gradon Nicholls

  The results of our 2017 Bitcoin Omnibus Survey (December 12 to 15, 2017) when compared with those from 2016 show that Bitcoin “awareness” increased from 64 to 85 per cent, while ownership increased from 2.9 to 5.0 per cent. Most Bitcoin purchasers are using the cryptocurrency as an investment and not as a means of payment for goods or services.

  Content Type(s): Staff Research, Staff Analytical Notes Topic(s): Bank notes, Digital Currencies and Fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4

• Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data

  Staff Working Paper 2018-28 Valéry Dongmo Jiongo, Pierre Nguimkeu

  This paper proposes a new bootstrap procedure for mean squared errors of robust small-area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite sample performance through Monte Carlo simulations.

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Bank notes, Econometric and statistical methods JEL Code(s): C, C1, C13, C15, C8, C83, E, E4, E41

• On the Evolution of the United Kingdom Price Distributions

  Staff Working Paper 2018-25 Ba M. Chu, Kim Huynh, David T. Jacho-Chávez, Oleksiy Kryvtsov

  We propose a functional principal components method that accounts for stratified random sample weighting and time dependence in the observations to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK).

  Content Type(s): Staff Research, Staff Working Papers Topic(s): Econometric and statistical methods, Inflation and prices JEL Code(s): C, C1, C14, C8, C83, E, E3, E31, E37