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 and uncertainty, Monetary policy communications, Monetary policy transmission 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
Noisy Monetary Policy Staff Working Paper 2018-23 Tatjana Dahlhaus, Luca Gambetti We introduce limited information in monetary policy. Agents receive signals from the central bank revealing new information (“news") about the future evolution of the policy rate before changes in the rate actually take place. However, the signal is disturbed by noise. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial markets, Monetary policy implementation, Monetary policy transmission JEL Code(s): C, C1, C18, C3, C32, E, E0, E02, E4, E43, E5, E52
State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models Staff Working Paper 2018-14 Luis Uzeda Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Inflation and prices JEL Code(s): C, C1, C11, C15, C5, C51, C53
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. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Financial system regulation and policies, Monetary and financial indicators, Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C0, C01, C1, C11, C15, E, E1, E17, E3, E32, E37, E4, E44, E47, E5, E58, E6, E66, G, G0, G01, G1, G18
A Barometer of Canadian Financial System Vulnerabilities Staff Analytical Note 2017-24 Thibaut Duprey, Tom Roberts This note presents a composite indicator of Canadian financial system vulnerabilities—the Vulnerabilities Barometer. It aims to complement the Bank of Canada’s vulnerabilities assessment by adding a quantitative and synthesized perspective to the more granular (distributional) analysis presented in the Financial System Review. Content Type(s): Staff research, Staff analytical notes Topic(s): Econometric and statistical methods, Financial stability, Monetary and financial indicators JEL Code(s): C, C1, C14, C4, C40, D, D1, D14, E, E3, E32, E6, E66, F, F0, F01, G, G0, G01, G1, G15, G2, G21, H, H6, H63