Assessing Vulnerabilities in Emerging-Market Economies Staff discussion paper 2018-13 Tatjana Dahlhaus, Alexander Lam This paper introduces a new tool to monitor economic and financial vulnerabilities in emerging-market economies. We obtain vulnerability indexes for several early warning indicators covering 26 emerging markets from 1990 to 2017 and use them to monitor the evolution of vulnerabilities before, during and after an economic or financial crisis. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C8, C82, F, F3, F34, G, G0, G01, G1, G15 Research Theme(s): Financial markets and funds management, Market functioning, Financial system, Financial stability and systemic risk, Structural challenges, International trade, finance and competitiveness
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 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 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models
The Size and Destination of China’s Portfolio Outflows Staff discussion paper 2018-11 Rose Cunningham, Eden Hatzvi, Kun Mo The size of China’s financial system raises the possibility that the liberalization of its capital account could have a large effect on the global financial system. This paper provides a counterfactual scenario analysis that estimates what the size and direction of China’s overseas portfolio investments would have been in 2015 if China had had no restrictions on these outflows. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C2, C23, F, F2, F21, F3, F32, G, G1, G15 Research Theme(s): Financial system, Financial stability and systemic risk, Structural challenges, International trade, finance and competitiveness
Disaggregating Household Sensitivity to Monetary Policy by Expenditure Category Staff analytical note 2018-32 Tony Chernis, Corinne Luu Because the Bank of Canada has started withdrawing monetary stimulus, monitoring the transmission of these changes to monetary policy will be important. Subcomponents of consumption and housing will likely respond differently to a monetary policy tightening, both in terms of the aggregate effect and timing. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C3, C32, E, E2, E21, E22, E4, E43, E47, E5, E52 Research Theme(s): Financial system, Household and business credit, Monetary policy, Monetary policy framework and transmission, Real economy and forecasting
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 JEL Code(s): C, C1, C18, C3, C32, E, E0, E02, E4, E43, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Monetary policy framework and transmission, Monetary policy tools and implementation, Real economy and forecasting
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 JEL Code(s): C, C0, C01, C1, C14, C5, C58 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods
How Long Does It Take You to Pay? A Duration Study of Canadian Retail Transaction Payment Times Staff working paper 2018-46 Geneviève Vallée Using an exclusive data set of payment times for retail transactions made in Canada, I show that cash is the most time-efficient method of payment (MOP) when compared with payments by debit and credit cards. I model payment efficiency using Cox proportional hazard models, accounting for consumer choice of MOP. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C25, C3, C36, C4, C41, D, D2, D23, E, E4, E41, E42 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes, Retail payments
Nowcasting Canadian Economic Activity in an Uncertain Environment Staff discussion paper 2018-9 Tony Chernis, Rodrigo Sekkel This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, C53, E, E3, E37, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
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 JEL Code(s): C, C1, C14, D, D1, D14, E, E4, E41 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes
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 JEL Code(s): C, C1, C12, E, E4 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes, Digital assets and fintech