Maturity Composition and the Demand for Government Debt Staff Working Paper 2020-29 Jason Allen, Jakub Kastl, Milena Wittwer The main objectives of debt management are to raise stable and low-cost funding to meet the government’s financial needs and to maintain a well-functioning market for government securities. Content Type(s): Staff research, Staff working papers Topic(s): Debt management, Financial markets JEL Code(s): C, C1, C14, D, D4, D44, E, E5, E58, G, G1, G12
Cash and COVID-19: The impact of the pandemic on demand for and use of cash Staff Discussion Paper 2020-6 Heng Chen, Walter Engert, Kim Huynh, Gradon Nicholls, Mitchell Nicholson, Julia Zhu Consumer spending declined significantly during the recent COVID-19 pandemic. This negative shock likely reduced spending across all methods of payment (cash, debit, credit, etc.). The mix of payment methods consumers use could also be affected. We study how the pandemic has influenced the demand for and use of cash. We also offer insights into the use of other payment methods, such as debit and credit cards. Content Type(s): Staff research, Staff discussion papers Topic(s): Bank notes, Central bank research, Coronavirus disease (COVID-19), Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54
Endogenous Time Variation in Vector Autoregressions Staff Working Paper 2020-16 Danilo Leiva-Leon, Luis Uzeda We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence — contemporaneously and with a lag — the dynamics of the intercept and autoregressive coefficients in these models. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Inflation and prices, Monetary policy transmission JEL Code(s): C, C1, C11, C3, C32, E, E3, E31, E5, E52
Identifying Consumer-Welfare Changes when Online Search Platforms Change Their List of Search Results Staff Working Paper 2020-5 Ryan Martin Online shopping is often guided by search platforms. Consumers type keywords into query boxes, and search platforms deliver a list of products. Consumers' attention is limited, and exhaustive searches are often impractical. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Market structure and pricing JEL Code(s): C, C1, C14, D, D1, D11, D12, D6, D8, D83, L, L4, L40
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, Casper G. de Vries, Laurens de Haan 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 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