C1 - Econometric and Statistical Methods and Methodology: General

• Bitcoin Awareness, Ownership and Use: 2016–20

  Staff discussion paper 2022-10 Daniela Balutel, Marie-Hélène Felt, Gradon Nicholls, Marcel Voia

  In this paper, we examine trends in Canadian ownership of Bitcoin and other cryptocurrencies from 2016 to 2020 using data from surveys conducted by the Bank of Canada.

  Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, E, E4, O, O5, O51 Research Theme(s): Money and payments, Cash and bank notes, Digital assets and fintech

• Cash and COVID-19: What happened in 2021

  Staff discussion paper 2022-8 Heng Chen, Walter Engert, Kim Huynh, Daneal O’Habib, Joy Wu, Julia Zhu

  Using data from the Bank Note Distribution System and consumer surveys, we find that bank notes in circulation remained high through 2021. Canadians continued to rely on electronic methods of payment, but a significant share also continued using cash for payments.

  Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54 Research Theme(s): Money and payments, Cash and bank notes, Retail payments

• 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 JEL Code(s): C, C0, C01, C1, C14, C5, C58 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods

• Cash and COVID-19: The impact of the second wave in Canada

  Staff discussion paper 2021-12 Heng Chen, Walter Engert, Marie-Hélène Felt, Kim Huynh, Gradon Nicholls, Daneal O’Habib, Julia Zhu

  The COVID-19 pandemic significantly increased the demand for cash. Cash in circulation increased sharply from March through December 2020, particularly in the early months of this period. Although use of electronic methods of payment also increased significantly, cash use for payments remains high for low-value transactions and among certain demographic groups.

  Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54 Research Theme(s): Money and payments, Cash and bank notes, Retail payments

• Cash and COVID-19: The Effects of Lifting Containment Measures on Cash Demand and Use

  Staff discussion paper 2021-3 Heng Chen, Walter Engert, Kim Huynh, Gradon Nicholls, Julia Zhu

  Using Bank Note Distribution System data on the demand for cash up to September 2020, we find that demand was strong. This is true even though cash use for payments declined early in the pandemic. When mobility restrictions and lockdown measures were eased, cash use for payments increased sharply but remained less popular than electronic methods of payment.

  Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54 Research Theme(s): Money and payments, Cash and bank notes, Retail payments

• (Optimal) Monetary Policy with and without Debt

  Staff working paper 2021-5 Boris Chafwehé, Rigas Oikonomou, Romanos Priftis, Lukas Vogel

  How should policy be designed at high debt levels, when fiscal authorities have little room to adjust taxes? Assigning the monetary authority a role in achieving debt sustainability makes it less effective in stabilizing inflation and output.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, E, E3, E31, E5, E52, E58, E6, E62 Research Theme(s): Models and tools, Economic models, Monetary policy, Monetary policy framework and transmission, Monetary policy tools and implementation, Real economy and forecasting

• Networking the Yield Curve: Implications for Monetary Policy

  Staff working paper 2021-4 Tatjana Dahlhaus, Julia Schaumburg, Tatevik Sekhposyan

  We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C18, C2, C21, C5, C53, E, E4, E43, E44, 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

• Understanding Trend Inflation Through the Lens of the Goods and Services Sectors

  Staff working paper 2020-45 Yunjong Eo, Luis Uzeda, Benjamin Wong

  The goods and services sectors have experienced considerably different dynamics over the past three decades. Our goal in this paper is to understand how such contrasting behaviors at the sectoral level affect the aggregate level of trend inflation dynamics.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C3, C32, E, E3, E31, E5, E52 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Monetary policy framework and transmission

• On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

  Staff working paper 2020-42 Ruben Hipp

  Banks’ business interactions create a network of relationships that are hidden in the correlations of bank stock returns. But for policy interventions, we need causality to understand how the network changes. Thus, this paper looks for the causal network anticipated by investors.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C3, C32, C5, C58, L, L1, L14 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods

• The New Benchmark for Forecasts of the Real Price of Crude Oil

  Staff working paper 2020-39 Amor Aniss Benmoussa, Reinhard Ellwanger, Stephen Snudden

  How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C5, C53, Q, Q4, Q47 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting