C8 - Data Collection and Data Estimation Methodology; Computer Programs

• Low Response Rate from Merchants? Sample and Ask Consumers! An Application of Indirect Sampling Under a Consumer-Merchant Bipartite Network

  Technical Report No. 126 Heng Chen, Joy Wu

  Under the consumer-merchant bipartite network, we apply the indirect sampling approach to estimate merchant payment acceptance through a consumer payment diary.

  Content Type(s): Staff research, Technical reports Research Topic(s): Bank notes, Econometric and statistical methods JEL Code(s): C, C8, C80, C83, E, E5

• Canadian Bitcoin Ownership in 2023: Key Takeaways

  Staff Discussion Paper 2025-4 Daniela Balutel, Marie-Hélène Felt, Doina Rusu

  The Bitcoin Omnibus Survey is an important tool for monitoring Canadians’ awareness and ownership of bitcoin and other cryptoassets over time. In this paper, we present data highlights from the 2023 survey.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C8, C81, E, E4, O, O5, O51

• Bouncing Back: How Mothballing Curbs Prices

  Staff Working Paper 2024-51 Thibaut Duprey, Artur Kotlicki, Daniel E. Rigobon, Philip Schnattinger

  We investigate the macroeconomic impacts of mothballed businesses—those that closed temporarily—on sectoral equilibrium prices after a negative demand shock. Our results suggest that pandemic fiscal support for temporary closures may have eased inflationary pressures.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Firm dynamics, Fiscal policy, Inflation and prices JEL Code(s): C, C5, C55, C8, C81, D, D2, D22, E, E3, E32

• Familiarity with Crypto and Financial Concepts: Cryptoasset Owners, Non-Owners, and Gender Differences

  Staff Working Paper 2024-48 Daniela Balutel, Walter Engert, Christopher Henry, Kim Huynh, Doina Rusu, Marcel Voia

  Measuring cryptoasset knowledge alongside financial knowledge enhances our understanding of individuals' decisions to purchase cryptoassets. This paper uses microdata from the Bank of Canada’s Bitcoin Omnibus Survey to examine gender differences and the interrelationship between crypto and financial knowledge through an empirical joint analysis.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C8, C81, D, D1, D14, D9, D91, G, G5, G53, O, O5, O51

• Seasonal Adjustment of Weekly Data

  Staff Discussion Paper 2024-17 Jeffrey Mollins, Rachit Lumb

  The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C4, C5, C52, C8, E, E0, E01, E2, E21

• Survey of Indigenous Firms: A Snapshot of Wages, Prices and Financing in the Indigenous Business Sector in Canada

  Staff Discussion Paper 2024-4 Calista Cheung, James Fudurich, Janki Shah, Farrukh Suvankulov

  What sources of financing do Indigenous-owned businesses in Canada use, and what are their expectations about prices, wages and inflation? We find Indigenous-owned firms are significantly less reliant on financial institutions as sources of financing compared with non-Indigenous firms. We also find Indigenous-owned firms have higher inflation expectations and weaker wage-growth expectations.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Firm dynamics JEL Code(s): C, C8, C83, D, D0, G, G3, G38, J, J1, J15

• COVID-19 Hasn’t Killed Merchant Acceptance of Cash: Results from the 2023 Merchant Acceptance Survey

  Staff Discussion Paper 2024-2 Angelika Welte, Katrina Talavera, Liang Wang, Joy Wu

  The Bank of Canada’s Merchant Acceptance Survey finds that 96% of small and medium-sized businesses in Canada accepted cash in 2023. Acceptance of debit and credit cards has increased to 89%, and acceptance of digital payments has also increased. However, Canada is far from being a cashless society.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C8, D, D2, D22, E, E4, L, L2
• January 15, 2024

  Flood risk and residential lending

  Craig Johnston, Geneviève Vallée, Hossein Hosseini Jebeli, Miguel Molico, Marie-Christine Tremblay, Aidan Witts

  We present key findings of a recent study that evaluates the credit risk that flooding poses to the residential lending activities of Canadian banks and credit unions. Results show that such risk currently appears modest but could become larger with climate change.

  Content Type(s): Publications, Financial System Hub articles Research Topic(s): Central bank research, Climate change, Credit risk management, Econometric and statistical methods, Financial institutions, Financial stability JEL Code(s): C, C8, C81, G, G2, G21, Q, Q5, Q54

• Climate-Related Flood Risk to Residential Lending Portfolios in Canada

  Staff Discussion Paper 2023-33 Craig Johnston, Geneviève Vallée, Hossein Hosseini Jebeli, Brett Lindsay, Miguel Molico, Marie-Christine Tremblay, Aidan Witts

  We assess the potential financial risks of current and projected flooding caused by extreme weather events in Canada. We focus on the residential real estate secured lending (RESL) portfolios of Canadian financial institutions (FIs) because RESL portfolios are an important component of FIs’ balance sheets and because the assets used to secure such loans are immobile and susceptible to climate-related extreme weather events.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Central bank research, Climate change, Credit risk management, Econometric and statistical methods, Financial institutions, Financial stability JEL Code(s): C, C8, C81, G, G2, G21, Q, Q5, Q54

• Identifying Nascent High-Growth Firms Using Machine Learning

  Staff Working Paper 2023-53 Stephanie Houle, Ryan Macdonald

  Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Econometric and statistical methods, Firm dynamics JEL Code(s): C, C5, C55, C8, C81, L, L2, L25