C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Analysis

• 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 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 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 Topic(s): Econometric and statistical methods, Firm dynamics JEL Code(s): C, C5, C55, C8, C81, L, L2, L25

• Cryptoasset Ownership and Use in Canada: An Update for 2022

  Staff Discussion Paper 2023-14 Daniela Balutel, Christopher Henry, Doina Rusu

  We find that Bitcoin ownership declined from 13% in 2021 to 10% in 2022. This drop occurred against a background of steep price declines and an increasingly tight regulatory atmosphere.

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

• Historical Data on Repurchase Agreements from the Canadian Depository for Securities

  Technical Report No. 121 Maxim Ralchenko, Adrian Walton

  We develop an algorithm that extracts information about sale and repurchase agreements (repos) from disaggregated settlement data in order to generate a new historical dataset for research.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C5, C55, C8, C81, G, G1, G10

• Business Closures and (Re)Openings in Real Time Using Google Places

  Staff Working Paper 2022-1 Thibaut Duprey, Daniel E. Rigobon, Philip Schnattinger, Artur Kotlicki, Soheil Baharian, T. R. Hurd

  The COVID-19 pandemic highlighted the need for policy-makers to closely monitor disruptions to the retail and food business sectors. We present a new method to measure business opening and closing rates using real-time data from Google Places, the dataset behind the Google Maps service.

  Content Type(s): Staff research, Staff working papers Topic(s): Firm dynamics, Recent economic and financial developments JEL Code(s): C, C5, C55, C8, C81, D, D2, D22, E, E3, E32

• Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

  Staff Working Paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez

  Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

  Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C52, C6, C65, C8, C81, E, E4, E42, E5, E51

• Sample Calibration of the Online CFM Survey

  Technical Report No. 118 Marie-Hélène Felt, David Laferrière

  The Canadian Financial Monitor (CFM) survey uses non-probability sampling for data collection, so selection bias is likely. We outline methods for obtaining survey weights and discuss the conditions necessary for these weights to eliminate selection bias. We obtain calibration weights for the 2018 and 2019 online CFM samples.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C8, C81, C83

• 2017 Methods-of-Payment Survey: Sample Calibration and Variance Estimation

  Technical Report No. 114 Heng Chen, Marie-Hélène Felt, Christopher Henry

  This technical report describes sampling, weighting and variance estimation for the Bank of Canada’s 2017 Methods-of-Payment Survey. Under quota sampling, a raking ratio method is implemented to generate weights with both post-stratification and nonparametric nonresponse weight adjustments.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C8, C81, C83

• What’s Up with Unit Non-Response in the Bank of Canada’s Business Outlook Survey? The Effect of Staff Tenure

  Staff Discussion Paper 2017-11 Sarah Miller, David Amirault, Laurent Martin

  Since 1997, the Bank of Canada’s regional offices have been conducting the Business Outlook Survey (BOS), a quarterly survey of business conditions. Survey responses are gathered through face-to-face, confidential consultations with a sample of private sector firms representative of the various sectors, firm sizes and regions across Canada.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods, Firm dynamics, Regional economic developments JEL Code(s): C, C2, C21, C8, C81, D, D2, D22