Technical Reports - Bank of Canada
https://www.bankofcanada.ca/rss-feeds/
Bank of Canada RSS Feedsen2024-03-28T08:12:47+00:00BoC–BoE Sovereign Default Database: Appendix and References
https://www.bankofcanada.ca/2023/07/technical-report-125/
Since 2014, the Bank of Canada (BoC) has maintained a comprehensive database of sovereign defaults to systematically measure and aggregate the nominal value of the different types of sovereign government debt in default. The database is posted on the BoC’s website and is updated annually in partnership with the Bank of England (BoE).2023-07-28T11:13:28+00:00enBoC–BoE Sovereign Default Database: Appendix and References2023-07-28Debt managementDevelopment economicsFinancial stabilityInternational financial marketsTechnical Report 2023-125https://www.bankofcanada.ca/wp-content/uploads/2023/07/tr125.pdfTechnical Report 2023-125David BeersObiageri NdukweAlex CharronJuly 2023FF3F34GG1G10G14G15BoC–BoE Sovereign Default Database: Methodology and Assumptions
https://www.bankofcanada.ca/2023/07/technical-report-124/
The Bank of Canada (BoC), in partnership with the Bank of England (BoE), developed a comprehensive database of sovereign defaults in 2014. The database is posted on the Bank of Canada’s website and updated annually. The BoC–BoE database draws on datasets published by various public and private sector sources. It combines elements of these, together with new information, to develop comprehensive estimates of stocks of government obligations in default.2023-07-28T11:04:38+00:00enBoC–BoE Sovereign Default Database: Methodology and Assumptions2023-07-28Debt managementDevelopment economicsFinancial stabilityInternational financial marketsTechnical Report 2023-124https://www.bankofcanada.ca/wp-content/uploads/2023/07/tr124.pdfTechnical Report 2023-124David BeersObiageri NdukweAlex CharronJuly 2023FF3F34GG1G10G14G15Risk Amplification Macro Model (RAMM)
https://www.bankofcanada.ca/2023/01/technical-report-123/
The Risk Amplification Macro Model (RAMM) is a new nonlinear two-country dynamic model that captures rare but severe adverse shocks. The RAMM can be used to assess the financial stability implications of both domestic and foreign-originated risk scenarios.2023-01-26T10:06:18+00:00enRisk Amplification Macro Model (RAMM)2023-01-26Business fluctuations and cyclesEconometric and statistical methodsFinancial stabilityMonetary policy transmissionTechnical Report 123https://www.bankofcanada.ca/wp-content/uploads/2023/01/tr123.pdfRisk Amplification Macro Model (RAMM)Kerem TuzcuogluJanuary 2023CC5C51EE3E37E4E44FF4F44Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model
https://www.bankofcanada.ca/2022/10/technical-report-122/
We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.2022-10-03T16:29:10+00:00enForecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model2022-10-03Economic modelsFinancial institutionsFinancial stabilityFinancial system regulation and policiesTechnical Report 2022-122https://www.bankofcanada.ca/wp-content/uploads/2022/10/tr122.pdfTechnical Report 2022-122Gabriel BruneauThibaut DupreyRuben HippOctober 2022CC2C22C5C52C53GG1G17G2G21G28Historical Data on Repurchase Agreements from the Canadian Depository for Securities
https://www.bankofcanada.ca/2022/05/technical-report-121/
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.2022-05-03T08:57:44+00:00enHistorical Data on Repurchase Agreements from the Canadian Depository for Securities2022-05-03Econometric and statistical methodsFinancial marketsTechnical Report 121https://www.bankofcanada.ca/wp-content/uploads/2022/05/tr121.pdfHistorical Data on Repurchase Agreements from the Canadian Depository for SecuritiesMaxim RalchenkoAdrian WaltonMay 2022CC5C55C8C81GG1G10Assessing Climate-Related Financial Risk: Guide to Implementation of Methods
https://www.bankofcanada.ca/2022/01/technical-report-120/
A pilot project on climate transition scenarios by the Bank of Canada and the Office of the Superintendent of Financial Institutions assessed climate-related credit and market risks. This report describes the project’s methodologies and provides guidance on implementing them.2022-01-14T12:00:37+00:00enAssessing Climate-Related Financial Risk: Guide to Implementation of Methods2022-01-14Climate changeCredit and credit aggregatesEconometric and statistical methodsFinancial stabilityTechnical Report 2022-120https://www.bankofcanada.ca/wp-content/uploads/2021/11/tr120.pdfHossein HosseiniCraig JohnstonCraig LoganMiguel MolicoXiangjin ShenMarie-Christine TremblayJanuary 2022CC5C53C8C83GG1G3G32ToTEM III: The Bank of Canada’s Main DSGE Model for Projection and Policy Analysis
https://www.bankofcanada.ca/2021/06/technical-report-119/
ToTEM III is the most recent generation of the Bank of Canada’s main dynamic stochastic general equilibrium model for projection and policy analysis. The model helps Bank staff tell clear and coherent stories about the Canadian economy’s current state and future evolution.2021-06-28T08:50:52+00:00enToTEM III: The Bank of Canada’s Main DSGE Model for Projection and Policy Analysis2021-06-28Business fluctuations and cyclesEconomic modelsHousingInterest ratesMonetary policyTechnical Report 2021-119https://www.bankofcanada.ca/wp-content/uploads/2021/06/tr119.pdfTechnical Report 2021-119Paul CorriganHélène DesgagnésJosé DorichVadym LepetyukWataru MiyamotoYang ZhangJune 2021EE1E17E2E20E3E30E4E40E5E50E6E62E65FF4F40F41GG5G51Sample Calibration of the Online CFM Survey
https://www.bankofcanada.ca/2020/08/technical-report-118/
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.2020-08-12T08:56:17+00:00enSample Calibration of the Online CFM Survey2020-08-12Econometric and statistical methodsTechnical Report 2020-118https://www.bankofcanada.ca/wp-content/uploads/2020/08/tr118.pdfTechnical Report 2020-118Marie-Hélène FeltDavid LaferrièreAugust 2020CC8C81C83BoC–BoE Sovereign Default Database: Methodology, Assumptions and Sources
https://www.bankofcanada.ca/2020/06/technical-report-117/
Until recently, few efforts have been made to systematically measure and aggregate the nominal value of the different types of sovereign government debt in default. To help fill this gap, the Bank of Canada (BoC) developed a comprehensive database of sovereign defaults that is posted on its website and updated in partnership with the Bank of England (BoE).2020-06-30T09:00:39+00:00enBoC–BoE Sovereign Default Database: Methodology, Assumptions and Sources2020-06-30Debt managementDevelopment economicsFinancial institutionsInternational financial marketsTechnical Report no 117https://www.bankofcanada.ca/wp-content/uploads/2020/06/tr117.pdfDavid BeersElliot JonesJohn WalshJune 2020FF3F34GG1G10G14G15IMPACT: The Bank of Canada’s International Model for Projecting Activity
https://www.bankofcanada.ca/2020/03/technical-report-116/
We present the structure and features of the International Model for Projecting Activity (IMPACT), a global semi-structural model used to conduct projections and policy analysis at the Bank of Canada. Major blocks of the model are developed based on the rational error correction framework of Kozicki and Tinsley (1999), which allows the model to strike a balance between theoretical structure and empirical performance.2020-03-06T11:09:46+00:00enIMPACT: The Bank of Canada’s International Model for Projecting Activity2020-03-06Business fluctuations and cyclesEconometric and statistical methodsEconomic modelsInternational topicsTechnical Report 116https://www.bankofcanada.ca/wp-content/uploads/2020/03/tr116.pdfTechnical Report 116Patrick BlagraveClaudia GodboutJustin-Damien GuénetteRené LalondeNikita PerevalovMarch 2020CC6C68EE2E27E3E37FF0F01F3F32F4F47