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86 result(s)

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

BoC–BoE Sovereign Default Database: Methodology, Assumptions and Sources

Technical Report No. 117 David Beers, Elliot Jones, John Walsh
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).

IMPACT: The Bank of Canada’s International Model for Projecting Activity

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.

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

The Framework for Risk Identification and Assessment

Technical Report No. 113 Cameron MacDonald, Virginie Traclet
Risk assessment models are an important component of the Bank’s analytical tool kit for assessing the resilience of the financial system. We describe the Framework for Risk Identification and Assessment (FRIDA), a suite of models developed at the Bank of Canada to quantify the impact of financial stability risks to the broader economy and a range of financial system participants (households, businesses and banks).
Content Type(s): Staff research, Technical reports Topic(s): Economic models, Financial institutions, Financial stability, Housing JEL Code(s): C, C3, C5, C6, C7, D, D1, E, E0, E00, E2, E27, E3, E37, E4, E47, G, G0, G2, G21

The MacroFinancial Risk Assessment Framework (MFRAF), Version 2.0

Technical Report No. 111 Jose Fique
This report provides a detailed technical description of the updated MacroFinancial Risk Assessment Framework (MFRAF), which replaces the version described in Gauthier, Souissi and Liu (2014) as the Bank of Canada’s stress-testing model for banks with a focus on domestic systemically important banks (D-SIBs).

The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Estimation of the Total Private Cost for Large Businesses

Technical Report No. 110 Valéry Dongmo Jiongo
The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods faced low response rates and outliers in sample data for two of its retailer strata: chains and large independent businesses. This technical report investigates whether it is appropriate to combine these two strata to produce more accurate estimates of the total private cost to large businesses of the main payment methods.
Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C12, C8, C83

The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Calibration for Single-Location Retailers

Technical Report No. 109 Heng Chen, Rallye Shen
Calibrated weights are created to (a) reduce the nonresponse bias; (b) reduce the coverage error; and (c) make the weighted estimates from the sample consistent with the target population in terms of certain key variables.