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 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.
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.
Nonresponse is a considerable challenge in the Retailer Survey on the Cost of Payment Methods conducted by the Bank of Canada in 2015. There are two types of nonresponse in this survey: unit nonresponse, in which a business does not reply to the entire survey, and item nonresponse, in which a business does not respond to particular questions within the survey.
Household debt can be an important source of vulnerability to the financial system. This technical report describes the Household Risk Assessment Model (HRAM) that has been developed at the Bank of Canada to stress test household balance sheets at the individual level.
In this paper, we investigate how liquidity conditions in Canada may affect domestic and/or foreign lending of globally active banks and whether this transmission is influenced by individual bank characteristics.
Sampling units for the 2013 Methods-of-Payment Survey were selected through an approximate stratified random sampling design. To compensate for non-response and non-coverage, the observations are weighted through a raking procedure.
Sample calibration is a procedure that utilizes sample and national-level demographic distribution information to weight survey participants. The objective of calibration is to weight the sample so that it is demographically representative of the target population.