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
A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint Distributions Staff Working Paper 2018-29 Marie-Hélène Felt This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure. Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C14, D, D1, D14, E, E4, E41
Interest Rate and Renewal Risk for Mortgages Staff Analytical Note 2018-18 Olga Bilyk, Cameron MacDonald, Brian Peterson In this note, we explore two types of risk faced by holders of mortgages and home equity lines of credit (HELOCs) in the context of rising interest rates: interest rate risk and renewal risk. Content Type(s): Staff research, Staff analytical notes Topic(s): Credit and credit aggregates, Financial institutions, Interest rates, Recent economic and financial developments JEL Code(s): D, D1, E, E4, E5, G, G2, G21, G28
Did U.S. Consumers Respond to the 2014–2015 Oil Price Shock? Evidence from the Consumer Expenditure Survey Staff Working Paper 2018-13 Patrick Alexander, Louis Poirier The impact of oil price shocks on the U.S. economy is a topic of considerable debate. In this paper, we examine the response of U.S. consumers to the 2014–2015 negative oil price shock using representative survey data from the Consumer Expenditure Survey. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Domestic demand and components, Recent economic and financial developments JEL Code(s): D, D1, D12, E, E2, E21, Q, Q4, Q43
Home Equity Extraction and the Boom-Bust Cycle in Consumption and Residential Investment Staff Working Paper 2018-6 Xiaoqing Zhou The consumption boom-bust cycle in the 2000s coincided with large fluctuations in the volume of home equity borrowing. Contrary to conventional wisdom, I show that homeowners largely borrowed for residential investment and not consumption. Content Type(s): Staff research, Staff working papers Topic(s): Credit and credit aggregates, Economic models, Housing JEL Code(s): D, D1, E, E2, E3
Merchant Acceptance of Cash and Credit Cards at the Point of Sale Staff Analytical Note 2018-1 Ben Fung, Kim Huynh, Kerry Nield, Angelika Welte Recent data show that the use of credit cards in Canada has been increasing, while the use of cash has been declining. At the same time, only two-thirds of small or medium-sized businesses accept credit cards. Content Type(s): Staff research, Staff analytical notes Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services JEL Code(s): C, C2, D, D1, E, E4, E41
Recent Evolution of Canada’s Credit-to-GDP Gap: Measurement and Interpretation Staff Analytical Note 2017-25 Timothy Grieder, Dylan Hogg, Thibaut Duprey Over the past several years, the Bank for International Settlements has noted that Canada’s credit-to-GDP gap has widened and is above thresholds indicating future banking stress. Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Credit and credit aggregates, Financial stability, Monetary and financial indicators, Recent economic and financial developments, Sectoral balance sheet JEL Code(s): D, D1, E, E3, E32, G, G0, G01, G1, G2, G21, G3, G30
A Barometer of Canadian Financial System Vulnerabilities Staff Analytical Note 2017-24 Thibaut Duprey, Tom Roberts This note presents a composite indicator of Canadian financial system vulnerabilities—the Vulnerabilities Barometer. It aims to complement the Bank of Canada’s vulnerabilities assessment by adding a quantitative and synthesized perspective to the more granular (distributional) analysis presented in the Financial System Review. Content Type(s): Staff research, Staff analytical notes Topic(s): Econometric and statistical methods, Financial stability, Monetary and financial indicators JEL Code(s): C, C1, C14, C4, C40, D, D1, D14, E, E3, E32, E6, E66, F, F0, F01, G, G0, G01, G1, G15, G2, G21, H, H6, H63
November 28, 2017 Analysis of Household Vulnerabilities Using Loan-Level Mortgage Data Financial System Review - November 2017 Olga Bilyk, Alexander Ueberfeldt, Yang Xu This report examines detailed data on home mortgages to provide a better understanding of the vulnerabilities associated with the mortgage market. The proportion of low-ratio mortgages is growing, particularly in regions with strong house price growth. Moreover, these borrowers exhibit less flexibility to adverse shocks, since they have high debt levels relative to income and have taken mortgages with long amortization periods. Content Type(s): Publications, Financial System Review articles Topic(s): Credit and credit aggregates, Recent economic and financial developments, Sectoral balance sheet JEL Code(s): D, D1, D12, D14, G, G2, G21, G28
Identification of Random Resource Shares in Collective Households Without Preference Similarity Restrictions Staff Working Paper 2017-45 Geoffrey R. Dunbar, Arthur Lewbel, Krishna Pendakur Resource shares, defined as the fraction of total household spending going to each person in a household, are important for assessing individual material well-being, inequality and poverty. They are difficult to identify because consumption is measured typically at the household level, and many goods are jointly consumed, so that individual-level consumption in multi-person households is not directly observed. Content Type(s): Staff research, Staff working papers Topic(s): Domestic demand and components, Econometric and statistical methods JEL Code(s): C, C3, C31, D, D1, D11, D12, D13, I, I3, I32