C3 - Multiple or Simultaneous Equation Models; Multiple Variables

• Monetary Policy Transmission to Small Business Loan Performance: Evidence from Loan-Level Data

  Staff Working Paper 2024-41 Rodrigo Sekkel, Tamon Takamura, Yaz Terajima

  We analyze the dynamic and heterogeneous responses of small-business loan performance to a monetary-policy shock using loan-level data in Canada. We find evidence of monetary policy transmission through the cash-flow channel and the aggregate demand channel as well as some, though limited, impact of collateral to discipline loan repayment.

  Content Type(s): Staff research, Staff working papers Topic(s): Firm dynamics, Monetary policy transmission JEL Code(s): C, C3, C32, E, E1, E17, E3, E37, E5, E52

• Beyond the averages: Measuring underlying wage growth using Labour Force Survey microdata

  Staff Analytical Note 2024-23 Fares Bounajm, Tessa Devakos, Gabriela Galassi

  When it comes to understanding the influence of labour costs on inflation, average wage growth is a misleading indicator because it is affected by composition effects. We propose an alternative measure that corrects for these effects by using microdata from the Labour Force Survey. Our new measure has many desirable properties, including reduced volatility and a better relationship with labour market fundamentals.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Econometric and statistical methods, Labour markets JEL Code(s): C, C3, C31, J, J2, J21, J3, J30, J31, J8, J82

• Let’s Get Physical: Impacts of Climate Change Physical Risks on Provincial Employment

  Staff Working Paper 2024-32 Thibaut Duprey, Soojin Jo, Geneviève Vallée

  We analyze 40 years’ worth of natural disasters using a local projection framework to assess their impact on provincial labour markets in Canada. We find that disasters decrease hours worked within a week and lower wage growth in the medium run. Our study highlights that disasters affect vulnerable workers through the income channel.

  Content Type(s): Staff research, Staff working papers Topic(s): Climate change, Labour markets, Regional economic developments JEL Code(s): C, C3, C33, E, E2, E24, J, J3, Q, Q5, Q54

• Decision Synthesis in Monetary Policy

  Staff Working Paper 2024-30 Tony Chernis, Gary Koop, Emily Tallman, Mike West

  We use Bayesian predictive decision synthesis to formalize monetary policy decision-making. We develop a case-study of monetary policy decision-making of an inflation-targeting central bank using multiple models in a manner that considers decision goals, expectations and outcomes.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Economic models, Monetary policy JEL Code(s): C, C1, C11, C3, C32, C5, C53

• Untapped Potential: Mobile Device Ownership and Mobile Payments in Canada

  Staff Working Paper 2024-25 Marie-Hélène Felt, Angelika Welte, Katrina Talavera

  We present a two-stage model of mobile phone and mobile payment usage that controls for selectivity. This reveals unobserved factors that work against having a mobile phone and toward mobile paying. Therefore, people who are unable to acquire or choose not to own a mobile device might have unmet payment needs.

  Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C3, C39, D, D1, D12, E, E4, E42

• Decomposing Systemic Risk: The Roles of Contagion and Common Exposures

  Staff Working Paper 2024-19 Grzegorz Halaj, Ruben Hipp

  We examine systemic risks within the Canadian banking sector, decomposing them into three contribution channels: contagion, common exposures, and idiosyncratic risk. Through a structural model, we dissect how interbank relationships and market conditions contribute to systemic risk, providing new insights for financial stability.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Economic models, Financial institutions, Financial stability JEL Code(s): C, C3, C32, C5, C51, G, G2, G21, L, L1, L14

• Predictive Density Combination Using a Tree-Based Synthesis Function

  Staff Working Paper 2023-61 Tony Chernis, Niko Hauzenberger, Florian Huber, Gary Koop, James Mitchell

  This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C3, C32, C5, C53

• Finding the balance—measuring risks to inflation and to GDP growth

  Staff Analytical Note 2023-18 Bruno Feunou, James Kyeong

  Using our new quantitative tool, we show how the risks to the inflation and growth outlooks have evolved over the course of 2023.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17

• Making It Real: Bringing Research Models into Central Bank Projections

  Staff Discussion Paper 2023-29 Marc-André Gosselin, Sharon Kozicki

  Macroeconomic projections and risk analyses play an important role in guiding monetary policy decisions. Models are integral to this process. This paper discusses how the Bank of Canada brings research models and lessons learned from those models into the central bank projection environment.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Economic models, Monetary policy JEL Code(s): C, C3, C32, C5, C51, E, E3, E37, E4, E47, E5, E52

• Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency

  Staff Discussion Paper 2023-19 Chinara Azizova, Bruno Feunou, James Kyeong

  This paper quantifies tail risks in the outlooks for Canadian inflation and real GDP growth by estimating their conditional distributions at a daily frequency. We show that the tail risk probabilities derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17