A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models Staff discussion paper 2023-23 Donald Coletti The fourth generation of Bank of Canada projection and policy analysis models seeks to improve our understanding of inflation dynamics, the supply side of the economy and the underlying risks faced by policy-makers coming from uncertainty about how the economy functions. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, C50, C51, C52, C53, C54, C55 Research Theme(s): Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Monetary policy framework and transmission, Real economy and forecasting
Predicting Changes in Canadian Housing Markets with Machine Learning Staff discussion paper 2023-21 Johan Brannlund, Helen Lao, Maureen MacIsaac, Jing Yang We apply two machine learning algorithms to forecast monthly growth of house prices and existing homes sales in Canada. Although the algorithms can sometimes outperform a linear model, the improvement in forecast accuracy is not always statistically significant. Content Type(s): Staff research, Staff discussion papers JEL Code(s): A, C, C4, C45, C5, C53, D, D2, R, R2, R3 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
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 JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis Staff working paper 2023-45 Tony Chernis I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Generalized Autoregressive Gamma Processes Staff working paper 2023-40 Bruno Feunou We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C58, G, G1, G12 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods
Turning Words into Numbers: Measuring News Media Coverage of Shortages Staff discussion paper 2023-8 Lin Chen, Stéphanie Houle We develop high-frequency, news-based indicators using natural language processing methods to analyze news media texts. Our indicators track both supply (raw, intermediate and final goods) and labour shortages over time. They also provide weekly time-varying topic narratives about various types of shortages. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, C55, C8, C82, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Climate Variability and International Trade Staff working paper 2023-8 Geoffrey R. Dunbar, Walter Steingress, Ben Tomlin This paper quantifies the impact of hurricanes on seaborne international trade to the United States. Matching the timing of hurricane–trade route intersections with monthly U.S. port-level trade data, we isolate the unanticipated effects of a hurricane hitting a trade route using two separate identification schemes: an event study and a local projection. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C22, C5, F, F1, F14, F18, Q, Q5, Q54 Research Theme(s): Structural challenges, Climate change, International trade, finance and competitiveness
Risk Amplification Macro Model (RAMM) Technical report No. 123 Kerem Tuzcuoglu 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. Content Type(s): Staff research, Technical reports JEL Code(s): C, C5, C51, E, E3, E37, E4, E44, F, F4, F44 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Economic models, Monetary policy, Real economy and forecasting
Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model Technical report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp 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. Content Type(s): Staff research, Technical reports JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models
Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models Staff discussion paper 2022-19 James Younker This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C0, C01, C02, C1, C13, C5, C50, C51, C52, C53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting