Climate-Related Flood Risk to Residential Lending Portfolios in Canada Staff Discussion Paper 2023-33 Craig Johnston, Geneviève Vallée, Hossein Hosseini, Brett Lindsay, Miguel Molico, Marie-Christine Tremblay, Aidan Witts We assess the potential financial risks of current and projected flooding caused by extreme weather events in Canada. We focus on the residential real estate secured lending (RESL) portfolios of Canadian financial institutions (FIs) because RESL portfolios are an important component of FIs’ balance sheets and because the assets used to secure such loans are immobile and susceptible to climate-related extreme weather events. Content Type(s): Staff research, Staff discussion papers Topic(s): Central bank research, Climate change, Credit risk management, Econometric and statistical methods, Financial institutions, Financial stability JEL Code(s): C, C8, C81, G, G2, G21, Q, Q5, Q54
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
Testing Collusion and Cooperation in Binary Choice Games Staff Working Paper 2023-58 Erhao Xie This paper studies the testable implication of players’ collusive or cooperative behaviour in a binary choice game with complete information. I illustrate the implementation of this test by revisiting the entry game between Walmart and Kmart. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Market structure and pricing JEL Code(s): C, C5, C57, L, L1, L13
Machine learning for economics research: when, what and how Staff Analytical Note 2023-16 Ajit Desai This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used. Content Type(s): Staff research, Staff analytical notes Topic(s): Central bank research, Econometric and statistical methods, Economic models JEL Code(s): A, A1, A10, B, B2, B23, C, C4, C45, C5, C55
Identifying Nascent High-Growth Firms Using Machine Learning Staff Working Paper 2023-53 Stephanie Houle, Ryan Macdonald Firms that grow rapidly have the potential to usher in new innovations, products or processes (Kogan et al. 2017), become superstar firms (Haltiwanger et al. 2013) and impact the aggregate labour share (Autor et al. 2020; De Loecker et al. 2020). We explore the use of supervised machine learning techniques to identify a population of nascent high-growth firms using Canadian administrative firm-level data. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Firm dynamics JEL Code(s): C, C5, C55, C8, C81, L, L2, L25
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 Topic(s): Econometric and statistical methods, Financial markets, Housing JEL Code(s): A, C, C4, C45, C5, C53, D, D2, R, R2, R3
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
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 Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37
Competition for Exclusivity and Customer Lock-in: Evidence from Copyright Enforcement in China Staff Working Paper 2023-43 Youming Liu This paper studies the music streaming industry and argues that having exclusive rights granted by copyright law drives firms to offer exclusive content to lock in customers. I employ theoretical and descriptive empirical analysis, along with a dynamic structural model, to support the argument and explore policies for improving competition. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Firm dynamics, Market structure and pricing JEL Code(s): L, L1, L13, L4, L42, L5, L51
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 Topic(s): Asset pricing, Econometric and statistical methods JEL Code(s): C, C5, C58, G, G1, G12