Identifying Nascent High-Growth Firms Using Machine Learning Staff working paper 2023-53 Stéphanie 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 JEL Code(s): C, C5, C55, C8, C81, L, L2, L25 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Structural challenges, Digitalization and productivity
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
Three things we learned about the Lynx payment system Staff analytical note 2023-14 Nikil Chande, Zhentong Lu, Hiru Rodrigo, Phoebe Tian Canada transitioned to a new wholesale payment system, Lynx, in August 2021. Lynx is based on a real-time settlement model that eliminates credit risk in the system. This model can require more liquidity; however, Lynx’s design allows Canada’s wholesale payments to settle efficiently. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C1, C10, E, E4, E42, G, G2, G28 Research Theme(s): Money and payments, Payment and financial market infrastructures
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
Digitalization: Implications for Monetary Policy Staff discussion paper 2023-18 Vivian Chu, Tatjana Dahlhaus, Christopher Hajzler, Pierre-Yves Yanni We explore the implications of digitalization for monetary policy, both in terms of how monetary policy affects the economy and in terms of data analysis and communication with the public. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C4, C8, E, E3, E31, E32, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Monetary policy framework and transmission, Structural challenges, Digitalization and productivity
Unmet Payment Needs and a Central Bank Digital Currency Staff discussion paper 2023-15 Christopher Henry, Walter Engert, Alexandra Sutton-Lalani, Sebastian Hernandez, Darcey McVanel, Kim Huynh We discuss the payment habits of Canadians both in the current payment environment and in a hypothetical cashless environment. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54 Research Theme(s): Money and payments, Cash and bank notes, Digital assets and fintech, Retail payments
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
Is Money Essential? An Experimental Approach Staff working paper 2023-39 Janet Hua Jiang, Peter Norman, Daniela Puzzello, Bruno Sultanum, Randall Wright Monetary theory says that money is essential if it helps to achieve better incentive-feasible outcomes. We test this in the laboratory. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C9, C92, E, E4, E5 Research Theme(s): Models and tools, Economic models, Monetary policy, Monetary policy framework and transmission