C55 - Large Data Sets: Modeling and Analysis

• 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

• 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 Topic(s): Economic models, Inflation and prices, Labour markets, Monetary policy and uncertainty JEL Code(s): C, C5, C50, C51, C52, C53, C54, C55

• Turning Words into Numbers: Measuring News Media Coverage of Shortages

  Staff Discussion Paper 2023-8 Lin Chen, Stephanie 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 Topic(s): Coronavirus disease (COVID-19), Econometric and statistical methods, Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C5, C55, C8, C82, E, E3, E37