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We present a tool for creating density nowcasts for Canadian real GDP growth. We demonstrate that the combined densities are a reliable and accurate tool for assessing the state of the economy and risks to the outlook.

Senior Deputy Governor Tiff Macklem discusses how price and financial stability help promote growth and mitigate economic cycles and inequality.

What is the role of central banks in financial stability? How has this role changed in recent years? Bank researchers share their insights on this matter and provide an overview of recent changes the Bank has made to its Emergency Lending Assistance Policy. Researchers also provide a history of four major commodity supercycles, dating back to the early 1900s. Finally, there is discussion about structural reforms in emerging-market economies, such as China, and how these reforms influence potential growth.

I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.

This paper develops a general equilibrium model to assess central bank digital currency (CBDC) design in a monetary system where traditional banks and “crypto banks” (i.e., banks that issue stablecoins) coexist. We compare tokenized and non-tokenized CBDC, showing that their desirability depends on the reliability of private money provision, the availability of collateral assets and the features of the crypto sector.

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.

We study how participants in the Lynx payment system use the net send limit (NSL) tool to control their intraday payment outflow levels. Our results show that participants typically adopt a “set it and forget it” approach to scheduling NSLs and sometimes have distinct intraday NSL adjustment behaviours.

I examine the impact of non-regulated lenders in the mortgage market using a dynamic stochastic general equilibrium (DSGE) model. My model features two types of financial intermediaries that differ in three ways: (i) only regulated intermediaries face a capital requirement, (ii) non-regulated intermediaries finance themselves by selling securities and cannot accept deposits, and (iii) non-regulated intermediaries face a more elastic demand.

We use detailed consumer credit data to investigate the impact of the 2016 Fort McMurray wildfire, the costliest wildfire disaster in Canadian history, on consumers’ financial stress. We focus on the arrears of insured mortgages because of their important implications for financial institutions and insurers’ business risk and relevant management practices.

I study a model of competing data intermediaries (e.g., online platforms and data brokers) that collect personal data from consumers and sell it to downstream firms.