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The year that just passed posed many challenges for all Canadians. The slowdown in the global economy became more pronounced as the year went on, and this affected households, businesses, and governments alike. The tragedy of 11 September compounded the economic difficulties and issues facing us all. Through this period of rapidly changing circumstances, the Bank met its responsibilities by responding quickly and vigorously to events in order to underpin confidence and support the economy.

The official Chinese labour market indicators have been seen as problematic, given their small cyclical movement and their only-partial capture of the labour force. In our paper, we build a monthly Chinese labour market conditions index (LMCI) using text analytics applied to mainland Chinese-language newspapers over the period from 2003 to 2017.

Six months ago, at the time of the last Monetary Policy Report, the global economic and financial environment was volatile and highly uncertain because of the adverse situation in Asia and the fallout from the Russian debt moratorium.

This Report outlines recent developments in the Canadian economy that affect the rate of inflation and provides an account of the measures taken by the Bank of Canada to control inflation.

Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.

Household debt can be an important source of vulnerability to the financial system. This technical report describes the Household Risk Assessment Model (HRAM) that has been developed at the Bank of Canada to stress test household balance sheets at the individual level.

The Canadian economy continued to expand robustly in 2000 while inflation remained low.

The Canadian economy regained strong momentum in 1999 as the U.S. economy remained vigorous, the global economy recovered, and commodity prices moved upwards.

Our study aims to gain insight on financial stability and climate transition risk. We develop a methodological framework that captures the direct effects of a stressful climate transition shock as well as the indirect—or systemic—implications of these direct effects. We apply this framework using data from the Canadian financial system.

Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo.