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The Canadian overnight repo market persistently shows signs of latent funding pressure around month-end periods. Both the overnight repo rate and Bank of Canada liquidity provision tend to rise in these windows. This paper proposes three non-mutually exclusive hypotheses to explain this phenomenon.

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.

Carbon dioxide emissions have been commonly modelled as rising and falling with total output. Yet many factors, such as energy-efficiency improvements and shifts to cleaner energy, can break this relationship. We evaluate these factors using US data and find that changes in energy efficiency of consumption goods explain a significant proportion of emissions fluctuations. This finding also implies that models that omit energy efficiency likely overestimate the trade-off between environmental protection and economic performance.

Exporters frequently change their market destinations. This paper introduces a new approach to identifying the drivers of these decisions over time. Analysis of customs data from China and the UK shows most changes are driven by demand rather than supply-related shocks.

We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing.

In the last half-year, the economic expansion in Canada has become well established, supported by low inflation, highly stimulative monetary conditions, and a strong U.S. economy.

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.

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.

The global economy has continued to grow at a robust pace since the July Monetary Policy Report Update.

In the year just ended, the global economy faced a number of exceptional challenges, reflecting a wide range of economic, financial, and geopolitical risks and uncertainties. These included the fallout from the September 2001 terrorist attacks, corporate accounting scandals, stock market volatility, and developments in the Middle East. Despite this global backdrop, the Canadian economy outperformed virtually all other industrial economies, growing by about 3 1/4 per cent and creating 560,000 jobs, while inflation expectations remained well anchored to the Bank of Canada’s 2 per cent inflation-control target.