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This paper estimates an open-economy dynamic stochastic general equilibrium model with Bayesian techniques to analyse the macroeconomic effects of the European Central Bank’s (ECB’s) quantitative easing (QE) programme. Using data on government debt stocks and yields across maturities, we identify the parameter governing portfolio adjustment in the private sector.

This paper quantifies global demand, supply and uncertainty shocks and compares two major global recessions: the 2008–09 Great Recession and the COVID-19 pandemic. We use two alternate approaches to decompose economic shocks: text mining techniques on earnings calls transcripts and a structural Bayesian vector autoregression model.

The official consumer price index (CPI) inflation measure, based on a fixed basket set before the COVID 19 pandemic, may not fully reflect what consumers are currently experiencing. We partnered with Statistics Canada to construct a more representative index for the pandemic with weights based on real-time transaction and survey data.

The TSX index rose by 9.5 percent in November 2020, adding large gains to an already sharp V-shaped recovery. The economic outlook improved at that time as well. We ask whether the stock market gains since last autumn are due to improving forecasts of firms’ earnings.

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.

The U.S. recovery from the Great Recession has been slow relative to other postwar-era recoveries in the United States. Encouraged by loose lending standards in the pre-crisis period, U.S. households took on unsustainable amounts of debt, making them vulnerable to adverse shocks. Subsequently, a considerable drop in asset prices forced households to repair their balance sheets. While there has been progress in household deleveraging, the government sector now needs to delever, which will restrain growth over the next few years.

The 2002 Bank of Canada Conference focused on price adjustment, a critically important issue for monetary policy. Given the acceptance throughout the 1990s and 2000s of the existence of price stickiness in goods or labour markets, or both, and of the important role that monetary policy can play in an economy, the time was right for a conference that would focus on current developments in this area of research, particularly within a Canadian context. Conference papers covering both theoretical and empirical studies explored such themes as sources of the persistence of inflation, forward-looking models of inflation, models of inflation in open economies, the macroeconomic effects of technology shocks, and models of the interaction between wages, prices, and real economic outcomes.

Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

When financial system vulnerabilities are elevated, they can give rise to asymmetric risks to the economic outlook. To illustrate this, I consider the economic outlook presented in the Bank of Canada’s October 2017 Monetary Policy Report in the context of two key financial system vulnerabilities: high levels of household indebtedness and housing market imbalances.

We assess the response of Government of Canada bond yields to the Bank of Canada’s initial announcement of the Government Bond Purchase Program (GBPP) as well as to the Bank’s later GBPP purchase operations.