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We develop a heterogeneous-agent New Keynesian model featuring a frictional labor market with on-the-job search to quantitatively study the positive and normative implications of employer-to-employer transitions for inflation.

Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading.

As the title of the conference suggests, we have seen many boom-and-bust cycles in the commodity sector. This raises one obvious and central question: How can we avoid them in the future?

During the COVID-19 pandemic, Canadian financial institutions offered debt-relief programs to help borrowers cope with job losses and economic insecurity. We consider the low take-up rates for these programs and suggest that to be effective, such programs must be visible and easy to use.

The uncertainty around future changes to the Federal Reserve target rate varies over time. In our results, the main driver of uncertainty is a “path” factor signaling information about future policy actions, which is filtered from federal funds futures data.

Consumers, businesses and banks make millions of payments each day using a variety of instruments, such as debit cards, cheques and wires. Canada is currently developing three new systems to process these transactions: Lynx, Settlement Optimization Engine (SOE) and Real-Time Rail (RTR).

This paper explores the reliability of using prices of credit default swap contracts (CDS) as indicators of default probabilities during the 2007/2008 financial crisis.

Because commodity prices help determine Canada’s terms of trade, employment, income and, ultimately, inflation, it is important to understand what causes them to fluctuate. Since the early 1900s, there have been four commodity price supercycles—which we define as extended periods of boom and bust that can take decades to complete. Now in its downswing phase, the current supercycle started after growth in China and other emerging-market economies in the mid-1990s resulted in an unexpected demand shock. The extent of this downswing depends on numerous factors that are presently uncertain.

We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way.

G-20 representatives, academics, market participants, and members of international financial institutions were brought together in Ottawa to explore the connection between robust financial markets and economic growth and development, share experiences, and to develop policy recommendations, where possible. Participants identified several areas they deemed critical for fostering strong domestic financial markets and reducing external vulnerability: sound macroeconomics policies, strengthened financial infrastructures and banking systems, and exchange rate flexibility for countries with widely open capital accounts. Papers presented in the six sessions and keynote address highlighted a number of issues, including currency mismatches, the sequence of financial liberalization and supervisory reforms, the development of local financial markets, infrastructure building and governance, and appropriate incentives.