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Understanding the size of sectoral links is crucial to predicting the impact of a crisis on the whole economy. We show that statistical learning techniques substantially outperform traditional estimation techniques when measuring large networks of these links.

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.

Many reports and analyses interpret the release of new economic data based on the headline surprise—for instance, total inflation, real GDP growth and the unemployment rate. However, we find that headline news alone cannot adequately explain the responses of market prices to new information. Rather, market prices react more strongly, on average, to non-headline news such as the composition of GDP growth, quality of jobs created and revisions to past data. Thus, tracking the impact of non-headline information released on the news day is crucial in analyzing how markets interpret and react to new economic data.

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.

Conditions in the international financial system have improved considerably since June in response to the forceful actions taken by policy-makers around the world.

FSR Highlights - December 2009

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.

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.

ToTEM III is the most recent generation of the Bank of Canada’s main dynamic stochastic general equilibrium model for projection and policy analysis. The model helps Bank staff tell clear and coherent stories about the Canadian economy’s current state and future evolution.

This paper examines the behaviour of the Canadian dollar from 1997 to 1999 to see if there is any evidence of excess volatility or significant overshooting. A small econometric model of the exchange rate, based on market fundamentals, is presented and used to make tentative judgments about the extent to which the currency might have been systematically over- or undervalued.

Some evidence points to the procyclicality of leverage among financial institutions leading to aggregate volatility. This procyclicality occurs when financial institutions finance their assets with non-equity funding (i.e., debt financed asset expansions). Wholesale funding is an important source of market-based funding that allows some institutions to quickly adjust their leverage.