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A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

Similar to those of other forecasters, the Bank of Canada’s forecasts of global GDP growth have shown persistent negative errors over the past five years. This is in contrast to the pre-crisis period, when errors were consistently positive as global GDP surprised to the upside. All major regions have contributed to the forecast errors observed since 2011, although the United States has been the most persistent source of notable errors.

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.

In the past few years, many have postulated that the possible disinflationary effects of digitalization could explain the subdued inflation in advanced economies. In this note, we review the evidence found in the literature. We look at three main channels.

Central banks continuously strive to improve how they communicate to financial markets and the public in order to increase transparency. For this reason, many central banks have begun to include guidance on the policy rate in the form of forward-looking statements in their communications. This article examines the debate over the usefulness of providing such statements from both theoretical and empirical standpoints. The evidence presented here suggests that the use of forward-looking statements in Bank of Canada communications has made the Bank more predictable, but not necessarily more transparent.

Many emerging-market economies (EMEs) have significantly improved their macroeconomic fundamentals and undergone structural reforms since the Asian crisis. These developments have enhanced the composition of capital flows to EMEs through an improved debt structure, a larger share of capital flows as foreign direct investment, and greater access to international debt markets for corporations in EMEs. Structural changes in the global financial landscape have also increased capital flows, bringing economic and financial benefits to EMEs. During the recent financial crisis, however, the opening up of capital accounts and increased financial and trade linkages left many countries vulnerable to external disruptions. Countries with sound fundamentals have weathered the crisis relatively well. Policy-makers in EMEs need to implement policies that support capital flows and ensure that controls imposed to deal with detrimental outflows during periods of stress or rapid inflows are only temporary.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

In a speech to the Vancouver Board of Trade, Governor Mark Carney discusses the fundamentals of the Canadian residential real estate market, the international context, and the implications for monetary policy.

Using turnover ratios, Anderson and Lavoie describe the recent evolution of liquidity in various secondary government bond markets, focusing specifically on the market for Government of Canada securities. They attribute much of the recent variation in liquidity to such cyclical factors as changes in the interest rate environment and investors' appetite for risk, as well as developments in equity markets in the late 1990s. They also examine longer-term structural and policy-related trends, including the rate of adoption of financial and technological innovations and the level of government borrowing and debt-management initiatives.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.