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We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

We develop a dynamic model to capture key features of decentralized finance lending. We identify a price-liquidity feedback: the market outcome in any given period depends on agents' expectations about lending activities in future periods, with higher future price expectations leading to more lending and higher prices in that period.

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.

We quantify the reaction of U.S. equity, bond futures, and exchange rate returns to oil price shocks driven by oil inventory news.

In this paper, we assess several methods that have been used to measure the Canadian trend unemployment rate (TUR). We also consider improvements and extensions to some existing methods.

We document a strong asymmetry in the evolution of federal funds rate expectations and map this observed asymmetry into measures of monetary policy uncertainty. We show that periods of monetary policy tightening and easing are distinctly related to downside (policy rate is higher than expected) and upside (policy rate is lower than expected) uncertainty.

We decompose total variance into its bad and good components and measure the premia associated with their fluctuations using stock and option data from a large cross-section of firms.

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.

What is the role of central banks in financial stability? How has this role changed in recent years? Bank researchers share their insights on this matter and provide an overview of recent changes the Bank has made to its Emergency Lending Assistance Policy. Researchers also provide a history of four major commodity supercycles, dating back to the early 1900s. Finally, there is discussion about structural reforms in emerging-market economies, such as China, and how these reforms influence potential growth.

An important channel in the transmission of monetary policy is the relationship between the short-term policy rate and long-term interest rates. Using a new term-structure model, the authors show that the variation in long-term interest rates over time consists of two components: one representing investor expectations of future policy rates, and another reflecting a term-structure risk premium that compensates investors for holding a risky asset. The time variation in the term-structure risk premium is countercyclical and largely determined by global macroeconomic conditions. As a result, long-term rates are pushed up during recessions and down during times of expansion. This is an important phenomenon that central banks need to take into account when using short-term rates as a policy tool.