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In Canada and abroad, yields on long-term government bonds have stayed high even as policy interest rates have fallen. This is due to rising term premiums―the extra compensation investors demand for holding these bonds. A key factor driving higher term premiums is global concerns about the ability of markets to absorb substantial amounts of government debt.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

We show how Treasury demand shocks transmit to foreign exchange and bond markets globally. Higher Treasury demand weakens the U.S. dollar and raises foreign bond prices, with effects persisting for two weeks. The transmission varies predictably across countries based on their monetary policy alignment with the United States.

The BoC–BoE database of sovereign debt defaults, published and updated annually by the Bank of Canada and the Bank of England, provides comprehensive estimates of stocks of government obligations in default. The 2025 edition highlights a decline in the US-dollar value of sovereign debt in default and provides more data about defaults on China’s official loans.

Using almost two decades of detailed high-frequency data, we show how Canadian interest rates, the CAD/USD spot exchange rate, and stock market returns react to both US and domestic macro announcements. We find that Canadian macroeconomic announcements invoke greater responses in short-term yields, whereas US macroeconomic announcements play an increasingly important role in the yield movements of longer-term assets.

Changes in domestic interest rates affect the value of the Canadian dollar less than changes in the risk premium do. These variations often occur when a broad shift in risk sentiment occurs in global markets. Ultimately, the value of the currency reflects long-term, slow-moving features of the economies.

Global currency risk factors continue to explain a large share of the variation in the Canadian dollar during the period following the 2008–09 global financial crisis. We show that they are also systematically important for risk premiums, and only in recent months has the role of idiosyncratic country-specific risks grown.

The BoC–BoE database of sovereign debt defaults, published and updated annually by the Bank of Canada and the Bank of England, provides comprehensive estimates of stocks of government obligations in default. The 2024 edition updates the historical data and revisits sovereign defaults on local currency debt.

We evaluate, both empirically and theoretically, the spillover effects that debt-financed fiscal policy interventions of the United States have on other economies. We consider a two-country model with international portfolio rebalancing effects. We show that US fiscal expansions would increase global long-term rates and hinder economic activity in the rest of the world.

This paper studies exchange rate dynamics by incorporating bounded rationality, that is, limited foresight, in a small open-economy model. This behavior of limited foresight helps explain several observations and puzzles in the data of exchange rate movements.