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We break down the exchange rate based on an explicit link between fixed income and currency markets. We isolate a foreign exchange risk premium and show it is the main driver of the exchange rate between the Canadian and US dollars, especially on monetary policy and macroeconomic news announcement days.

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.

How do households respond when they receive unanticipated income, such as an inheritance or government stimulus cheque? This paper studies these windfall income shocks through a model of household behaviour that generates a realistic consumption response for households along the entire distribution of wealth.

The paper explores the link between financial distress and the commodity price hedging behaviour of Canadian oil firms.

News media present competing interpretations of what breaking news implies for the macroeconomy. Recent examples include news reporting on high inflation and yield curve inversions. Do these narratives shape macroeconomic sentiment? In this paper, we highlight the importance of narratives using evidence linking traditional media and social media.

Models for macroeconomic forecasts do not usually take into account the risk of a crisis—that is, a sudden large decline in gross domestic product (GDP). However, policy-makers worry about such GDP tail risk because of its large social and economic costs.

Two approaches have been taken in the literature to evaluate the relative importance of news shocks as a source of business cycle volatility. The first is an empirical approach that performs a structural vector autoregression to assess the relative importance of news shocks, while the second is a structural-model-based approach.

This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure.

I use a structural vector autoregression (SVAR) with sign restrictions to provide conditional evidence on the behavior of the US external finance premium (EFP). The results indicate that the excess bond premium, a proxy for the EFP, reacts countercyclically to supply and monetary policy shocks and procyclically to demand shocks.

We present the daily time series of the outstanding amounts of all Government of Canada marketable debt securities from July 2001 to June 2017.