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This note investigates the relationship between crude oil prices and investment in the energy sector. We employ a set of vector autoregression (VAR) models (unconstrained VAR, vector error-correction and Bayesian VAR) to formalize the relationship between the West Texas Intermediate (WTI) benchmark and fixed-asset cash spending in the oil and gas extraction and support activities sector of the Canadian economy.

The paper studies the determinants of being unbanked in the euro area and the United States as well as the effects of being unbanked on wealth accumulation. Based on household-level data from The Eurosystem Household Finance and Consumption Survey and the U.S. Survey of Consumer Finances, it first documents that there are, respectively, 3.6 per cent and 7.5 per cent of unbanked households in the two economies.

We study the revision properties of the Bank of Canada’s staff output gap estimates since the mid-1980s. Our results suggest that the average staff output gap revision has decreased significantly over the past 15 years, in line with recent evidence for the U.S.

This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables that are representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric models, which allows us to deal with data of different sampling frequencies.

This paper shows point identification in first-price auction models with risk aversion and unobserved auction heterogeneity by exploiting multiple bids from each auction and variation in the number of bidders. The required exclusion restriction is shown to be consistent with a large class of entry models.

This paper considers the problem of estimating a linear model between two heavy-tailed variables if the explanatory variable has an extremely low (or high) value. We propose an estimator for the model coefficient by exploiting the tail dependence between the two variables and prove its asymptotic properties.

We propose an early warning model for predicting the likelihood of a financial stress event for a given future time, and examine whether credit plays an important role in the model as a non-linear propagator of shocks.

Futures markets are a potentially valuable source of information about price expectations. Exploiting this information has proved difficult in practice, because time-varying risk premia often render the futures price a poor measure of the market expectation of the price of the underlying asset.

This paper introduces a new methodology to date systemic financial stress events in a transparent, objective and reproducible way. The financial cycle is captured by a monthly country-specific financial stress index.

We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.