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The impact of oil price shocks on the U.S. economy is a topic of considerable debate. In this paper, we examine the response of U.S. consumers to the 2014–2015 negative oil price shock using representative survey data from the Consumer Expenditure Survey.

This report provides a detailed technical description of the updated MacroFinancial Risk Assessment Framework (MFRAF), which replaces the version described in Gauthier, Souissi and Liu (2014) as the Bank of Canada’s stress-testing model for banks with a focus on domestic systemically important banks (D-SIBs).

We investigate the risks and opportunities to the mandates of central banks arising from fintech developments.

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.

Coletti and Lalonde compare inflation targeting and price-level targeting in the context of a small open economy subject to sizable terms-of-trade shocks. The authors summarize recent research that compares the ability of price-level targeting and inflation targeting to stabilize the macroeconomy when confronted with shocks similar to those experienced by Canada in recent years. Their preliminary results suggest that price-level targeting may represent a feasible alternative to traditional inflation targeting. Their article also provides insight into the direction of current research in this area at the Bank.

We simulate the impact of a central bank digital currency (CBDC) on consumer adoption, merchant acceptance and use of different payment methods. Modest frictions that deter consumer adoption of a CBDC inhibit its market penetration. Minor pricing responses by financial institutions and payment service providers further reduce the impact of a CBDC.

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms.

We analyze micro-level data from the Canadian Survey of Consumer Expectations through the lens of a heterogeneous-expectations model to study how inflation expectations form over the business cycle. We provide new insights into how households form expectations, documenting that forecasting behaviours, attention and noise in beliefs vary across socio-demographic groups and correlate with views about monetary policy.

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.

We present a two-stage model of mobile phone and mobile payment usage that controls for selectivity. This reveals unobserved factors that work against having a mobile phone and toward mobile paying. Therefore, people who are unable to acquire or choose not to own a mobile device might have unmet payment needs.