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We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers.

How much of a CBDC would Canadian households want to hold, and what design features of a CBDC would they care about?

Using an exclusive data set of payment times for retail transactions made in Canada, I show that cash is the most time-efficient method of payment (MOP) when compared with payments by debit and credit cards. I model payment efficiency using Cox proportional hazard models, accounting for consumer choice of MOP.

The Bank of Canada’s current suite of models faces challenges in addressing network effects that integrate household and firm-level heterogeneity and their behaviours. We develop CANVAS, a Canadian behavioural agent-based model to contribute to the Bank’s next-generation modelling effort. CANVAS improves forecasting performance and expands capacity for model-based scenario analysis.

Causes and consequences of declining inflation persistence in Canada; the evolution of capital flows to emerging-market economies (EMEs) and the need for EMEs to implement policies that support capital flows; making bank notes accessible for Canadians living with blindness or low vision, sharing assessments of the suite of accessibility features on the current series of bank notes and plans for the next series.

We study how the distribution of information supply by the news media affects the macroeconomy. We find that media coverage focuses particularly on the largest firms, and that firms’ equity financing and investment increase after media coverage. But these equity and investment responses are largest among small, rarely covered firms. Our quantitative studies highlight that the aggregate effects of media coverage depend crucially on how that coverage is allocated.

I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.

Carbon dioxide emissions have been commonly modelled as rising and falling with total output. Yet many factors, such as energy-efficiency improvements and shifts to cleaner energy, can break this relationship. We evaluate these factors using US data and find that changes in energy efficiency of consumption goods explain a significant proportion of emissions fluctuations. This finding also implies that models that omit energy efficiency likely overestimate the trade-off between environmental protection and economic performance.

During downturns, workers get stuck in low-productivity jobs and wages remain stagnant. I build an heterogenous agent incomplete market model with a full job ladder that accounts for these facts. An adverse financial shock calibrated to the US Great Recession replicates the period’s slow recovery and missing disinflation.

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.