Staff working papers

This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks.

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.

We model non-bank entry into fixed-income markets and state-dependent liquidity. Non-bank financial institutions improve liquidity more during normal times than in stress. Banks may become less reliable to marginal clients, exacerbating the difference in liquidity between normal and stressed times. Central bank lending during stress may limit this harmful division.

In 2023, the share of Canadian banks’ foreign assets and liabilities amounted to around 50%. While Canadian banks engage domestically mostly with households and non-financial corporations, their most common counterparties abroad are non-bank financial institutions.

We simulate introducing a central bank digital currency (CBDC) and consider consumer adoption, merchant acceptance and usage at the point of sale. Modest adoption frictions significantly inhibit CBDC market penetration along all three dimensions. Incumbent responses to restore pre-CBDC market shares are moderate to small and further reduce the impact of a CBDC.

We investigate the macroeconomic impacts of mothballed businesses—those that closed temporarily—on sectoral equilibrium prices after a negative demand shock. Our results suggest that pandemic fiscal support for temporary closures may have eased inflationary pressures.

We develop and estimate a search model in which identical consumers trade with price-setting firms that differ in productivity. We use the estimated model to characterize the qualitative and quantitative differences in prices and markups across firms. We explore how individual firms respond to changes in cost and demand and how they pass these through to their prices and markup.

We find the top 10% of the income distribution accounts for three-quarters of the gap in GDP per adult between Canada and the United States. The large gaps in income for high-income earners help distinguish between alternative explanations of this persistent gap in GDP per adult.

Measuring cryptoasset knowledge alongside financial knowledge enhances our understanding of individuals' decisions to purchase cryptoassets. This paper uses microdata from the Bank of Canada’s Bitcoin Omnibus Survey to examine gender differences and the interrelationship between crypto and financial knowledge through an empirical joint analysis.

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.