This paper provides an overview of cryptoasset exchanges. We contrast their design with exchanges in traditional financial markets and discuss emerging regulatory trends and innovations aimed at solving the problems cryptoasset exchanges face.
We present results from the 2022 Methods-of-Payment Survey, including updated payment shares based on a three-day shopping diary. We also assess various factors associated with long-term trends in cash use.
This paper explores the impact of extreme weather exposures on the financial outcomes of low-income households. Our findings highlight the heightened financial vulnerability of low-income households to environmental shocks and underscore the need for targeted policies.
We show how Canadian mortgage debt dynamics can be modelled in a semi-structural macroeconomic model, such as the Bank of Canada’s LENS. The model we propose accounts for Canada’s unique mortgage debt structure.
This newsletter features the latest research publications by Bank of Canada economists including external publications and working papers published on the Bank of Canada’s website.
Regulators need to provide effective procyclicality guidance, and central counterparties must design and calibrate their margin systems and procyclicality frameworks appropriately. To serve these needs, we provide a novel conceptual tool kit. Further, we highlight that the focus should be on the key margin system parameters in determining procyclicality.
We examine the value of direct communication to households about inflation and the uncertainty around inflation statistics. All types of information about inflation are effective at immediately managing inflation expectations, with information about outlooks being more effective and relevant than that about recent inflation and Bank targets.
We find that minority households see greater declines in housing returns and entries into homeownership than White households after a tightening of monetary policy. Our findings emphasize the unintended consequences of monetary policy on racial inequality in the housing market.
This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.