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The Risk Amplification Macro Model (RAMM) is a new nonlinear two-country dynamic model that captures rare but severe adverse shocks. The RAMM can be used to assess the financial stability implications of both domestic and foreign-originated risk scenarios.

This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.

Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

How can macroprudential policy and monetary policy stabilize segmented credit markets? Is there a trade-off between financial stability and price stability? I use a theoretical model to evaluate the performance of alternative policies and find the optimal mix of macroprudential and monetary policy in response to aggregate shocks.

Existing literature documents that house prices respond to monetary policy surprises with a significant delay, taking years to reach their peak response. We present new evidence of a much faster response.

We study household mortgage choice in a model with three mortgage contracts that differ in their payment structures: fixed-rate fixed-payment, variable-rate variable-payment, and a hybrid variable-rate fixed-payment mortgage where interest rate changes affect principal repayment rather than payment size. We calibrate the model to match mortgage choice patterns in Canada, where all these options are offered with short terms. We demonstrate that restricting contract choice or mandating long terms, as in the U.S. system, can lead to substantial welfare losses by limiting risk management strategies and increasing mortgage pricing ex-ante.

How do banks adjust their loan rate markup in response to macroeconomic shocks?

We conduct surveys to study how consumer spending responds to higher inflation expectations. Most respondents spend the same, sticking to fixed budget plans or not considering inflation for spending decisions. About 20% decrease spending because they feel poorer and cut spending to invest in inflation-proof assets. Very few increase spending.

We study how different types of monetary policy shape the distributional effects of external economic shocks on households’ consumption in a small open economy. Our results present a trade-off between maintaining overall stabilization and controlling consumption inequality.