Recent sharp declines in commodity prices and the simultaneous depreciation of the Canadian dollar (CAD) relative to the U.S. dollar (USD) have rekindled an interest in the relationship between commodity prices and the CAD-USD exchange rate.
Staff analytical notes
Staff working papers
We propose a new strength measure of the global financial cycle by estimating a regime-switching factor model on cross-border equity flows for 61 countries. We then assess how the strength of the global financial cycle affects monetary policy independence, which is defined as the response of central banks' policy interest rates to exogenous changes in inflation.
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.
We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes.
This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables that are representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric models, which allows us to deal with data of different sampling frequencies.
This paper proposes a novel methodology for identifying episodes of strong capital flows based on a regime-switching model. In comparison with the existing literature, a key advantage of our methodology is to estimate capital flow regimes without the need for context- and sample-specific assumptions.
This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging – so as to explicitly reflect the objective of forecasting a discrete outcome.
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets.
This paper deals with the estimation of the risk-return trade-off. We use a MIDAS model for the conditional variance and allow for possible switches in the risk-return relation through a Markov-switching specification.
Bank of Canada Review articles
August 15, 2013 The Bank of Canada uses several short-term forecasting models for the monitoring of key foreign economies - the United States, the euro area, Japan and China. The design of the forecasting models used for each region is influenced by the level of detail required, as well as the timeliness and volatility of data. Forecasts from different models are typically combined to mitigate model uncertainty, and judgment is applied to the model forecasts to incorporate information that is not directly reflected in the most recent indicators.