C5 - Econometric Modeling
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Deriving Longer-Term Inflation Expectations and Inflation Risk Premium Measures for Canada
We present two models for long-term inflation expectations and inflation risk premiums for Canada. -
Non-Parametric Identification and Testing of Quantal Response Equilibrium
We show that the utility function and the error distribution are non-parametrically over-identified under Quantal Response Equilibrium (QRE). This leads to a simple test for QRE. We illustrate our method in a Monte Carlo exercise and a laboratory experiment. -
Decomposing Systemic Risk: The Roles of Contagion and Common Exposures
We examine systemic risks within the Canadian banking sector, decomposing them into three contribution channels: contagion, common exposures, and idiosyncratic risk. Through a structural model, we dissect how interbank relationships and market conditions contribute to systemic risk, providing new insights for financial stability. -
Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems
Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems. -
Forecasting Recessions in Canada: An Autoregressive Probit Model Approach
We forecast recessions in Canada using an autoregressive (AR) probit model. The results highlight the short-term predictive power of the US economic activity and suggest that financial indicators are reliable predictors of Canadian recessions. In addition, the suggested model meaningfully improves the ability to forecast Canadian recessions, relative to a variety of probit models proposed in the Canadian literature. -
Predictive Density Combination Using a Tree-Based Synthesis Function
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. -
Finding the balance—measuring risks to inflation and to GDP growth
Using our new quantitative tool, we show how the risks to the inflation and growth outlooks have evolved over the course of 2023. -
Making It Real: Bringing Research Models into Central Bank Projections
Macroeconomic projections and risk analyses play an important role in guiding monetary policy decisions. Models are integral to this process. This paper discusses how the Bank of Canada brings research models and lessons learned from those models into the central bank projection environment. -
Testing Collusion and Cooperation in Binary Choice Games
This paper studies the testable implication of players’ collusive or cooperative behaviour in a binary choice game with complete information. I illustrate the implementation of this test by revisiting the entry game between Walmart and Kmart.