C5 - Econometric Modeling
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A Blueprint for the Fourth Generation of Bank of Canada Projection and Policy Analysis Models
The fourth generation of Bank of Canada projection and policy analysis models seeks to improve our understanding of inflation dynamics, the supply side of the economy and the underlying risks faced by policy-makers coming from uncertainty about how the economy functions. -
Predicting Changes in Canadian Housing Markets with Machine Learning
We apply two machine learning algorithms to forecast monthly growth of house prices and existing homes sales in Canada. Although the algorithms can sometimes outperform a linear model, the improvement in forecast accuracy is not always statistically significant. -
Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency
This paper quantifies tail risks in the outlooks for Canadian inflation and real GDP growth by estimating their conditional distributions at a daily frequency. We show that the tail risk probabilities derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022. -
Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis
I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best. -
Generalized Autoregressive Gamma Processes
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does. -
Turning Words into Numbers: Measuring News Media Coverage of Shortages
We develop high-frequency, news-based indicators using natural language processing methods to analyze news media texts. Our indicators track both supply (raw, intermediate and final goods) and labour shortages over time. They also provide weekly time-varying topic narratives about various types of shortages. -
Climate Variability and International Trade
This paper quantifies the impact of hurricanes on seaborne international trade to the United States. Matching the timing of hurricane–trade route intersections with monthly U.S. port-level trade data, we isolate the unanticipated effects of a hurricane hitting a trade route using two separate identification schemes: an event study and a local projection. -
Risk Amplification Macro Model (RAMM)
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. -
Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model
We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.