C53 - Forecasting and Prediction Methods; Simulation Methods
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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. -
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. -
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. -
Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models. -
Nowcasting Canadian GDP with Density Combinations
We present a tool for creating density nowcasts for Canadian real GDP growth. We demonstrate that the combined densities are a reliable and accurate tool for assessing the state of the economy and risks to the outlook. -
Macroeconomic Predictions Using Payments Data and Machine Learning
We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges. -
Assessing Climate-Related Financial Risk: Guide to Implementation of Methods
A pilot project on climate transition scenarios by the Bank of Canada and the Office of the Superintendent of Financial Institutions assessed climate-related credit and market risks. This report describes the project’s methodologies and provides guidance on implementing them. -
Shaping the future: Policy shocks and the GDP growth distribution
Can central bank and government policies impact the risks around the outlook for GDP growth? We find that fiscal stimulus makes strong GDP growth more likely—even more so when monetary policy is constrained—rather than weak GDP growth less likely. Thus, fiscal stimulus should accelerate the recovery phase of the COVID-19 pandemic. -
Detecting exuberance in house prices across Canadian cities
We introduce a model to detect periods of extrapolative house price expectations across Canadian cities. The House Price Exuberance Indicator can be updated on a quarterly basis to support the Bank of Canada’s broader assessment of housing market imbalances.