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Macroeconomic Predictions Using Payments Data and Machine Learning

Staff Working Paper 2022-10 James Chapman, Ajit Desai
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

Staff Analytical Note 2021-9 Ugochi Emenogu, Cars Hommes, Mikael Khan
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.

Networking the Yield Curve: Implications for Monetary Policy

We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff Working Paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

The New Benchmark for Forecasts of the Real Price of Crude Oil

How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.

The Trend Unemployment Rate in Canada: Searching for the Unobservable

In this paper, we assess several methods that have been used to measure the Canadian trend unemployment rate (TUR). We also consider improvements and extensions to some existing methods.

GDP by Industry in Real Time: Are Revisions Well Behaved?

Staff Analytical Note 2018-40 Patrick Rizzetto
The monthly data for real gross domestic product (GDP) by industry are used extensively in real time both to ground the Bank of Canada’s monitoring of economic activity and in the Bank’s nowcasting tools, making these data one of the most important high-frequency time series for Canadian nowcasting.
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