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66 Results

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. We find this approach yields a significant increase in forecasting precision over a linear benchmark model. This model can help policy-makers before official data are released.

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.

Nowcasting Canadian Economic Activity in an Uncertain Environment

Staff Discussion Paper 2018-9 Tony Chernis, Rodrigo Sekkel
This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.
Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53, E, E3, E37, E5, E52

State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models

Staff Working Paper 2018-14 Luis Uzeda
Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood.

Dismiss the Gap? A Real-Time Assessment of the Usefulness of Canadian Output Gaps in Forecasting Inflation

We use a new real-time database for Canada to study various output gap measures. This includes recently developed measures based on models incorporating many variables as inputs (and therefore requiring real-time data for many variables).

On the Tail Risk Premium in the Oil Market

Staff Working Paper 2017-46 Reinhard Ellwanger
This paper shows that changes in market participants’ fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and significantly forecast crude oil futures and spot returns.

A Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth

Staff Discussion Paper 2017-8 Tony Chernis, Gabriella Velasco, Calista Cheung
This paper estimates a three‐frequency dynamic factor model for nowcasting Canadian provincial gross domestic product (GDP). Canadian provincial GDP is released by Statistics Canada on an annual basis only, with a significant lag (11 months).