C53 - Forecasting and Prediction Methods; Simulation Methods

• Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis

  Staff Working Paper 2023-45 Tony Chernis

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37

• Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model

  Technical Report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp

  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.

  Content Type(s): Staff research, Technical reports Topic(s): Economic models, Financial institutions, Financial stability, Financial system regulation and policies JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28

• Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models

  Staff Discussion Paper 2022-19 James Younker

  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.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C02, C1, C13, C5, C50, C51, C52, C53

• Nowcasting Canadian GDP with Density Combinations

  Staff Discussion Paper 2022-12 Tony Chernis, Taylor Webley

  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.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C52, C53, E, E3, E7

• 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.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52

• Assessing Climate-Related Financial Risk: Guide to Implementation of Methods

  Technical Report No. 120 Hossein Hosseini Jebeli, Craig Johnston, Craig Logan, Miguel Molico, Xiangjin Shen, Marie-Christine Tremblay

  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.

  Content Type(s): Staff research, Technical reports Topic(s): Climate change, Credit and credit aggregates, Econometric and statistical methods, Financial stability JEL Code(s): C, C5, C53, C8, C83, G, G1, G3, G32

• Shaping the future: Policy shocks and the GDP growth distribution

  Staff Working Paper 2021-24 Francois-Michel Boire, Thibaut Duprey, Alexander Ueberfeldt

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Central bank research, Econometric and statistical methods, Financial stability, Fiscal policy, Monetary policy JEL Code(s): C, C3, C32, C5, C53, E, E5, E52, E6, E62

• 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.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Econometric and statistical methods, Financial stability, Housing JEL Code(s): C, C5, C53, R, R2, R21, R3, R31

• Networking the Yield Curve: Implications for Monetary Policy

  Staff Working Paper 2021-4 Tatjana Dahlhaus, Julia Schaumburg, Tatevik Sekhposyan

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Interest rates, Monetary policy implementation JEL Code(s): C, C1, C18, C2, C21, C5, C53, E, E4, E43, E44, E5, E52

• 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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52