E37 - Forecasting and Simulation: Models and Applications

• 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

• Turning Words into Numbers: Measuring News Media Coverage of Shortages

  Staff Discussion Paper 2023-8 Lin Chen, Stephanie Houle

  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.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Coronavirus disease (COVID-19), Econometric and statistical methods, Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C5, C55, C8, C82, E, E3, E37

• Risk Amplification Macro Model (RAMM)

  Technical Report No. 123 Kerem Tuzcuoglu

  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.

  Content Type(s): Staff research, Technical reports Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Monetary policy transmission JEL Code(s): C, C5, C51, E, E3, E37, E4, E44, F, F4, F44

• Understanding Post-COVID Inflation Dynamics

  Staff Working Paper 2022-50 Martin Harding, Jesper Lindé, Mathias Trabandt

  We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. Our model can generate more sizable inflation surges due to cost-push and demand shocks than a standard linearized model when inflation is high.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Central bank research, Coronavirus disease (COVID-19), Economic models, Inflation and prices, Inflation: costs and benefits, Monetary policy, Monetary policy implementation JEL Code(s): E, E3, E30, E31, E32, E37, E4, E44, E5, E52

• Harnessing the benefit of state-contingent forward guidance

  Staff Analytical Note 2022-13 Vivian Chu, Yang Zhang

  A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Central bank research, Economic models, Monetary policy framework, Monetary policy transmission JEL Code(s): E, E2, E27, E3, E37, E4, E5, E52, E58

• How well can large banks in Canada withstand a severe economic downturn?

  Staff Analytical Note 2022-6 Andisheh (Andy) Danaee, Harsimran Grewal, Brad Howell, Guillaume Ouellet Leblanc, Xuezhi Liu, Mayur Patel, Xiangjin Shen

  We examine the potential impacts of a severe economic shock on the resilience of major banks in Canada. We find these banks would suffer significant financial losses but nevertheless remain resilient. This underscores the role well-capitalized banks and sound underwriting practices play in supporting economic activity in a downturn.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Financial institutions, Financial stability JEL Code(s): E, E2, E27, E3, E37, E4, E44, G, G1, G2, G21, G23

• 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

• What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data

  Staff Working Paper 2021-52 Alberto Cavallo, Oleksiy Kryvtsov

  Did supply disruptions and cost pressures play a role in rising inflation in 2020 during the COVID-19 pandemic? Using data collected from websites of large retailers in multiple sectors and countries, we show that shortages may indicate transitory inflationary pressures.

  Content Type(s): Staff research, Staff working papers Topic(s): Coronavirus disease (COVID-19), Inflation and prices JEL Code(s): D, D2, D22, E, E3, E31, E37

• Potential output and the neutral rate in Canada: 2021 update

  Staff Analytical Note 2021-6 Dany Brouillette, Guyllaume Faucher, Martin Kuncl, Austin McWhirter, Youngmin Park

  We expect potential output growth to be higher than in the October 2020 reassessment. By 2024, growth will be slightly above its average growth from 2010 to 2019. We assess that the Canadian nominal neutral rate continues to lie in the range of 1.75 to 2.75 percent.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Economic models, Interest rates, Labour markets, Monetary policy, Potential output, Productivity JEL Code(s): E, E2, E23, E24, E3, E37, E4, E43, E5, E52

• A Generalized Endogenous Grid Method for Default Risk Models

  Staff Working Paper 2021-11 Youngsoo Jang, Soyoung Lee

  Models with default options are hard to solve. We propose an extension of the endogenous grid method that solves default risk models more efficiently and accurately.

  Content Type(s): Staff research, Staff working papers Topic(s): Credit and credit aggregates, Credit risk management JEL Code(s): C, C6, C63, E, E3, E37