E37 - Forecasting and Simulation: Models and Applications
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Turning Words into Numbers: Measuring News Media Coverage of Shortages
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. -
Risk Amplification Macro Model (RAMM)
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. -
Understanding Post-COVID Inflation Dynamics
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. -
Harnessing the benefit of state-contingent forward guidance
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. -
How well can large banks in Canada withstand a severe economic downturn?
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. -
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. -
What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data
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. -
Potential output and the neutral rate in Canada: 2021 update
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. -
A Generalized Endogenous Grid Method for Default Risk Models
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.