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