C5 - Econometric Modeling

• Predictive Density Combination Using a Tree-Based Synthesis Function

  Staff Working Paper 2023-61 Tony Chernis, Niko Hauzenberger, Florian Huber, Gary Koop, James Mitchell

  This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C3, C32, C5, C53

• Finding the balance—measuring risks to inflation and to GDP growth

  Staff Analytical Note 2023-18 Bruno Feunou, James Kyeong

  Using our new quantitative tool, we show how the risks to the inflation and growth outlooks have evolved over the course of 2023.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17

• Making It Real: Bringing Research Models into Central Bank Projections

  Staff Discussion Paper 2023-29 Marc-André Gosselin, Sharon Kozicki

  Macroeconomic projections and risk analyses play an important role in guiding monetary policy decisions. Models are integral to this process. This paper discusses how the Bank of Canada brings research models and lessons learned from those models into the central bank projection environment.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Economic models, Monetary policy JEL Code(s): C, C3, C32, C5, C51, E, E3, E37, E4, E47, E5, E52