Tony Chernis - Latest

• Decision Synthesis in Monetary Policy

  Staff Working Paper 2024-30 Tony Chernis, Gary Koop, Emily Tallman, Mike West

  We use Bayesian predictive decision synthesis to formalize monetary policy decision-making. We develop a case-study of monetary policy decision-making of an inflation-targeting central bank using multiple models in a manner that considers decision goals, expectations and outcomes.

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

• 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 Research Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C3, C32, C5, C53

• 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 Research Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37

• The Business Leaders’ Pulse—An Online Business Survey

  Staff Discussion Paper 2022-14 Tony Chernis, Chris D'Souza, Kevin MacLean, Tasha Reader, Joshua Slive, Farrukh Suvankulov

  This paper introduces the Business Leaders’ Pulse, a new online survey conducted each month. It is designed to provide timely and flexible input into the Bank of Canada’s monetary policy decision making by asking firms about their sales and employment growth expectations, the risks to their business outlook, and topical questions that address specific information needs of the Bank.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C8, C83, D, D2, D22, E, E3, E32

• 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 Research Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C52, C53, E, E3, E7

• Disaggregating Household Sensitivity to Monetary Policy by Expenditure Category

  Staff Analytical Note 2018-32 Tony Chernis, Corinne Luu

  Because the Bank of Canada has started withdrawing monetary stimulus, monitoring the transmission of these changes to monetary policy will be important. Subcomponents of consumption and housing will likely respond differently to a monetary policy tightening, both in terms of the aggregate effect and timing.

  Content Type(s): Staff research, Staff analytical notes Research Topic(s): Business fluctuations and cycles, Domestic demand and components, Econometric and statistical methods, Housing, Interest rates, Monetary policy transmission, Recent economic and financial developments JEL Code(s): C, C3, C32, E, E2, E21, E22, E4, E43, E47, E5, E52

• Nowcasting Canadian Economic Activity in an Uncertain Environment

  Staff Discussion Paper 2018-9 Tony Chernis, Rodrigo Sekkel

  This paper studies short-term forecasting of Canadian real GDP and its expenditure components using combinations of nowcasts from different models. Starting with a medium-sized data set, we use a suite of common nowcasting tools for quarterly real GDP and its expenditure components.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C53, E, E3, E37, E5, E52

• A Three‐Frequency Dynamic Factor Model for Nowcasting Canadian Provincial GDP Growth

  Staff Discussion Paper 2017-8 Tony Chernis, Gabriella Velasco, Calista Cheung

  This paper estimates a three‐frequency dynamic factor model for nowcasting Canadian provincial gross domestic product (GDP). Canadian provincial GDP is released by Statistics Canada on an annual basis only, with a significant lag (11 months).

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Regional economic developments JEL Code(s): C, C5, C53, E, E3, E32, E37, R, R1, R11

• A Dynamic Factor Model for Nowcasting Canadian GDP Growth

  Staff Working Paper 2017-2 Tony Chernis, Rodrigo Sekkel

  This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, C38, C5, C53, E, E3, E37

• Global Real Activity for Canadian Exports: GRACE

  Staff Discussion Paper 2017-2 André Binette, Tony Chernis, Daniel de Munnik

  Canadian exports have often disappointed since the Great Recession. The apparent disconnect between exports and the Bank of Canada’s current measure of foreign demand has created an impetus to search for an alternative.

  Content Type(s): Staff research, Staff discussion papers Research Topic(s): Balance of payments and components, Econometric and statistical methods, Exchange rates JEL Code(s): F, F1, F10, F14, F4, F43