Seasonal Adjustment of Weekly Data Staff discussion paper 2024-17 Jeffrey Mollins, Rachit Lumb The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C4, C5, C52, C8, E, E0, E01, E2, E21 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
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 JEL Code(s): C, C1, C11, C3, C32, C5, C53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Monetary policy, Monetary policy framework and transmission
Non-Parametric Identification and Testing of Quantal Response Equilibrium Staff working paper 2024-24 Johannes Hoelzemann, Ryan Webb, Erhao Xie We show that the utility function and the error distribution are non-parametrically over-identified under Quantal Response Equilibrium (QRE). This leads to a simple test for QRE. We illustrate our method in a Monte Carlo exercise and a laboratory experiment. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C14, C5, C57, C9, C92 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models
Parallel Tempering for DSGE Estimation Staff working paper 2024-13 Joshua Brault I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C15, E, E1, E10 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models
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 JEL Code(s): C, C1, C11, C3, C32, C5, C53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Three things we learned about the Lynx payment system Staff analytical note 2023-14 Nikil Chande, Zhentong Lu, Hiru Rodrigo, Phoebe Tian Canada transitioned to a new wholesale payment system, Lynx, in August 2021. Lynx is based on a real-time settlement model that eliminates credit risk in the system. This model can require more liquidity; however, Lynx’s design allows Canada’s wholesale payments to settle efficiently. Content Type(s): Staff research, Staff analytical notes JEL Code(s): C, C1, C10, E, E4, E42, G, G2, G28 Research Theme(s): Money and payments, Payment and financial market infrastructures
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 JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Unmet Payment Needs and a Central Bank Digital Currency Staff discussion paper 2023-15 Christopher Henry, Walter Engert, Alexandra Sutton-Lalani, Sebastian Hernandez, Darcey McVanel, Kim Huynh We discuss the payment habits of Canadians both in the current payment environment and in a hypothetical cashless environment. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54 Research Theme(s): Money and payments, Cash and bank notes, Digital assets and fintech, Retail payments
Global Demand and Supply Sentiment: Evidence from Earnings Calls Staff working paper 2023-37 Temel Taskin, Franz Ulrich Ruch This paper quantifies global demand, supply and uncertainty shocks and compares two major global recessions: the 2008–09 Great Recession and the COVID-19 pandemic. We use two alternate approaches to decompose economic shocks: text mining techniques on earnings calls transcripts and a structural Bayesian vector autoregression model. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C3, C32, E, E3, E32, G, G1, G10 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
What Can Earnings Calls Tell Us About the Output Gap and Inflation in Canada? Staff discussion paper 2023-13 Marc-André Gosselin, Temel Taskin We construct new indicators of demand and supply for the Canadian economy by using natural language processing techniques to analyze earnings calls of publicly listed firms. Our results indicate that the new indicators could help central banks identify inflationary pressures in real time. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C1, C3, E, E3, E5 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting