Search

Content Types

Subjects

Authors

Research Themes

JEL Codes

Sources

Published After

Published Before

190 Results

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.

Competition for Exclusivity and Customer Lock-in: Evidence from Copyright Enforcement in China

Staff working paper 2023-43 Youming Liu
This paper studies the music streaming industry and argues that having exclusive rights granted by copyright law drives firms to offer exclusive content to lock in customers. I employ theoretical and descriptive empirical analysis, along with a dynamic structural model, to support the argument and explore policies for improving competition.

Digitalization: Implications for Monetary Policy

We explore the implications of digitalization for monetary policy, both in terms of how monetary policy affects the economy and in terms of data analysis and communication with the public.

Generalized Autoregressive Gamma Processes

Staff working paper 2023-40 Bruno Feunou
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.

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.

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.

What People Believe About Monetary Finance and What We Can(’t) Do About It: Evidence from a Large-Scale, Multi-Country Survey Experiment

Staff working paper 2023-36 Cars Hommes, Julien Pinter, Isabelle Salle
We conduct a large-scale survey to shed light on what people believe about public finance. An experiment demonstrates that central bank communication can persistently shift views on monetary financing. It further suggests that views on monetary financing impact support for fiscal discipline.

Pricing Indefinitely Lived Assets: Experimental Evidence

Staff working paper 2023-25 John Duffy, Janet Hua Jiang, Huan Xie
We study the trading of an asset with bankruptcy risk. The traded price of the asset is, on average, 40% of the expected total dividend payments. We investigate which economic models can explain the low traded price.

Turning Words into Numbers: Measuring News Media Coverage of Shortages

Staff discussion paper 2023-8 Lin Chen, Stéphanie 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.

Supply Drivers of US Inflation Since the COVID-19 Pandemic

Staff working paper 2023-19 Serdar Kabaca, Kerem Tuzcuoglu
This paper examines the contribution of several supply factors to US headline inflation since the start of the COVID-19 pandemic. We identify six supply shocks using a structural VAR model: labor supply, labor productivity, global supply chain, oil price, price mark-up and wage mark-up shocks.
Go To Page