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175 Results

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.

Macroeconomic Disasters and Consumption Smoothing: International Evidence from Historical Data

Staff working paper 2023-4 Lorenzo Pozzi, Barbara Sadaba
Does consumption smoothing fundamentally decrease during macroeconomic disasters? This paper uses a large historical dataset (1870–2016) for 16 industrial economies to show that during macroeconomic disasters (e.g., wars, pandemics, depressions) aggregate consumption and income are significantly less decoupled than during normal times.

The 2021–22 Merchant Acceptance Survey Pilot Study

Staff discussion paper 2023-1 Angelika Welte, Joy Wu
The rise in digital payment innovations has spurred a discussion about the future of cash at the point of sale. The Bank conducted the 2021–22 Merchant Acceptance Survey Pilot Study to study trends in merchant cash acceptance and monitor conditions for the potential issuance of a central bank digital currency.

Simulating Intraday Transactions in the Canadian Retail Batch System

Staff working paper 2023-1 Nellie Zhang
This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.

Private Digital Cryptoassets as Investment? Bitcoin Ownership and Use in Canada, 2016-2021

We report on the dynamics of Bitcoin awareness and ownership from 2016 to 2021, using the Bank of Canada's Bitcoin Omnibus Surveys (BTCOS). Our analysis also helps understand Bitcoin owners who adopted during the COVID-19 and how they differ from long-term owners. 

Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models

Staff discussion paper 2022-19 James Younker
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models.
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