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3829 Results

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.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff working paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.
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