Econometric and statistical methods
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Generalized Autoregressive Gamma Processes
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. -
Cryptoasset Ownership and Use in Canada: An Update for 2022
We find that Bitcoin ownership declined from 13% in 2021 to 10% in 2022. This drop occurred against a background of steep price declines and an increasingly tight regulatory atmosphere. -
Is Climate Transition Risk Priced into Corporate Credit Risk? Evidence from Credit Default Swaps
We study whether the credit derivatives of firms reflect the risk from climate transition. We find that climate transition risk has asymmetric and significant economic impacts on the credit risk of more vulnerable firms, and negligible effects on other firms. -
Global Demand and Supply Sentiment: Evidence from Earnings Calls
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?
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. -
Benchmarks for assessing labour market health: 2023 update
We enhance benchmarks for assessing strength in the Canadian labour market. We find the labour market remains tight despite recent strong increases in labour supply, including among prime-working-age women. We also assess the anticipated easing in labour conditions in a context of high population growth. -
Turning Words into Numbers: Measuring News Media Coverage of Shortages
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
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. -
Cost Pass-Through with Capacity Constraints and International Linkages
How are regional cost shocks passed through into global prices? We investigate the role of short-run capacity constraints and show that they can induce stark non-linearities in the pass-through. We highlight this effect for the market for ammonia, a commodity produced largely from natural gas.