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2125 Results

The Heterogeneous Effects of COVID-19 on Canadian Household Consumption, Debt and Savings

Staff working paper 2020-51 James (Jim) C. MacGee, Thomas Michael Pugh, Kurt See
The impact of COVID-19 on Canadian households’ debt and unplanned savings varies by household income. Low-income and high-income households accrued unplanned savings, while middle-income households tended to accumulate more debt.

Macroeconomic Predictions Using Payments Data and Machine Learning

Staff working paper 2022-10 James Chapman, Ajit Desai
We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges.

What COVID-19 May Leave Behind: Technology-Related Job Postings in Canada

Staff working paper 2022-17 Alejandra Bellatin, Gabriela Galassi
COVID-19 affects technology adoption: online job postings for technology-related occupations fall less during pandemic lockdowns and pick up faster during reopenings than postings for more traditional occupations.

Lending Standards, Productivity and Credit Crunches

Staff working paper 2019-25 Jonathan Swarbrick
We propose a macroeconomic model in which adverse selection in investment drives the amplification of macroeconomic fluctuations, in line with prominent roles played by the credit crunch and collapse of the asset-backed security market in the financial crisis.
August 4, 2010

Fellowship Award

Annual research grants and expense allowances for a term of up to five years.

We Didn’t Start the Fire: Effects of a Natural Disaster on Consumers’ Financial Distress

We use detailed consumer credit data to investigate the impact of the 2016 Fort McMurray wildfire, the costliest wildfire disaster in Canadian history, on consumers’ financial stress. We focus on the arrears of insured mortgages because of their important implications for financial institutions and insurers’ business risk and relevant management practices.

Markov‐Switching Three‐Pass Regression Filter

We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes.
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