C55 - Large Data Sets: Modeling and Analysis

• 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.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52

• Can Media and Text Analytics Provide Insights into Labour Market Conditions in China?

  Staff Working Paper 2018-12 Jeannine Bailliu, Xinfen Han, Mark Kruger, Yu-Hsien Liu, Sri Thanabalasingam

  The official Chinese labour market indicators have been seen as problematic, given their small cyclical movement and their only-partial capture of the labour force. In our paper, we build a monthly Chinese labour market conditions index (LMCI) using text analytics applied to mainland Chinese-language newspapers over the period from 2003 to 2017.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics, Labour markets JEL Code(s): C, C3, C38, C5, C55, E, E2, E24, E27

• What Drives Interbank Loans? Evidence from Canada

  Staff Working Paper 2018-5 Narayan Bulusu, Pierre Guérin

  We identify the drivers of unsecured and collateralized loan volumes, rates and haircuts in Canada using the Bayesian model averaging approach to deal with model uncertainty. Our results suggest that the key friction driving behaviour in this market is the collateral reallocation cost faced by borrowers.

  Content Type(s): Staff research, Staff working papers Topic(s): Financial markets, Wholesale funding JEL Code(s): C, C5, C55, E, E4, E43, G, G2, G23