Sectoral Uncertainty Staff Working Paper 2022-38 Efrem Castelnuovo, Kerem Tuzcuoglu, Luis Uzeda We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Monetary policy and uncertainty JEL Code(s): C, C5, C51, C55, E, E3, E32, E4, E44
Historical Data on Repurchase Agreements from the Canadian Depository for Securities Technical Report No. 121 Maxim Ralchenko, Adrian Walton We develop an algorithm that extracts information about sale and repurchase agreements (repos) from disaggregated settlement data in order to generate a new historical dataset for research. Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C5, C55, C8, C81, G, G1, G10
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. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52
Business Closures and (Re)Openings in Real Time Using Google Places Staff Working Paper 2022-1 Thibaut Duprey, Daniel E. Rigobon, Philip Schnattinger, Artur Kotlicki, Soheil Baharian, T. R. Hurd The COVID-19 pandemic highlighted the need for policy-makers to closely monitor disruptions to the retail and food business sectors. We present a new method to measure business opening and closing rates using real-time data from Google Places, the dataset behind the Google Maps service. Content Type(s): Staff research, Staff working papers Topic(s): Firm dynamics, Recent economic and financial developments JEL Code(s): C, C5, C55, C8, C81, D, D2, D22, E, E3, E32
Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data Staff Working Paper 2021-43 Tatjana Dahlhaus, Angelika Welte We examine how consumers have adjusted their payment habits during the COVID-19 pandemic. They seem to perform fewer transactions, spend more in each transaction, use less cash at the point of sale and withdraw cash from ATMs linked to their financial institution more often than from other ATMs. Content Type(s): Staff research, Staff working papers Topic(s): Coronavirus disease (COVID-19), Domestic demand and components, Payment clearing and settlement systems, Recent economic and financial developments JEL Code(s): C, C2, C22, C5, C55, D, D1, D12, E, E2, E21, E4, E42, E5, E52
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