Nowcasting Canadian GDP with Density Combinations Staff Discussion Paper 2022-12 Tony Chernis, Taylor Webley We present a tool for creating density nowcasts for Canadian real GDP growth. We demonstrate that the combined densities are a reliable and accurate tool for assessing the state of the economy and risks to the outlook. Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C52, C53, E, E3, E7
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
Equilibrium in Two-Sided Markets for Payments: Consumer Awareness and the Welfare Cost of the Interchange Fee Staff Working Paper 2022-15 Kim Huynh, Gradon Nicholls, Oleksandr Shcherbakov We construct and estimate a structural two-stage model of equilibrium in a market for payments in order to quantify the network externalities and identify the main determinants of consumer and merchant decisions. Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services JEL Code(s): C, C5, C51, D, D1, D12, E, E4, E42, L, L1, L14
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
Payment Coordination and Liquidity Efficiency in the New Canadian Wholesale Payments System Staff Discussion Paper 2022-3 Francisco Rivadeneyra, Nellie Zhang We study the impact of the Bank of Canada’s choice of settlement mechanism in Lynx on participant behaviors, liquidity usage, payment delays and the overall operational efficiency of the new system. Content Type(s): Staff research, Staff discussion papers Topic(s): Payment clearing and settlement systems JEL Code(s): C, C5, E, E4, E42, E5, E58
Assessing Climate-Related Financial Risk: Guide to Implementation of Methods Technical Report No. 120 Hossein Hosseini, Craig Johnston, Craig Logan, Miguel Molico, Xiangjin Shen, Marie-Christine Tremblay A pilot project on climate transition scenarios by the Bank of Canada and the Office of the Superintendent of Financial Institutions assessed climate-related credit and market risks. This report describes the project’s methodologies and provides guidance on implementing them. Content Type(s): Staff research, Technical reports Topic(s): Climate change, Credit and credit aggregates, Econometric and statistical methods, Financial stability JEL Code(s): C, C5, C53, C8, C83, G, G1, G3, G32
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
Covariates Hiding in the Tails Staff Working Paper 2021-45 Milian Bachem, Lerby Ergun, Casper G. de Vries We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data. Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C1, C14, C5, C58
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
Estimating Large-Dimensional Connectedness Tables: The Great Moderation Through the Lens of Sectoral Spillovers Staff Working Paper 2021-37 Felix Brunner, Ruben Hipp Understanding the size of sectoral links is crucial to predicting the impact of a crisis on the whole economy. We show that statistical learning techniques substantially outperform traditional estimation techniques when measuring large networks of these links. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C2, C22, C5, C52, E, E2, E23, E27