C4 - Econometric and Statistical Methods: Special Topics

• Seasonal Adjustment of Weekly Data

  Staff Discussion Paper 2024-17 Jeffrey Mollins, Rachit Lumb

  The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C4, C5, C52, C8, E, E0, E01, E2, E21

• Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems

  Staff Working Paper 2024-15 Ajit Desai, Anneke Kosse, Jacob Sharples

  Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

  Content Type(s): Staff research, Staff working papers Topic(s): Digital currencies and fintech, Financial institutions, Financial services, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): C, C4, C45, C5, C55, D, D8, D83, E, E4, E42

• Machine learning for economics research: when, what and how

  Staff Analytical Note 2023-16 Ajit Desai

  This article reviews selected papers that use machine learning for economics research and policy analysis. Our review highlights when machine learning is used in economics, the commonly preferred models and how those models are used.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Central bank research, Econometric and statistical methods, Economic models JEL Code(s): A, A1, A10, B, B2, B23, C, C4, C45, C5, C55

• Predicting Changes in Canadian Housing Markets with Machine Learning

  Staff Discussion Paper 2023-21 Johan Brannlund, Helen Lao, Maureen MacIsaac, Jing Yang

  We apply two machine learning algorithms to forecast monthly growth of house prices and existing homes sales in Canada. Although the algorithms can sometimes outperform a linear model, the improvement in forecast accuracy is not always statistically significant.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods, Financial markets, Housing JEL Code(s): A, C, C4, C45, C5, C53, D, D2, R, R2, R3

• Digitalization: Implications for Monetary Policy

  Staff Discussion Paper 2023-18 Vivian Chu, Tatjana Dahlhaus, Christopher Hajzler, Pierre-Yves Yanni

  We explore the implications of digitalization for monetary policy, both in terms of how monetary policy affects the economy and in terms of data analysis and communication with the public.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Digitalization, Inflation and prices, Market structure and pricing, Monetary policy, Monetary policy communications, Monetary policy transmission JEL Code(s): C, C4, C8, E, E3, E31, E32, E5, E52

• Transmission of Cyber Risk Through the Canadian Wholesale Payment System

  Staff Working Paper 2022-23 Anneke Kosse, Zhentong Lu

  This paper studies how the impact of a cyber attack that paralyzes one or multiple banks' ability to send payments would transmit to other banks through the Canadian wholesale payment system. Based on historical payment data, we simulate a wide range of scenarios and evaluate the total payment disruption in the system.

  Content Type(s): Staff research, Staff working papers Topic(s): Financial institutions, Financial stability, Payment clearing and settlement systems JEL Code(s): C, C4, C49, E, E4, E42, E47, G, G2, G21

• How Long Does It Take You to Pay? A Duration Study of Canadian Retail Transaction Payment Times

  Staff Working Paper 2018-46 Geneviève Vallée

  Using an exclusive data set of payment times for retail transactions made in Canada, I show that cash is the most time-efficient method of payment (MOP) when compared with payments by debit and credit cards. I model payment efficiency using Cox proportional hazard models, accounting for consumer choice of MOP.

  Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C2, C25, C3, C36, C4, C41, D, D2, D23, E, E4, E41, E42

• A Barometer of Canadian Financial System Vulnerabilities

  Staff Analytical Note 2017-24 Thibaut Duprey, Tom Roberts

  This note presents a composite indicator of Canadian financial system vulnerabilities—the Vulnerabilities Barometer. It aims to complement the Bank of Canada’s vulnerabilities assessment by adding a quantitative and synthesized perspective to the more granular (distributional) analysis presented in the Financial System Review.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Econometric and statistical methods, Financial stability, Monetary and financial indicators JEL Code(s): C, C1, C14, C4, C40, D, D1, D14, E, E3, E32, E6, E66, F, F0, F01, G, G0, G01, G1, G15, G2, G21, H, H6, H63

• A New Approach to Infer Changes in the Synchronization of Business Cycle Phases

  Staff Working Paper 2014-38 Danilo Leiva-Leon

  This paper proposes a Markov-switching framework to endogenously identify the following: (1) regimes where economies synchronously enter recessionary and expansionary phases; and (2) regimes where economies are unsynchronized, essentially following independent business cycles.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Regional economic developments JEL Code(s): C, C3, C32, C4, C45, E, E3, E32

• Predicting Financial Stress Events: A Signal Extraction Approach

  Staff Working Paper 2014-37 Ian Christensen, Fuchun Li

  The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky, Lizondo and Reinhart (1998) is used to monitor the evolution of a number of economic indicators that tend to exhibit an unusual behaviour in the periods preceding a financial stress event.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial stability JEL Code(s): C, C1, C14, C4, E, E3, E37, E4, E47, F, F3, F36, F37, G, G0, G01, G1, G17