Econometric, statistical and computational methods

• 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 JEL Code(s): C, C5, C52, C53, E, E3, E7 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting

• More Than Words: Fed Chairs’ Communication During Congressional Testimonies

  Staff working paper 2022-20 Michelle Alexopoulos, Xinfen Han, Oleksiy Kryvtsov, Xu Zhang

  We measure soft information contained in the congressional testimonies of U.S. Federal Reserve Chairs and analyze its effect on financial markets. Increases in the Chair’s text-, voice-, or face-emotion indices during these testimonies generally raise stock prices and lower their volatility.

  Content Type(s): Staff research, Staff working papers JEL Code(s): E, E5, E52, E58, E7, E71 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods, Monetary policy, Monetary policy framework and transmission

• 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 JEL Code(s): C, C5, C55, C8, C81, G, G1, G10 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods

• 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 JEL Code(s): C, C5, C51, D, D1, D12, E, E4, E42, L, L1, L14 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Payment and financial market infrastructures, Retail payments

• 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 JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting, Money and payments, Retail payments

• Assessing Climate-Related Financial Risk: Guide to Implementation of Methods

  Technical report No. 120 Hossein Hosseini Jebeli, 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 JEL Code(s): C, C5, C53, C8, C83, G, G1, G3, G32 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Structural challenges, Climate change

• 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 JEL Code(s): C, C5, C55, C8, C81, D, D2, D22, E, E3, E32 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting

• Bitcoin Adoption and Beliefs in Canada

  Staff working paper 2021-60 Daniela Balutel, Christopher Henry, Jorge Vásquez, Marcel Voia

  Using an economic model as well as survey data from the Bank of Canada, we study what factors influence the adoption of Bitcoin in Canada.

  Content Type(s): Staff research, Staff working papers JEL Code(s): D, D8, D83, O, O3, O33 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models, Money and payments, Digital assets and fintech

• Energy Efficiency and Fluctuations in CO2 Emissions

  Staff working paper 2021-47 Soojin Jo, Lilia Karnizova

  Carbon dioxide emissions have been commonly modelled as rising and falling with total output. Yet many factors, such as energy-efficiency improvements and shifts to cleaner energy, can break this relationship. We evaluate these factors using US data and find that changes in energy efficiency of consumption goods explain a significant proportion of emissions fluctuations. This finding also implies that models that omit energy efficiency likely overestimate the trade-off between environmental protection and economic performance.

  Content Type(s): Staff research, Staff working papers JEL Code(s): E, E3, E32, Q, Q4, Q43, Q5, Q50, Q55 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting, Structural challenges, Climate change

• 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 JEL Code(s): C, C0, C01, C1, C14, C5, C58 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods