C8 - Data Collection and Data Estimation Methodology; Computer Programs

• Qualitative Field Research in Monetary Policy Making

  Staff Discussion Paper 2021-1 Chris D'Souza, Jane Voll

  Central banks conduct research involving in-depth interviews with external parties—but little is known about how this information affects monetary policy. We address this gap by analyzing open-ended interviews with senior central bank economic and policy staff who work closely with policy decision-makers.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Business fluctuations and cycles, Monetary policy, Monetary policy and uncertainty JEL Code(s): C, C8, C83, E, E3, E37, E5, E52

• A Reference Guide for the Business Outlook Survey

  Staff Discussion Paper 2020-15 David Amirault, Naveen Rai, Laurent Martin

  The Business Outlook Survey (BOS) has become an important part of monetary policy deliberations at the Bank of Canada and is also well known in Canadian policy and financial circles. This paper compiles more than 20 years of experience conducting the BOS and serves as a comprehensive reference manual.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Firm dynamics, Regional economic developments JEL Code(s): C, C8, C83, D, D2, D22, E, E3, E32

• Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

  Staff Working Paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez

  Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

  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, C5, C52, C6, C65, C8, C81, E, E4, E42, E5, E51

• Sample Calibration of the Online CFM Survey

  Technical Report No. 118 Marie-Hélène Felt, David Laferrière

  The Canadian Financial Monitor (CFM) survey uses non-probability sampling for data collection, so selection bias is likely. We outline methods for obtaining survey weights and discuss the conditions necessary for these weights to eliminate selection bias. We obtain calibration weights for the 2018 and 2019 online CFM samples.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C8, C81, C83

• Social Learning and Monetary Policy at the Effective Lower Bound

  Staff Working Paper 2020-2 Jasmina Arifovic, Alex Grimaud, Isabelle Salle, Gauthier Vermandel

  This research develops a model in which the economy is directly influenced by how pessimistic or optimistic economic agents are about the future. The agents may hold different views and update them as new economic data become available.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Central bank research, Credibility, Economic models, Monetary policy, Monetary policy communications JEL Code(s): C, C8, C82, E, E3, E32, E5, E52

• 2018 Merchant Acceptance Survey

  Staff Analytical Note 2019-31 Kim Huynh, Gradon Nicholls, Mitchell Nicholson

  In 2015, the Bank of Canada surveyed merchants and found that cash was nearly universally accepted (Fung, Huynh and Kosse 2017). Since 2015, retail payments in Canada have become increasingly digitalized, as many Canadians have adopted digital payment innovations like contactless cards and Interac e-Transfer.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C8, D, D2, D22, E, E4, L, L2

• What Do Survey Data Tell Us About US Businesses?

  Staff Working Paper 2019-45 Anmol Bhandari, Serdar Birinci, Ellen McGrattan, Kurt See

  This paper examines the reliability of survey data on business incomes, valuations, and rates of return, which are key inputs for studies of wealth inequality and entrepreneurial choice.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Firm dynamics JEL Code(s): C, C8, C83, E, E2, E22, H, H2, H25

• Online Job Seekers in Canada: What Can We Learn from Bing Job Queries?

  Staff Analytical Note 2019-18 André Binette, Karyne B. Charbonneau, Nicholas Curtis, Gabriela Galassi, Scott Counts, Justin Cranshaw

  Labour markets in Canada and around the world are evolving rapidly with the digital economy. Traditional data are adapting gradually but are not yet able to provide timely information on this evolution.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Central bank research, Labour markets, Monetary policy JEL Code(s): C, C8, C80, E, E2, E24, J, J2, J21

• 2017 Methods-of-Payment Survey: Sample Calibration and Variance Estimation

  Technical Report No. 114 Heng Chen, Marie-Hélène Felt, Christopher Henry

  This technical report describes sampling, weighting and variance estimation for the Bank of Canada’s 2017 Methods-of-Payment Survey. Under quota sampling, a raking ratio method is implemented to generate weights with both post-stratification and nonparametric nonresponse weight adjustments.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C8, C81, C83

• GDP by Industry in Real Time: Are Revisions Well Behaved?

  Staff Analytical Note 2018-40 Patrick Rizzetto

  The monthly data for real gross domestic product (GDP) by industry are used extensively in real time both to ground the Bank of Canada’s monitoring of economic activity and in the Bank’s nowcasting tools, making these data one of the most important high-frequency time series for Canadian nowcasting.

  Content Type(s): Staff research, Staff analytical notes Topic(s): Business fluctuations and cycles, Central bank research, Econometric and statistical methods JEL Code(s): C, C5, C53, C8, C82, E, E0, E01