Christopher Henry

Survey Methodologist

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Bio

Christopher (Chris) is a Survey Methodologist. He joined the Bank in 2012. In his role, Christopher contributes to the design, implementation, and analysis of a range of surveys that measure the use of cash and alternative methods of payment.  He holds an MA in Economics from Western University and an MSc in Mathematics from McMaster University.


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Staff Analytical Notes

Bitcoin Awareness and Usage in Canada: An Update

Staff Analytical Note 2018-23 Christopher Henry, Kim Huynh, Gradon Nicholls
The results of our 2017 Bitcoin Omnibus Survey (December 12 to 15, 2017) when compared with those from 2016 show that Bitcoin “awareness” increased from 64 to 85 per cent, while ownership increased from 2.9 to 5.0 per cent. Most Bitcoin purchasers are using the cryptocurrency as an investment and not as a means of payment for goods or services.

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Staff Discussion Papers

2018 Bitcoin Omnibus Survey: Awareness and Usage

The Bank of Canada continues to use the Bitcoin Omnibus Survey (BTCOS) to monitor trends in Canadians’ awareness, ownership and use of Bitcoin. The most recent iteration was conducted in late 2018, following an 85 percent decline in the price of Bitcoin throughout the year.

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Staff Working Papers

Bitcoin Awareness and Usage in Canada

Staff Working Paper 2017-56 Christopher Henry, Kim Huynh, Gradon Nicholls
There has been tremendous discussion of Bitcoin, digital currencies and FinTech. However, there is limited empirical evidence of Bitcoin’s adoption and usage. We propose a methodology to collect a nationally representative sample using the Bitcoin Omnibus Survey (BTCOS) to track the ubiquity and usage of Bitcoin in Canada.

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Technical Reports

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

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