Statistics Canada Crowdsources Cannabis Prices

By Allan W. Gregory and Eliane Hamel Barker, Queen’s University

Statistics Canada recently took up the difficult challenge of finding out what Canadians pay for their cannabis both medically (licensed and unlicensed) and recreationally. Currently only licensed use of medical cannabis (both dried and oil) is legal to purchase from licensed producers under Access to Cannabis for Medical Purposes Regulations (ACMPR). One reason governments are so interested in the street price of cannabis is the legalization of marijuana for recreational use due sometime this summer. The thinking is that legal marijuana prices must not be greater than those on the street; otherwise black markets will continue to flourish.

Statistics Canada is not new to the survey business and have in the past attempted to price cannabis and quantities smoked. However, in their most recent effort, a novel feature was using crowdsourcing on a web site survey to gather the data. Statistics Canada understood that there was a selectivity or participation problem in such a methodology but decided this was the best approach possible. We agree with this decision. Since cannabis was soon to be legalized for recreational use and no special personal identifiers were asked, the participating decision should not be associated with either positive (higher price) or negative (lower price) bias.Read More »

Doctoral Fellow develops methods to better understand regional recessions

sergei2Zooming-in without losing focus – understanding regional recessions and the importance of spatial interactions

By Sergei Shibaev, JDI Student Fellow, Queen’s University

Here is the scenario – you are an interested party (e.g. regional policy maker or researcher) in a small regional division in Canada (e.g. Central Okanagan Regional District of British Columbia).  You need to know if your region is likely to become economically at-risk or potentially distressed separately from the national economy, and to do so you require an informative assessment of any synchronicities (i.e. co-movements) with other regions in the country regarding how your small region’s economy has evolved in the last decade. Furthermore, you have existing knowledge regarding several types of connections to other regions that you know are important for your local economy (e.g. your largest regional trading partners), and you wish to explore and compare them through time. I develop and investigate a tool that is capable of learning by itself about these types of phenomena in a unified framework that collectively models a large number of small regions in a country.Read More »