I have a researcher who is interested in a custom tab from the Labour Force Survey. Can you confirm that the following would be available as a custom tab?
He is looking at assessing socio-economic impacts of changes in the forest products sector – both mill closures and start-ups of new biorefinery ventures – and would like to develop a socio-economic index (or measures) that can be incorporated into Canmet ENERGY (part of Natural Resources Canada) I-BIOREF biorefinery simulation model.
Here are the specifications for the data he is interested in from the LFS. The attached excel file provides an illustration of the data output framework that he would like to see. It also includes a list of all the NAICS and NOC codes he is looking for.
- Number of total workers (all industries)
- Employment income (all workers/all industries)
- Number of workers by industry – NAICS
- Total Employment Income by industry – NAICS
- Number of Employees by Occupation – NOC
- Highest level of Education attainment
- Geographic areas – the CA’s specified will be the focus of case study examinations within my research because each exhibits particular characteristics of change / rejuvenation with respect to the forest sector. The CA’s are: Corner Brook, NL; Val d’Or, QC; Thunder Bay, ON; and Prince George, BC. Additionally, it would also be very useful to obtain the data for two Census Subdivisions in Québec – La Tuque and Matagami – as these two communities exhibit forest industry change characteristics that are not readily observable elsewhere.
- Time frame – the overall time period of focus / interest is 2000 – 2017. Monthly data is not essential – annualised or December end-of-year data would work just fine. My objective in pursuing the LFS data is to obtain more frequent tracking of changes in the communities than is achievable from the Census data.
Answer:
I’ve received the following response from subject matter:
“The level of detail requested is too high for the CA geography.
The Labour force survey is not designed for this level of granularity.”
