MiHR's Labour Market Information Methodology

This following information outlines the methodology used to produce forecasts of hiring requirements in the mining industry for each region in Canada.

1. Collect and analyze data that may potentially explain changes in the number of jobs in each region's mining industry.
2. Determine the driver(s) that explain the greatest level of variation in employment in each region's mining industry by testing various model specifications through regression analysis.
3. Produce baseline, contractionary and expansionary forecasts for each driver determined in Step 2.
4. Produce the forecasts for employment in each region under baseline, contractionary and expansionary scenarios.
5. Produce forecasts of the total hiring requirements given the change in employment determined in Step 4 and estimates of replacement requirements due to retirement and non-retirement separation.
6. Calculate and apply occupational coefficients for each region to produce estimates of hiring requirements by occupation.

Several indicators were considered, based on their potential to explain changes in the level of employment in the mining industry at the regional level. Potential explanatory variables included:

• Real compensation per hour worked
• Real level of production
• Industrial Materials Commodity Price Index
• Metals and Minerals Price Index
• Selected Commodity Price Indices (e.g., iron ore, gold and nickel)
• Labour productivity (i.e., real GDP per hour worked)

 Availability of data was a limiting factor in model development.

• Employment series and labour productivity data for the mining industry were obtained from Statistics Canada . Due to confidentiality rules, employment data are suppressed for various provinces and territories and were thus available only at a regional level.
• Suppression of some provincial level mining production values prohibited the development of a weighted commodity price index for each province.
• In select cases where it was known that certain metals represent a large proportion of the provincial total (e.g., iron ore in Quebec), individual price indices were used, as noted in the Canadian Mining Industry Employment and Hiring Forecasts 2010 report. In all other cases the Bank of Canada's weighted Metals and Minerals Price Index was used.

Forecast models were developed for the following geographical areas. The national forecast is based on the sum of all regional forecasts.

• Atlantic Region
• Quebec
• Ontario
• Prairie Region
• British Columbia
• Territories

In general, it was found that metal and mineral prices in conjunction with labour productivity, to explain longer-term trends in employment, explained the most variation in mining employment.

• Employment in each region is strongly related to commodity price levels, labour productivity levels and the previous years' employment.
• Commodity prices and employment are positively related. When commodity prices rise, employment levels increase.
  Labour productivity and employment are negatively related. When labour productivity increases employment levels decline.
• Current employment levels were positively related to the previous year's employment.