Employment/Mining
Could you please help me understand how the employment data for Colorado and its counties is derived and how to explain the difference between it and other sets to my clients? Your database indicates there are 3.2 million employees in Colorado.
I know your database includes more than CES employment, which is about 2.2 million. Nonemployer data is about 440,000.
This difference between your database and commonly used information presents two problems.
First, I would like to produce a report measuring the impact of mining on Colorado and some of its counties. I would like for the report to reconcile with a report put together by The National Mining Association, calledThe Economic Contributions of Mining (see attached).
The NMA report was produced using Implan data. The problem is employment data in their report does not match known employment levels in the Colorado mining industry. The problem is exacerbated at the county level. I cannot tell the agencies in a rural setting that the model says 800 people work at a mine, when they know there are only 400 employees.
On page 5 of the NMA report in Table 6 it states the direct effects of Colorado miners was 12,590 employees. On page 11, Table 10a the report stated the direct effects of coal mine worker employment was 3,910. The QCEW data reports about 5.400 mining workers and 2,200 coal mining workers for the state.
This brings me to the second problem, do I not use the model and calculate the impact by hand, using our known employment data. Or should I create an event, plug in the employment data we have, and use the results from that for the report?
Thank you.
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Hi Gary, The difference between the sum of CEW employment and non-employment and IMPLAN employment is that IMPLAN employment includes all proprietors. Proprietor employment includes not just non-employers, but also all owners of partnerships. So, if I own 5% of a partnership and never show up to work there, I still am an employee in IMPLAN data. In certain industries, the difference between wage & salary employment, non-employers, and the sum of all proprietors can be large, though usually it is small. Large differences tend to occur in oil & gas, mining, and real estate. It is our policy and practice not to comment on reports that use IMPLAN (unless retained in a consulting role to do so), but we can offer some possible ways to address the different concepts of employment used by various public sources and IMPLAN data. You could use IMPLAN’s own data to estimate the contribution or impact of mining, and explain that employment impact estimates for some sectors (whether direct, indirect, or induced) include owners of partnerships. If you do this, definitions of employment will be consistent. If you want to estimate only wage & salary + nonemployer jobs for coal mining, for example, and you believe that such jobs represent, say, 75% of IMPLAN jobs in that industry, you could adjust your estimates of employment effects accordingly (but only in the industries for which you have an estimate of the ratio between these concepts of employment – a total employment effect across several industries shouldn’t be adjusted by one industry’s ratio). If you use your own estimates of wage and salary and non-employer jobs (say, directly from QCEW or Census) as an impact, you will be underestimating economic effects, since when modeled, IMPLAN will assume that the initial employment effect you used as an input includes various types of partners in partnerships as employees. We are aware that customers often are interested in a concept of employment that does not include partners with limited roles within a company and we are working to make that distinction within our data and model. Thanks.
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