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    IMPLAN Support
    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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