Mining GRP/value added

Hello,

I'm working on an analysis related to the mining industry in Northeast Minnesota. In describing the study area, I included a graph that showed value added by industry for the eight sectors in IMPLAN's default aggregate scheme. The mining industry was reported to have contributed $1.1 billion to the region's total value added.

However, in another section of the report, I pulled data from the Bureau of Economic Analysis website, which showed $2.1 billion in GRP (2018, in current dollars) for the mining industry (two-digit NAICS sector 21). I can't figure out why the value shown in IMPLAN would be so different from that reported by the BEA. I tried to find a more detailed list of the IMPLAN sectors included in the default aggregation scheme, but every link I found on the forum was broken. Can you help me?

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    Hello there!

    Our data isn't directly comparable to BEA data. We do not use the Total GDP data from the BEA since it is lagged a year relative to the IMPLAN data year.  However, we do use that data set for some of the components of GDP.

    Here is the process that IMPLAN uses to calculate Value Added:

    1. We start with the one-year-lagged raw Value Added data from the BEA, which provides Total GDP, EC, Gross Operating Surplus, Gross TOPI, and Subsidies. These data do not separate out PI from OPI but rather report the combination of the two, known as Gross Operating Surplus (GOS).
    2. To get OPI, we subtract our own PI estimates (for which we have a separate process) for the sector and state and year (which is one year lagged, so we're using the previous year's PI value).  
    3. Now, since these are lagged values, we have to project them, and to do that we use the change in EC (for which we have a separate process) between the two years.  We use this growth rate to project GDP, Gross TOPI, and Subsidies, then we subtract from this projected GDP value the projected TOPI and subsidies values as well as our non-lagged estimates for EC and PI (for which we have separate processes) to arrive at a "projected" OPI value.  
      1. Note: The reason we use the growth rate to project GDP, Gross TOPI, and Subsidies, but not OPI itself, is that GDP and Gross TOPI are always positive numbers, which lends well to them being used with growth rates.  Things that can be negative are harder to project - positive growth in EC applied to a negative OPI value would yield even more negative OPI, which is counterintuitive for a growing sector.  Thus, we project the other items (GDP, Gross TOPI, Subsidies) and subtract everything else from GDP to arrive at OPI.  
    4. The next task is to distribute this value among the IMPLAN construction sectors.  To do this, we rely on the U.S. values, for which we have other data sources that give more sector detail, including the BEA Benchmark, which comes out every 5 years, with the new one having just come out last year and having been incorporated into the IMPLAN data for the first time in the 2018 data set.  

     

    Info on Value Added data: 

    How Value Added is estimated and distributed:

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