Significant difference in Grain Farming employment

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    IMPLAN Support
    Hi Suzette, There were several changes that occurred with the 2013 data set from the 2012, two of which were very important for the Grain Farming sector: [u]New Census of Agriculture[/u]: The Census of Agriculture is released every 5 years. The 2012 Census of Agriculture was released in 2014 and incorporated into the 2013 IMPLAN data set. Thus, there may be some sizeable changes in some farm sectors in some regions. [u]NASS Data for Agriculture Output[/u]: We now use NASS sales and production data, where available, as a supplement to ERS agricultural output by state, since the ERS sales data may omit inventory changes, home consumption, and production used in the production process of another agricultural good (e.g. hay used to feed animals). Thus, large differences may occur with products that are likely to be added or removed from inventory (grains) or consumed on a farm (hay, meat). The agriculture sectors are particularly difficult to estimate because there are no employment and earnings data collected on a commodity basis, even at the national level. The BEA’s REA data have county-level employment and income data, but these are farm totals that are not broken down by type of agricultural commodity. And while CEW publishes some data by agricultural commodity, we do not use them since they only cover about 90% of the REA value for wage and salary farm employment. As a result, IMPLAN has developed procedures to estimate employment and income by commodity and county. These estimates of employment and income are then used to distribute the total farm employment value given by the REA data. For employment, we use a combination of farm counts by commodity from the latest Census of Agriculture (as an indication of proprietors) and employment-to-output relationships from the BEA Benchmark I-O (which have the commodity detail) to get a first estimate of employment by commodity. These are controlled to U.S. REA “Farm Total” numbers for the current data year. The resulting U.S. relationships to output are then applied to state output values to derive state employment numbers, which are then controlled to each state’s REA “Farm Total”. Notice that this method involves both the Census of Agriculture and the BEA Benchmark, both of which were new this year.
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